High-resolution 3D LiDAR measurements of natural debris flows at sub-second intervals; Illgraben, Switzerland

Debris flows are extremely rapid, flow-like landslides composed of fine and coarser-grained components, boulders, woody debris as well as water. They are characterized by large impact forces as well as long runout distances and are one of the most dangerous types of mass movements in mountainous regions. More detailed field-scale measurements of hazard-related parameters in natural debris flows are required to better understand the fundamental mechanisms governing their motion and, ultimately, reduce the associated risks.

In the present work, we analyzed two debris-flow events using timelapse point clouds from a high-resolution, high-frequency 3D LiDAR sensor (Ouster OS1), which we installed at the WSL debris-flow monitoring station in the Illgraben catchment (Valais, Switzerland). We developed and applied both manual and automated algorithms to derive critical hazard-related parameters – including front and surface velocities, cross-sectional area, discharge and event volume – at an unprecedented level of detail.

In both events, we observed that surface velocities measured directly behind the front exceeded the front velocity (by a factor of 1.75x on average), which likely led to the formation of the bouldery front. We further found that different objects traveled at systematically different velocities: large, rolling boulders were moving at 0.6–0.8 the velocity of floating woody debris during both analyzed events. This observation was likely caused by these different objects sampling the vertical velocity profile at different depths, and thus provided quantitative information about the shape of the velocity profile.

We further applied automated surface velocity estimation techniques as well as automated cross-sectional area measurements to derive the discharge over time and in space at three different, closely spaced channel sections upstream of a check dam. We accounted for potential changes in the shape of the channel bed by considering different “channel geometry scenarios” (based on pre-event and post-event scans) and included presumed changes in the vertical velocity profile – based on our findings mentioned above – in our discharge derivation. We assessed the reliability of these different scenarios by comparing the discharge values at different sections, which allowed us to infer potential changes in the channel bed geometry.

The LiDAR data analyzed in this work is unique because it allows for a truly 3D, high-resolution investigation of moving debris flows at sub-second intervals. The developed methods will be applied to LiDAR data from additional monitoring stations and events at the Illgraben, which should allow for further inference into the internal dynamics of debris flows. Eventually, this might enhance our understanding of the fundamental debris-flow mechanisms, help to optimize numerical as well as empirical modeling approaches, improve hazard mitigation in general and reduce the risk posed by flow-like landslides in the future.