On the surface roughness of a braidplain in an Alpine proglacial area

Abstract:

Surface roughness is a crucial parameter of studies concerning (paleo) flood peak discharge estimation and related factors (cf. stream power). Usually, the analysis requires preliminary knowledge of grain size distribution of the study site. However, in some cases this is impractical, especially when investigating large areas, or even impossible due to inaccessibility. In addition, the particles in the channel are usually hidden by other particles or incorporated into finer sediment. Therefore, removing particles from the channel bottom is not suitable, because it falsifies the results.

Here, the application of noninvasive terrestrial laser scanning (TLS) offers new possibilities. The indirect recording of the surface leads to a significant reduction of the workload. Furthermore, form roughness and burial/imbrication are taken into account. However, there are some disadvantages in using TLS. The resolution of the TLS data is a limiting factor when defining surface roughness, because coarseness at finer detail will not be captured at lower resolution (Baewert et al. 2014). There are numerous other factors, which may alter the results. We would like to further understand how the noise associated with TLS data alters the outcome and whether the interpolation method has an influence.

This study focuses on the latter two issues. For this purpose, a braidplain in the forefield of the glacier Gepatschferner in Austria was surveyed using a terrestrial laser scanner. The images were taken from different angles and with different resolutions. Subsequently, the outliers are removed from the point cloud in order to investigate the influence of the noise. Thinning the point cloud is another method used to understand the effects of the point density.

References

Baewert, H., Bimböse, M., Bryk, A., Rascher, E., Schmidt, K.-H. & Morche, D. (2014): Roughness determination of coarse grained alpine river bed surfaces using Terrestrial Laser Scanning data. – Zeitschrift für Geomorphologie N.F. 58(1): 81–95. Doi: 10.1127/0372-8854/2013/S-00127 .