English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

An innovative approach for the analysis and interpretation of snow avalanche simulation in three dimensional terrain is presented. Snow avalanche simulation software is used as a supporting tool in hazard mapping. When performing a high number of simulation runs the user is confronted with a considerable amount of simulation results. The objective of this work is to establish an objective, model independent framework to evaluate and compare results of different simulation approaches with respect to indicators of practical relevance, providing an answer to the important questions: <i>how far</i> and <i>how destructive</i> does an avalanche move down slope. For this purpose the Automated Indicator based Model Evaluation and Comparison (AIMEC) method is introduced. It operates on a coordinate system which follows a given avalanche path. A multitude of simulation runs is performed with the snow avalanche simulation software SamosAT (Snow Avalanche MOdelling and Simulation – Advanced Technology). The variability of pressure-based run out and avalanche destructiveness along the path is investigated for multiple simulation runs, varying release volume and model parameters. With this, results of deterministic simulation software are processed and analysed by means of statistical methods. Uncertainties originating from varying input conditions, model parameters or the different model implementations are assessed. The results show that AIMEC contributes to the interpretation of avalanche simulations with a broad applicability in model evaluation, comparison as well as examination of scenario variations

A novel approach to evaluate and compare computational snow avalanche simulation