Flow-Pathway Dependent Estimation of Sedimentation Integrated over a Hydrograph

The ability to predict and understand where and how frequently particular size classes of particles deposit on a floodplain has important implications for nutrient cycling and mitigation of legacy pollutants associated with sediment. A straightforward model to understand the physical processes underpinning floodplain deposition could better inform floodplain management and restoration efforts. In this work we present a model to predict grain-size specific sedimentation along flow pathways on a floodplain and apply this model to the South River in Virginia, a river-floodplain system with decades of sediment data collected in response to mercury pollution. We generated a 2D HEC-RAS model of the South River from aerial lidar data. From the model we extracted velocity and shear stress across inundated areas of the floodplain at various flows. Flow paths from the channel to discrete points on the floodplain were determined from the velocity field generated by the model for each flow. Along the flow paths, we computed a Rouse number from shear stress and grain size to then estimate which size particles can transport past or deposit at individual points. We then integrated the sedimentation results over a long-term hydrograph to estimate the grain size distribution at each point based on frequency of deposition and compare these results with the measured data. Overall, this work provides a process-based tracking of sediment transport/deposition on floodplains to better understand sediment-related dynamics on floodplains.