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A prediction model for horizontal run-out distance of landslides triggered by Wenchuan earthquake
Authors:Changwei Yang  Jianjing Zhang  Ming Zhang
Institution:2. Department of Civil Engineering, Southwest Jiaotong University, Chengdu, 610031, China
1. Ministry of Education, Key Laboratory of High-speed Railway Engineering (Southwest Jiaotong University), Chengdu, China
3. Zhengzhou Zhonghe Geotechnical Engineering Co., LTD, Zhengzhou, China
Abstract:The peak ground acceleration (PGA), the volume of a sliding mass V, the height of a mountain H L and the slope angle θ of a mountain are four important parameters affecting the horizontal run-out distance of a landslide L. Correlations among them are studied statistically based on field investigations from 67 landslides triggered by the ground shaking and other factors during the Wenchuan earthquake, and then a prediction model for horizontal run-out distance L is developed in this study. This model gives due consideration to the implications of the above four parameters on the horizontal run-out distance L and the validity of the model is verified by the Donghekou and Magong Woqian landslides. At the same time, the advantages of the model are shown by comparing it with two other common prediction methods. The major findings drawn from the analyses and comparisons are: (1) an exponential relationship exists between L and log V, L and log H L, L and log PGA separately, but a negative exponential relationship exists between L and log tanθ, which agrees with the statistical results; and (2) according to the analysis results of the relative relationship between the height of a mountain (H) and the place where the landslides occur, the probabilities at distances of 2H/3-H, H/3-2H/3, and 0-H/3 are 70.8%, 15.4%, and 13.8%, respectively, revealing that most landslides occurred at a distance of H/2-H. This prediction model can provide an effective technical support for the prevention and mitigation of landslide hazards.
Keywords:Wenchuan earthquake  landslides  run-out distance  prediction model  relationship
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