Field Validation of the Superelevation Method for Debris-Flow Velocity Estimation Using High-Resolution Lidar and UAV Data

Abstract

Estimating flow velocities is key to assessing hazards associated with debris flows. One approach to post-event velocity estimation is the superelevation method, which uses debris-flow mudlines to measure the cross-channel surface inclination, or superelevation, produced by centripetal forces acting on the flow in a bend. Flow velocities are then calculated using a subjective parameterization of the forced vortex equation modified to include a debris-flow specific correction factor. Subjective parameterization of this equation leads to substantial variability and uncertainty in the resulting flow velocities. We present an analysis of the reliability of the superelevation method using a large UAV-based data set of 14 debris flows with front velocities of ∼0.8–6.5 m s−1 and cross-channel surface inclinations of ∼0.6–8.5°, as well as a validation for a single debris flow measured using high-resolution, high-frequency 3D lidar data fused to video imagery. The validation event indicates that when the flow surface inclination can be measured directly, the forced vortex equation produces excellent results without needing a correction factor for Froude numbers ranging from 0.7 to 1.5. This finding indicates that the main challenge with the superelevation method lies in obtaining accurate measurements of superelevation from the mudlines, and that a correction factor may serve to compensate for measurement difficulties rather than variable flow properties. For very small and highly subcritical flows, the superelevation method may generate a large overestimation of flow velocities.