کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4676666 | 1347775 | 2007 | 20 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Revisiting statistical–topographical methods for avalanche predetermination: Bayesian modelling for runout distance predictive distribution Revisiting statistical–topographical methods for avalanche predetermination: Bayesian modelling for runout distance predictive distribution](/preview/png/4676666.png)
Return period is a classical tool for avalanche hazard mapping but is often poorly defined. To reduce ambiguity, high quantiles of a given quantity should be preferred. Inspired by the statistical–topographical “Norwegian” approaches and concepts developed by Ancey and Meunier, this paper presents a new method for computing the predictive distribution of snow avalanche runout distances. We evaluate the uncertainties associated with design values using a very simple propagation operator and minimal statistical hypotheses. Only release and runout altitudes are necessary, allowing the model to work with the French historical avalanche database.We propose a stochastic model flexible enough to reasonably capture avalanche data variability and to express inter-variable correlations. The Bayesian framework facilitates parameter inference and allows taking estimation error into account for predictive simulations.
Journal: Cold Regions Science and Technology - Volume 49, Issue 1, July 2007, Pages 88–107