Comment on nhess-2022-97

Natural hazard models need accurate digital elevation models (DEMs) to simulate mass movements on three-dimensional terrain. A variety of platforms (terrestrial, drones, aerial, satellite) and sensor technologies (photogrammetry, LiDAR, interferometric synthetic aperture radar) are used to generate DEMs at a range of spatial resolutions with varying accuracy. As the availability of high-resolution DEMs continues to increase and the cost to produce DEMs continues to fall, hazard modellers must often choose which DEM to use for their modelling. Here we use current state-of-the-art sensor technologies (satellite photogrammetry and terrestrial LiDAR) to generate high-resolution DEMs and test the sensitivity of the Rapid Mass Movements Simulation software (RAMMS) to the DEM source and spatial resolution for simulating a large and complex snow avalanche along Milford Road in Fiordland, Aotearoa New Zealand. Holding the RAMMS parameters constant while adjusting the source and spatial resolution of the DEM reveals how differences in terrain representation between the satellite photogrammetry and terrestrial LiDAR DEMs (2 m spatial resolution) affect the reliability of the simulation estimates (e.g., maximum core velocity, powder pressure, final debris pattern). At the same time, coarser representations of the terrain (5 m, 15 m spatial resolution) produce simulated avalanches that run too far and produce a powder cloud that is too large, though with lower maximum impact pressures, compared to the actual event. The complex nature of the alpine terrain in the avalanche path (steep, rough, rock faces, tree-less) made it a suitable location to specifically test the model sensitivity to digital surface models (DSMs) where both the ground and above-ground features on the topography are included in the elevation model. Combined with the nature of the snowpack in the path (warm, deep with a steep elevation gradient) lying on a bedrock surface and plunging over a cliff, RAMMS performed well in the challenging conditions when using the high spatial-resolution 2 m DSM.