摘要：Surface roughness influences the release of avalanches and thedynamics of rockfall, avalanches and debris flow, but it is often notobjectively implemented in natural hazard modelling. For two study areas, atreeline ecotone and a windthrow-disturbed forest landscape of the EuropeanAlps, we tested seven roughness algorithms using a photogrammetric digitalsurface model (DSM) with different resolutions (0.1, 0.5 and 1 m) anddifferent moving-window areas (9, 25 and 49 m2). Thevector ruggedness measure roughness algorithm performed best overall in distinguishing betweenroughness categories relevant for natural hazard modelling (including shrubforest, high forest, windthrow, snow and rocky land cover). The results with1 m resolution were found to be suitable to distinguish between theroughness categories of interest, and the performance did not increase withhigher resolution. In order to improve the roughness calculation along thehazard flow direction, we tested a directional roughness approach thatimproved the reliability of the surface roughness computation in channelisedpaths. 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 thetwo study areas. Surface roughness above a treeline, which in comparison tothe forest is not represented within the RAMMS, is therefore underestimated.We conclude that using DSM-based surface roughness in combination with DTM-based surface roughnessand considering the directional roughness is promising for achieving betterassessment of terrain in an alpine landscape, which might improve the naturalhazard modelling.
