Lidar-aided Channelized Debris Flow Numerical Modelling

The accuracy of numerical simulations for debris flows is critically dependent on the precision of terrain morphology data, regardless of the mechanical model employed. However, digital elevation models (DEMs) derived from satellite imagery and unmanned aerial vehicle (UAV) photogrammetry often exhibit limitations in mountainous regions, particularly in areas characterized by narrow channels and significant elevation differences. Additionally, air- and space-based DEMs are often insufficient for capturing channel bed information in locations where the view is obstructed by vegetation or sidewalls. This challenge is especially pronounced for channelized debris flows, where channel morphology significantly influences the flow dynamics. To address this bottleneck, we developed a ground-based channel morphology detection system utilizing simultaneous localization and mapping (SLAM) technology. The advanced SLAM-based channel detection and mapping system (AscDAMs) enables the acquisition of accurate, high-resolution channel morphology data, including channel DEMs and typical cross-sections (TCS). In this study, we applied the AscDAMs system to the debris flow event that occurred on June 26, 2023, in Banzi Gully, Wenchuan County, Sichuan Province, China. By comparing DEMs derived from satellite imagery, UAV photogrammetry, and AscDAMs, we found that the AscDAMs-based DEM exhibited superior resolution, capturing finer-scale morphological details and achieving higher accuracy. Furthermore, numerical simulations using different DEMs were conducted and compared with event video data. Results demonstrated that the simulated flow field generated from the AscDAMs-based DEM showed the highest consistency with the flow field observed in the video. These improved simulation outcomes provide deeper insights into the dynamic processes of debris flow events and contribute to more effective risk management of such hazards.