GSA Connects 2023 Meeting in Pittsburgh, Pennsylvania

Paper No. 130-4
Presentation Time: 2:20 PM

QGG STANLEY A. SCHUMM AWARD: MAPPING ALLUVIAL RIVER BANK EROSION OVER BIWEEKLY TO YEARLY TIME SCALES


NELSON, Mariel, Jackson School of Geosciences, The University of Texas at Austin, 2305 Speedway, Stop C1160, Austin, TX 78712, GOUDGE, Timothy, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78712 and MOHRIG, David, Jackson School of Geosciences, The University of Texas at Austin, 2275 Speedway, Stop C9000, Austin, TX 78712-1722

River bank erosion widens alluvial channels, changes the planform shape of river bends, and causes land loss and property damage. Further, it is an essential process that drives the migration of meandering rivers. Bank erosion is primarily controlled by mechanisms related to the flow of water in the river—during a flood, river stage increases, submerging banks and exposing them to shear stresses sufficient to remove bank material. After a flood, river bank material can fail catastrophically as the steep and saturated river banks lose the buoyant force of the flood water. How do floods of varying magnitudes dictate river bank erosion patterns in a natural river? Here, we use repeat drone-based lidar data to map the subaerial river bank topography of 3.5 km of the ~180 meter-wide, sand-bedded Trinity River in East Texas and examine where and how it changes over time. We use data from nine surveys between April 2022 to May 2023, which captured several small floods within a drought year. The two surveyed river bends show extensive and consistent erosion of bank material. Material erodes via discrete, cohesive failures along the bank that often coalesce. Despite pervasive evidence of erosion between most sets of surveys, the position of the bank line—the mappable break in slope that delineates where the river bank meets the floodplain—rarely changed. Most erosion occurred below the bank line, removing sediment and woody vegetation from the subaerial bank that is exposed during baseflow, after a flood has passed. We explore several ways to analyze erosion patterns in our data: mapping the area between subsequent bank lines, differencing digital elevation models and summing the resulting raster cells, and computing 3D horizontal and vertical differences between subsequent point clouds using the M3C2 plugin in CloudCompare. This project ultimately aims to constrain when and where individual bank failures occur to understand how they interact to generate net migration of a river bend.