Preprints
https://doi.org/10.5194/egusphere-2026-485
https://doi.org/10.5194/egusphere-2026-485
13 Feb 2026
 | 13 Feb 2026
Status: this preprint is open for discussion and under review for The Cryosphere (TC).

Comparing high spatial and temporal resolution snow depth measurements and modelling results in an avalanche release area

Pia Ruttner, Nora Helbig, Annelies Voordendag, Andreas Wieser, and Yves Bühler

Abstract. Accurate representation of snow depth distribution within avalanche release areas is critical for understanding avalanche formation and supporting operational avalanche mitigation measures. In this study, we investigate the spatial variability of snow depth in an avalanche release area using high spatial (0.5 m) and temporal (hourly) resolution measurements obtained from a low-cost terrestrial laser scanner (TLS). The TLS data provide detailed snow depth distributions for three selected snow accumulation events, including sub-event evolution, enabling an event- and sub-event-based analysis of snow deposition patterns.

We assess the ability of three terrain-based modelling approaches to reproduce observed snow depth patterns: the topographic position index (TPI), a wind shelter index (Sx), and a statistical preferential deposition model. The results indicate that simple topography-derived indices generally achieve the highest correlations with measured snow depths across most events. The correlations reach maximum values of up to 0.57 (Spearman correlation), indicating that topographic predictors are able to partially, but not fully explain the present snow depth variability at sub-metre spatial resolution.

These findings emphasise the dominant role of local terrain in shaping snow accumulation patterns within avalanche release areas, demonstrate the value of TLS data for event-scale model evaluation, and highlight the potential to complement incomplete observations using simple terrain-based modelling approaches. The collection of additional snow depth distribution data with such high spatio-temporal resolution in different avalanche release areas would enable the development of machine learning approaches in the future. This fosters event-based avalanche forecasting by improving the spatial completeness of snow depth observations in complex terrain at slope scale.

Competing interests: At least one of the (co-)authors is a member of the editorial board of The Cryosphere.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Pia Ruttner, Nora Helbig, Annelies Voordendag, Andreas Wieser, and Yves Bühler

Status: open (until 27 Mar 2026)

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Pia Ruttner, Nora Helbig, Annelies Voordendag, Andreas Wieser, and Yves Bühler
Pia Ruttner, Nora Helbig, Annelies Voordendag, Andreas Wieser, and Yves Bühler

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Short summary
The spatial variability of snow depth distribution in avalanche release areas is key for avalanche forecasting but is strongly influenced by the interaction of wind with the terrain. We generate maps of high resolution snow depth changes during three snowfall events by using low-cost terrestrial laser scanner measurements and compare them to the results of selected snow depth distribution models. We show that basic terrain derivations have the highest correlations to our measurement results.
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