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http://dx.doi.org/10.7843/kgs.2015.31.6.59

A Statistical Mobilization Criterion for Debris-flow  

Yoon, Seok (Dept. of Civil and Environmental Eng., KAIST)
Lee, Seung-Rae (Dept. of Civil and Environmental Eng., KAIST)
Kang, Sin-Hang (Dept. of Civil and Environmental Eng., KAIST)
Park, Do-Won (Dept. of Civil and Environmental Eng., KAIST)
Publication Information
Journal of the Korean Geotechnical Society / v.31, no.6, 2015 , pp. 59-69 More about this Journal
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.
Keywords
Mobilization criterion; Landslide; Debris-flow; Logistic regression analysis;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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