Joint Probability Prediction Model of Rainfall Triggered Landslides and Debris Flows


The rainfall induced landslides and debris flows are the major disasters in China, as well in Europe, South America, Japan and Australia. This paper proposes a new type of joint probability prediction model—Double Layer Nested Multivariate Compound Extreme Value Distribution (DLNMCEVD) to predict landslides and debris flows triggered by rainfall. The outer layer of DLNMCEVD is predicting the joint probabilities of different combinations for rainfall characteristics, air temperature and humidity, which should be considered as external load factors with geological and geotechnical characteristics as resistance factors for reliability analysis of slope stability in the inner layer of model. For the reliability and consequence analysis of rainfall-induced slope failure, the Global Uncertainty Analysis and Global Sensitivity Analysis (GUA & GSA) should be taken into account for input-output iterations. Finally, based on the statistics prediction by DLNMCEVD, the geological hazards prevention alarm and regionalization can be provided in this paper.

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G. Liu, D. Liu, T. Li, F. Wang and T. Zou, "Joint Probability Prediction Model of Rainfall Triggered Landslides and Debris Flows," Open Journal of Geology, Vol. 2 No. 2, 2012, pp. 103-110. doi: 10.4236/ojg.2012.22011.

Conflicts of Interest

The authors declare no conflicts of interest.


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