Inferring spatial variations in velocity profiles and bed geometry of natural debris flows based on discharge estimates from high-frequency 3D LiDAR point clouds; Illgraben, Switzerland

¹ ETH Zürich, Department of Earth Sciences, Engineering Geology, 8092 Zurich, Switzerland
² Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland

^* Corresponding author: raffaele.spielmann@erdw.ethz.ch

Abstract

More detailed field measurements are required for a better understanding of surging debris flows. In this work, we analyze a debris flow at the field-scale using timelapse point clouds from a high-resolution, high-frequency 3D LiDAR sensor, which has been installed over a check dam on the fan of the Illgraben catchment in Switzerland. In our investigations, we manually measured the front velocity and tracked individual features such as large boulders and woody debris over a 25 m long channel segment. We observed a change in the front velocity as well as a difference in the velocity of large boulders and woody debris (v_boulder ≈ 0.6 v_wood) during the second surge of the event. We also estimated the discharge for different closely spaced channel sections based on automated measurements of the cross-sectional area and the surface velocity, which enabled us to infer spatial variations in the bed geometry and the velocity profile. From the discharge estimates, we then derived the volume of this event. Over the course of the next year, the amount of field-scale LiDAR data from the Illgraben will increase substantially and allow for an even more detailed analysis of fundamental debris-flow processes.