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The forced vortex equation, based on the cross-stream inclination of a flow surface as it passes through a bend, is a common approach to estimating debris flow velocities. Here, we present the preliminary results of a study of superelevation and the correction factor k, used to adapt the forced vortex equation to debris flows, based on data from the Illgraben torrent in Switzerland. The definition of the radius of curvature, a factor in the calculation of superelevation velocities, is not found to exercise a large influence on the calculated velocities when using high resolution aerial images, with the choice of cross-section location and k-factor exercising a more significant influence. The k-factors found here fall within the range previously reported in the literature, ranging from approximately 1 to 7, and a previously suggested non-linear relationship with Froude numbers is evident in the dataset. Following the debris flow season of 2022, the study will be continued with additional debris flow events and the investigative methods will be extended to include high-resolution LiDAR sensors installed along the Illgraben torrent.

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 (vboulder ≈ 0.6 vwood) 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.

In-situ measurements of debris-flow properties are crucial for understanding their movement mechanisms and quantifying their impact. Here we present the first results of a field monitoring campaign, at Illgraben, Switzerland, to measure debris-flow parameters using high temporal (10 Hz) and spatial resolution LiDAR sensors at several locations along the channel. The point cloud data is projected onto video images to enhance visualization and aid in the interpretation of the measurements. We process the data using machine vision and deep learning based algorithms, and show that this system can accurately measure front and flow surface velocity, flow depth and bed elevation change, as well as the size, style of motion (e.g. rotating or floating without rotation) and trajectories of individual particles. This system thus provides a promising new method for inferring the internal dynamics of debris flows.

The volume of a debris flow is a critical parameter in hazard analysis, yet accurate estimates of volume are often unavailable due to mixing with larger rivers at the downstream end of alluvial fans. We describe a method to calculate the volume of debris flows using flow depth data collected at a check dam, using a Manning friction relation to describe the velocity of the debris flow as a function of flow depth, and the geometry of the channel cross section. The method is evaluated using a published data set from the USGS debris-flow flume where event volume and stage information have been accurately measured, and results in volume estimates either somewhat smaller than or up to 50% larger than observed volumes. We further demonstrate the method to single-surge and a multiple-surge debris flows observed at Illgraben.

Accurate debris-flow modelling depends on the ability to simulate surging and pulsing behaviour. However, our understanding of these phenomena is starved of observational constraints. Here we propose the use of seismic measurements, which resolve the arrival of coarse-grained roll wave fronts in debris flows at Illgraben, Switzerland. Roll waves likely play a key role in flow pulses but are typically only observed with point measurements like depth gauges. We compare in-torrent force plate measurements with near-torrent seismic records and discuss how these data can test existing roll wave theories.