Abstract. Surface roughness influences the release of avalanches and the dynamics of rockfall, avalanches and debris flow, but is often not objectively implemented in natural hazard modelling. For two study… Click to show full abstract
Abstract. Surface roughness influences the release of avalanches and the dynamics of rockfall, avalanches and debris flow, but is often not objectively implemented in natural hazard modelling. For two study areas, a treeline ecotone and a windthrow disturbed forest landscape of the European Alps, we tested seven roughness algorithms using a digital surface models (DSM) with different resolutions (0.1, 0.5 and 1 m) and different moving window areas (9 m−2, 25 m−2 and 49 m−2). The vector ruggedness measure roughness algorithm performed best overall in distinguishing between roughness categories relevant for natural hazard modelling (including shrub forest, high forest, windthrow, snow and rocky land-cover). The results with 1 m resolution were found to be suitable to distinguish between the roughness categories of interest, and the performance did not increase with higher resolution. In order to improve the roughness calculation along the hazard flow direction, we tested a directional roughness approach that improved the reliability of the surface roughness computation in channelized paths. We simulated avalanches on a different elevation models to observe a potential influence of a DSM and a digital terrain model (DTM). Accounting for surface roughness based on a DSM instead of a DTM resulted not only in clearly higher roughness values of forest and shrub vegetation, but also in longer simulated avalanche runouts by 16–27 % in the two study areas. We conclude that directional roughness is promising for achieving better assessments of terrain topography in alpine landscapes and that applying an approach using DSM-based surface roughness could improve natural hazard modelling.
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