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Probabilistic modeling of rockfall trajectories: a review

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Abstract

Probabilistic approaches are widely adopted for the modeling of rockfall trajectories, but are not widely discussed in the literature. This paper aims to help fill this gap by reviewing probabilistic models of rockfall trajectories, while providing some perspectives for future study. We first make it clear that, from a theoretical point of view, the probabilistic approach is necessitated by both the ontic (inherent) uncertainty associated with rockfalls and the epistemic (information) uncertainty associated with numerical modeling. The review suggests that there may be the potential to improve the probabilistic modeling of rockfall trajectories in various aspects, including the systematic probabilistic modeling criterion, the random sampling approaches employed for probabilistic variables, the probabilistic modeling of rock shape, and the probabilistic prediction of rockfall intensity. However, there are still some open questions regarding the promotion of probabilistic modeling in practice. It is not clear whether probabilistically treating all of the variables of rockfall trajectory model with reasoned distributions will lead to significantly improved results, or whether the improvements will be great enough (given the difficulties and costs involved) that it is worth quantifying all of the uncertainties involved in rockfall trajectory modeling. The answers to these questions can be found in the practice of probabilistic modeling itself.

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Acknowledgments

This study was supported by the National Science Foundation of China (nos. 41272354 and 41072241), the One Hundred Talents Program of the Chinese Academy of Sciences, and the Railway Ground Hazard Research Program (RGHRP) of Canada. We thank the authors of CRSP-3D for permitting free online access of the program, and Rocscience Inc., Dr. Spang GmbH, and RocPro3D for providing trial versions of their software packages. The comments of two anonymous reviewers were very helpful for improving the manuscript. We would also like to express our sincere appreciation to Ms. Louise Vick for improving the writing.

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  1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing, 100101, China

    Langping Li & Hengxing Lan

  2. Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Canada

    Hengxing Lan

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Li, L., Lan, H. Probabilistic modeling of rockfall trajectories: a review. Bull Eng Geol Environ 74, 1163–1176 (2015). https://doi.org/10.1007/s10064-015-0718-9

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