OBSERVATIONS OF SEDIMENT TRANSPORT IN A RECENTLY BURNED WATERSHED USING TERRESTRIAL LASER SCANNING

Sediment transport rates are known to be significantly higher from recently burned watersheds than from nearby unburned basins with similar characteristics. While the physical and chemical changes that occur to surficial materials during wildfire and produce these accelerated rates are relatively well defined, the fine-scale spatial and temporal patterns of sediment transport are not as well understood. Terrestrial laser scanning (TLS) methods, when combined with robust survey control, provide the means to produce high-resolution digital elevation models (DEMs) from which changes in surface topography at multiple spatial scales can be determined. This information can be used to improve modeling and prediction of sediment transport processes. Here, we present the changes in pre- and post-rainstorm topography to assess post-fire sediment transport processes in a 9700 m² watershed near Santa Barbara, California.

Two TLS surveys documented pre- and post-storm conditions. TLS data were used to generate 1-cm resolution DEMs, from which changes in topography were calculated and sediment volumes derived. Between surveys 122 m³ of material was eroded in response to two small (< 1 year recurrence) rainstorms. We compared the distribution of sediment removed from hillslopes, gullies and stream channels, and found that the hillslopes provided the majority (96%) of the total material removed from the basin. We also assessed sediment transport along a flow path extending from the drainage divide to the basin outlet. Here, sediment transport was largely controlled by local physical conditions and morphology, such as the convergence of large rill networks, lateral or vertical confinement by bedrock, and the type of surficial material. The complexity of the patterns of sediment transport at fine spatial and temporal scales suggests that future models utilizing high-resolution models of topographic change will need to include equally fine-scale descriptions of surface properties when attempting to predict the magnitude and patterns of sediment transport. Despite the inherent complexity in this type of geomorphic system, TLS can provide a benchmark dataset from which highly refined models that assess the influence of various local conditions on sediment transport rates and patterns may be developed.