Multiscale analysis of surface roughness for the improvement of natural hazard modelling
<p>Surface roughness influences the release of avalanches and the dynamics of rockfall, avalanches and debris flow, but it 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,...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/d7f6a0f17468408687bea4aa796d8d86 |
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| Sumario: | <p>Surface roughness influences the release of avalanches and the
dynamics of rockfall, avalanches and debris flow, but it 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 photogrammetric digital
surface model (DSM) with different resolutions (0.1, 0.5 and 1 m) and
different moving-window areas (9, 25 and 49 m<span class="inline-formula"><sup>2</sup></span>). The
<i>vector ruggedness measure</i> 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 channelised
paths. We simulated avalanches on different elevation models (lidar-based)
to observe a potential influence of a DSM and a digital terrain model (DTM)
using the simulation tool Rapid Mass Movement Simulation (RAMMS). In this way,
we accounted for the surface roughness based on a DSM instead of a DTM,
which resulted in shorter simulated avalanche runouts by 16 %–27 % in the
two study areas. Surface roughness above a treeline, which in comparison to
the forest is not represented within the RAMMS, is therefore underestimated.
We conclude that using DSM-based surface roughness in combination with DTM-based surface roughness
and considering the directional roughness is promising for achieving better
assessment of terrain in an alpine landscape, which might improve the natural
hazard modelling.</p> |
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