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A Statistical Mobilization Criterion for Debris-flow

통계 분석을 통한 산사태 토석류 전이규준 모델

  • Received : 2015.05.06
  • Accepted : 2015.06.22
  • Published : 2015.06.30

Abstract

Recently, landslide and debris-flow disasters caused by severe rain storms have frequently occurred. Many researches related to landslide susceptibility analysis and debris-flow hazard analysis have been conducted, but there are not many researches related to mobilization analysis for landslides transforming into debris-flow in slope areas. In this study, statistical analyses such as discriminant analysis and logistic regression analysis were conducted to develop a mobilization criterion using geomorphological and geological factors. Ten parameters of geomorphological and geological factors were used as independent variables, and 466 cases (228 non-mobilization cases and 238 mobilization cases) were investigated for the statistical analyses. First of all, Fisher's discriminant function was used for the mobilization criterion. It showed 91.6 percent in the accuracy of actual mobilization cases, but homogeneity condition of variance and covariance between non-mobilization and mobilization groups was not satisfied, and independent variables did not follow normal distribution, either. Second, binomial logistic analysis was conducted for the mobilization criterion. The result showed 92.3 percent in the accuracy of actual mobilization cases, and all assumptions for the logistic analysis were satisfied. Therefore, it can be concluded that the mobilization criterion for debris-flow using binomial logistic regression analysis can be effectively applied for the prediction of debris-flow hazard analysis.

최근 들어 집중호우로 인한 산사태 및 토석류 피해가 종종 발생하고 있다. 이에 따라 산사태 재해 예측에 관한 연구 중 산사태 민감도 분석과 토석류 위험도 분석 관련 연구는 활발하게 진행되어 왔지만, 사면 지역에 적용하기 적합한 전이 분석 관련 연구는 부족한 실정이다. 본 연구에서는 판별분석과 로지스틱 회귀 분석과 같은 통계적 방법을 이용하여 실제 토석류가 발생했던 지역에서 추출한 지형학적 인자, 지질학적 인자 등을 토대로 토석류 전이규준을 제시하였다. 10개의 지형학적 및 지질학적 인자가 독립변수로 사용되었으며 실제 466개소(비전이: 228개소, 전이: 238개소)의 토석류 비전이 및 전이 데이터가 수집되었다. 우선, Fisher의 판별 분석이 수행되었으며, 수행 결과 실제경우와 91.6%의 분류 정확도를 보였다. 하지만 전이와 비전이 두 그룹간의 공분산 동질성이 만족되지 않았으며 또한 독립변수들이 정규분포를 보이지도 않았다. 두 번째로 이항 로지스틱 회귀분석이 수행되었으며, 분석 결과 92.3%의 분류 정확도를 나타냈으며 모든 통계적 조건들도 유의하게 나타났다. 따라서 이항 로지스틱 회귀 분석을 이용한 전이 규준은 토석류 재해 발생 여부를 예측하는데 효과적으로 사용될 수 있을 것으로 판단된다.

Keywords

References

  1. Ahn, H. (2012), "A Logistic Regression Analysis of Two-way Binary Attribute Data", Journal of the Society of Korea Industrial and Systems Engineering, Vol.35, No.3, pp.118-128. https://doi.org/10.11627/jkise.2012.35.4.118
  2. Berti, M., Genevois, R., Simoni, A., and Tecca, P. R. (1999), "Field Observations of a Debris Flow Event in the Dolomites", Geomorphology, Vol.29, pp.265-274. https://doi.org/10.1016/S0169-555X(99)00018-5
  3. Board on Atmospheric Sciences and Climate (BASC) (2011), America's Climate Choices, The National Academies Press, Wahsington, D.C.
  4. Brayshaw, D. and Hassan, M. A. (2009), "Debris Flow Initiation and Sediment Recharge in Gullies", Geomorphology, Vol.109, pp. 122-131. https://doi.org/10.1016/j.geomorph.2009.02.021
  5. Caine, N. (1980), "The Rainfall Intensity-duration Control of Shallow Landslides and Debris Flows", Geogr. Ann., A62, pp.23-27.
  6. Campbell, R. H. (1975), "Soil Slips, Debris Flows, and Rainstorms in the Santa Monica Mountains and Vicinity, Southern California", Professional Paper 851, U.S. Geologic Survey, Washington, D.C.
  7. Chen, C. Y. and Yu, F. C. (2011), "Morphometric Analysis of Debris Flows and Their Source Areas Using GIS", Geomorphology, Vol. 129, pp.387-397. https://doi.org/10.1016/j.geomorph.2011.03.002
  8. Choi, E. K., Kim, S. W., Lee, Y. C., Lee, K. H., and Kim, I. S. (2013), "Analyzing the Disaster Vulnerability of Mt. Baekdusan Area using Terrain Factors", Journal of the Korean Earth Science Society, Vol.34, No.7, pp.605-614. https://doi.org/10.5467/JKESS.2013.34.7.605
  9. Cokluk, O. (2010), "Logistic Regression : Concept and Application", Theory and Practice, Vol.10, No.3. pp.1397-1407.
  10. Griswold, J. P. and Iverson, R. M., (2008), "Mobility and Statistics and Automated Hazard Mapping for Debris Flows and Rock Avalanches", U.S. Geological Survey Scientific Investigations Report, 2007-5276.
  11. Hosmer, D. W. and Lemeshow, S. (2005), "Applied Logistic Regression", Second Edition, John Wiley &Sons, Incorporation.
  12. Hutchinson, J. N. (2002), Chalk flows from the coastal cliffs of northwest Europe, Reviews in Engineering Geology, 15, 257-302. https://doi.org/10.1130/REG15-p257
  13. Hur, M. and Yang, K. S. (2013), "Multivariate Data Analysis", Hannarae Publishing Corporation.
  14. Iverson, R. M. (1997), "The Physics of Debris Flows", Review of Geophysics, Vol.35, No.3, pp.245-296. https://doi.org/10.1029/97RG00426
  15. Iverson, R. M., Reid, M. E., and Lahusen, R. G. (1997), "Debris-flow Mobilization from Landslides", Annual Review of Earth and Planetary Sciences, 25, pp.85-138. https://doi.org/10.1146/annurev.earth.25.1.85
  16. Jeon, K. H., Lee, S. R., and Oh, G. D. (2010), "Probabilistic Analysis of Unsaturated Soil Properties for Korean Weathered Granite Soil", 24th KKCNN Symposium on Civil Engineering, Hyogo, Japan.
  17. Johnson, A. M. (1965), "A Model for Debris Flow", Ph.D Thesis, Pennsylvania State Univ., Pennsylvania, America.
  18. Johnson, A. M. and Rodine, J. R. (1984), "Debris Flow", In: Brunsden, D., Prior, D. B.(Editors), Slope Instability, Wiley, Chichestr, UK, pp.257-361.
  19. Kang, S. H,, Lee, S. R., Nikhil, V. V., and Park, J. Y. (2015), "Analysis of Differences in Geomorphological Characteristics on Initiation of Landslides and Debris flows", Journal of Korean Society of Hazard Mitigation, Vol.15, No.2, pp.1-10. https://doi.org/10.9798/KOSHAM.2015.15.2.1
  20. Kim, H. C. (2013), "Statistical Analysis by Self-study", Hakjisa Publishing Corporation.
  21. Korea Institute of Geoscience and Mineral Resources (2008), "Development of landslide prediction technology and damage mitigation countermeasures", pp.124-132.
  22. Lee, I. H. (2014), "Easy Flow Regression Analysis", Hannarae Publishing Corporation.
  23. Lee, S. W., Kim, G. H., Yune, C. Y., Ryu, H. J., and Hong, S. J. (2012), "Development of Landslide-risk Prediction Model Through Database Construction", Journal of Korean Geotechnical Society, Vol.28, No.4, pp.23-33. https://doi.org/10.7843/kgs.2012.28.4.23
  24. Lorente, A., Garcia-Ruiz, J. M., Begueria, S., and Arnaez, J. (2002), "Factors Explaining the Spatial Distribution of Hillslope Debris Flows", Mountain Research and Development, Vol.22, No.1, pp.32-39. https://doi.org/10.1659/0276-4741(2002)022[0032:FETSDO]2.0.CO;2
  25. Montrasio, L., Valentino, R., and Losi, G. L. (2011), "Towards a Real-time Susceptibility Assessment of Rainfall-induced Shallow Landslides on a Regional Scale", Natural Hazards Earth Systesm, Vol.11, pp.1927-1947. https://doi.org/10.5194/nhess-11-1927-2011
  26. Moore, I. D. and Wilson, J. P. (1992), "Length-slope Factors for the Revised Universal Soil Loss Equation: Simplified Method of estimation", Journal of soil and water conservation, 47, pp.423-428.
  27. Oh, H. J. (2010), "Landslide Detection and Landslide Susceptibility Mapping using Aerial Photos and Artificial Neural Networks", Korean journal of remote sensing, Vol.26, No.1, pp.47-57. https://doi.org/10.7780/kjrs.2010.26.1.47
  28. Park, D. W. (2014), "Simulation of Landslides and Debris-flows at Regional Scale using Coupled Model", M.S. Thesis, Korea Advanced Institute of Science and Technology, Korea.
  29. Park, D. W., Lee, S. R., Nikhil, N. V., Yoon, S., and Go, G. H. (2014), "Quantitative Assessment of Landslide Susceptibility on a Regional Scale using Geotechnical Databases Developed from GIS-based Maps", Disaster Advances, Vol.7, No.5, pp.25-38.
  30. Phoon, K. K., Santoso, A., and Quek, S. T. (2010), "Probabilistic Analysis of Soil-water Characteristic Curves", ASCE Journal of Geotechnical and Geoenvironmental Engineering, Vol.136, No.3, pp.445-455. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000222
  31. Rickenmann, D. and Zimmermann, M. (1993), "The 1987 Debris Flows in Switzerland: Documentation and Analysis", Geomorphology, Vol.8, No.2-3, pp.175-189. https://doi.org/10.1016/0169-555X(93)90036-2
  32. Ryu, H. J., Shin, J. H., Seo, H. S., Kim, K. H., and Lee, S. W. (2012), "A Model for Evaluation of Debris Flow Risk in a Watershed", Journal of korean society of hazard mitigation, Vol.12, No.4, pp. 66-76.
  33. Shapiro, S. S. and Wilk, M. B. (1965), "An Analysis of Variance Test for Normality (complete samples)", Biometrika, Vol.52, pp. 591-611. https://doi.org/10.1093/biomet/52.3-4.591
  34. Takahashi, T. (1978), "Mechanical Characteristics of Debris Flow", Journal of the Hydraulic Division, Vol.104, pp.1153-1169.
  35. Takahshi, T. (1981), "Estimation of Potential Debris Flows and Their Hazardous Zones: Soft countermeasures for a disaster", Journal of Natural Disaster Science, Vol.3, No.1, pp.57-89.
  36. Van Dine, D. (1996), "Debris Flow Control Structures for Forest Engineering", Research Branch, Ministry of Forests, Victoria, BC Working Pater 22/1996.
  37. Varnes, D. J. (1978), "Slope Movements, Type and Processes", In: Schuster, R. L., Krizek, R. J. (Editors), Landslides Analysis and Control, Special Report 176: Transportation Research Board, National Academy of Sciences, Washington, D.C., pp.11-33.
  38. Wieczorek, G. F., Mandrone, G., and Decola, L. (1997), "The Influence of Hillslope Shape on Debris-Flow Initiation", In: ASCE (editor), First International Conference Water Resources Engineering Division, SanFrancisco, CA, 21-31.
  39. Yoon, S., Lee, S. R., Kim, Y. T., and Go, G. H. (2015), "Estimation of Saturated Hydraulic Conductivity of Korean Weathered Granite Soils Using a Regression Analysis", Geomechanics and Engineering, accepted.
  40. Zou, G. (2004), "A Modified Poisson Regression Approach to Prospective Studies with Binary Data", American Journal of Epidemiology, Vol.159, No.7, pp.702-706. https://doi.org/10.1093/aje/kwh090

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