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Probabilistic prediction of slope failure time
Abstract The inverse velocity method is widely used for slope failure time prediction. In practice, the presence of factors like measurement error, environmental noise, and modeling assumptions may make the predicted failure time different from the actual failure time. While the traditional inverse velocity method can provide useful information about the probable failure time, it does not furnish an estimate about the reliability of the prediction. In this paper, the uncertainties in slope failure time forecast are divided into two categories, i.e., observational uncertainty and model uncertainty. A method is suggested to assess the effect of observational uncertainty on slope failure time prediction through site-specific data based on the maximum likelihood principle. The model uncertainty associated with the inverse velocity method is calibrated based on a database containing 50 landslides with known failure time. A procedure is suggested to predict the probability density function of the slope failure time considering both uncertainties. Two illustrative examples are provided to show that the outcome from the probabilistic method suggested in this paper can be more informative for rational decision making.
Highlights There are both observational uncertainty and model uncertainty involved in slope failure time forecast. Methods are suggested to characterize the above two types of uncertainties. The probability distribution of the slope failure time is derived. Probabilistic prediction of failure time is more consistent with the observed data. Probabilistic prediction of failure time is more informative for decision makers.
Probabilistic prediction of slope failure time
Abstract The inverse velocity method is widely used for slope failure time prediction. In practice, the presence of factors like measurement error, environmental noise, and modeling assumptions may make the predicted failure time different from the actual failure time. While the traditional inverse velocity method can provide useful information about the probable failure time, it does not furnish an estimate about the reliability of the prediction. In this paper, the uncertainties in slope failure time forecast are divided into two categories, i.e., observational uncertainty and model uncertainty. A method is suggested to assess the effect of observational uncertainty on slope failure time prediction through site-specific data based on the maximum likelihood principle. The model uncertainty associated with the inverse velocity method is calibrated based on a database containing 50 landslides with known failure time. A procedure is suggested to predict the probability density function of the slope failure time considering both uncertainties. Two illustrative examples are provided to show that the outcome from the probabilistic method suggested in this paper can be more informative for rational decision making.
Highlights There are both observational uncertainty and model uncertainty involved in slope failure time forecast. Methods are suggested to characterize the above two types of uncertainties. The probability distribution of the slope failure time is derived. Probabilistic prediction of failure time is more consistent with the observed data. Probabilistic prediction of failure time is more informative for decision makers.
Probabilistic prediction of slope failure time
Zhang, J. (author) / Wang, Z.P. (author) / Zhang, G.D. (author) / Xue, Y.D. (author)
Engineering Geology ; 271
2020-03-10
Article (Journal)
Electronic Resource
English
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