Rock and Roll: Passive and automated sensing of fluvial sediment and wood transport

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Fluvial bedload is a fundamental process by which coarse sediment is transferred through landscapes by fluvial action. Large wood is a major component of many rivers, but its influence on bedload transport is poorly understood. Rivers across the western USA are currently experiencing increased wood loading due to infestation of forests by the mountain pine beetle over the past decade. This project will investigate the impact of increased wood loading on bedload sediment transport dynamics in a stream within an infected forest. The project will apply passive radio tracer technology in which individual grains/wood pieces are tagged with Passive Integrative Transponders (PIT) to track bedload and wood transport. Studies using this technology have shown that bed- particles move like a random walk model with intermittent periods of movement followed by long periods of rest (Bradley and Tucker, 2012). The project will acquire data on the impact of wood on bed-particle rest intervals and travel distances for the first time. Secondly, the project will apply and develop unmanned aerial vehicles (UAVs) to quantify changes in wood loading to the stream and channel geomorphology. It particular, it will develop technology to aid the use of UAVs in forested environments with tight flying corridors.The student will be part of a large scale PIT tracer experiment of bedload sediment transport in St Louis Creek, an alpine stream in Fraser Experimental Forest (FEF), Colorado, USA. In August 2016, G. Bennett and S. Ryan seeded 1000 PIT tagged rocks in the stream. An initial survey one year later found 90% of the rocks, with 30% of these showing movement from their initial seed location to up to 100 m along the river bed. The student will update and analyze a growing database of sediment transport and wood recruitment - from the seeded site and other subwatersheds at FEF (e.g., Ryan et al. 2015). The student will compare data acquired on sediment transport with flow data in order to establish hydrologic controls on sediment transport. Furthermore, they will use an Unmanned Aerial Vehicle (UAV) to assess changes in wood loading to the stream, channel geomorphology and structural controls on particle movement. The student will work with Gerard Parr and colleagues in Computer Sciences at UEA to develop UAV anti-collision technology for flying through forested catchments (e.g. Luo et al., 2013).Bradley, D.E., and Tucker, G.E., 2012. Measuring gravel transport and dispersion in a mountain river using passive radio tracers. Earth Surface Processes and Landforms, DOI: 10.1002/esp.3223Ryan, S.E., Bishop, E.L., and Daniels, J.M. 2014. Influence of large wood on channel morphology and sediment storage in headwater mountain streams, Fraser Experimental Forest, Colorado. Geomorphology 217:73-88. doi:10.1016/j.geomorph.2014.03.046 C. Luo, S. I. McClean, G. Parr, L. Teacy and R. De Nardi, "UAV Position Estimation and Collision Avoidance Using the Extended Kalman Filter," in IEEE Transactions on Vehicular Technology, vol. 62, no. 6, pp. 2749-2762, July 2013.doi: 10.1109/TVT.2013.2243480