Preprints
https://doi.org/10.5194/nhess-2021-85
https://doi.org/10.5194/nhess-2021-85

  24 Mar 2021

24 Mar 2021

Review status: this preprint is currently under review for the journal NHESS.

Multiscale analysis of surface roughness for the improvement of natural hazard modelling

Natalie Brožová1,2,, Tommaso Baggio3,, Vincenzo D'Agostino3, Yves Bühler1, and Peter Bebi1 Natalie Brožová et al.
  • 1WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, 7260 Davos Dorf, Switzerland
  • 2Department of Environmental Systems Science, Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland
  • 3Department of Land, Environment, Agriculture and Forestry, University of Padova, via dell’Università 16, 35020 Legnaro, PD, Italy
  • These authors contributed equally to this work.

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.

Natalie Brožová et al.

Status: open (until 10 May 2021)

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Natalie Brožová et al.

Natalie Brožová et al.

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Short summary
Surface roughness plays a big role in natural hazard processes, but is not always well implemented in natural hazard modelling. The results of our study show, how surface roughness can be useful in representing vegetation and ground structures, which are currently underrated. By including surface roughness into natural hazard modelling, we could better illustrate the processes and thus improve hazard mapping, which is crucial for infrastructure and settlement planning in mountainous areas.
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