Abstract
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.
Highlights
IntroductionThe rainfall-induced landslides and debris flows are the major disasters in South American, Europe as well as in China due to the following facts: The climate of South American, some European counties and China mainly possess the features of hurricane/ typhoon/tropical cyclone, monsoon type and precipitation is concentrated in summer, forming stormy rainfall which is the main inducing factor for landslide and debris flow
The rainfall-induced landslides and debris flows are the major disasters in South American, Europe as well as in China due to the following facts: The climate of South American, some European counties and China mainly possess the features of hurricane/ typhoon/tropical cyclone, monsoon type and precipitation is concentrated in summer, forming stormy rainfall which is the main inducing factor for landslide and debris flow.The resident in mountainous area mainly distributes along valleys on river terraces, diluvia fans and taluses
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
Summary
The rainfall-induced landslides and debris flows are the major disasters in South American, Europe as well as in China due to the following facts: The climate of South American, some European counties and China mainly possess the features of hurricane/ typhoon/tropical cyclone, monsoon type and precipitation is concentrated in summer, forming stormy rainfall which is the main inducing factor for landslide and debris flow. The geological and geo-morphological conditions and the slope failure low have been studied in detail since the territory of Hong Kong is small, and the slope movement and the rainfall are monitored by a net equipped with automatic apparatus. On this basis the correlation of slope failure with rainfall could be established. Targets of the study are focused on scheme of zoning of a certain region according to the relative homogeneity of the geological and geo-morphological conditions as well as the similarity of the failure mechanism and failure type of slopes and establish a theoretically based and practically applicable joint probability prediction model for rainfall induced landslides and debris flows
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