Quantifying snowfall and avalanche release synchronization: A case study

Benoît Crouzy*, Romain Forclaz, Betty Sovilla, Javier Corripio, Paolo Perona

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We quantify the synchronization between snowfall and natural avalanches in relation to terrain properties at the detachment zone. We analyze field statistics of 549 avalanche events in terms of slope, aspect, timing, coordinate, and release area, identified by a georeferencing procedure applied on terrestrial photography. The information from the digital pictures, together with associated meteorological data, provides us with the input needed for model calibration, namely, the magnitude of snowfall, the snow compaction rate, and the timing of precipitation and of avalanche events. Synchronization between snowfall and avalanches is established for different slope categories. We obtain an average probability of release after a snow event of 30% and 16% for the high- and low-slope categories (average slope 44° and 36°, respectively). Using the notion of information entropy, we quantify the uncertainty in predicting avalanche occurrence from a snow event. The steeper slopes correspond to a larger entropy in avalanche prediction. Further, the presented method allows us to establish the return period of avalanches without requiring a long series of data. When considering events regardless of their release depth, the avalanches had a return period of 48 days (higher slopes) and 88 days (lower slopes). Finally, we determine the average daily detachment rate as a function of snow depth and the return period of avalanches as a function of the release depth.

Original languageEnglish
Pages (from-to)183–199
JournalJournal of Geophysical Research: Earth Surface
Volume120
Issue number2
DOIs
Publication statusPublished - 15 Mar 2015
Externally publishedYes

Keywords

  • Georeferencing
  • Image processing
  • Information entropy
  • Model calibration
  • Snow avalanches
  • Stochastic model

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