Southeastern Section - 73rd Annual Meeting - 2024

Paper No. 49-6
Presentation Time: 1:30 PM-5:30 PM

USING REPEAT LIDAR TO IDENTIFY STREAMBANK EROSION HOTSPOTS IN RALEIGH, NORTH CAROLINA


GURLEY, Laura N., HOPKINS, Kristina G. and STILLWELL, Charles C., U.S. Geological Survey, South Atlantic Water Science Center, 3916 Sunset Ridge Rd, Raleigh, NC 27607

Excess sediment is one of the leading causes of impairment in rivers and streams in the United States. Sediment eroded from streambanks is often the dominant source of measured suspended sediment loads in the suburban Piedmont. While streambank erosion is a natural process in fluvial systems, excess sediment in stream water can have negative impacts. For example, excess sediment can negatively affect aquatic habitat, transport harmful sediment-associated constituents, cause infilling of downstream reservoirs, and give rise to poor water clarity. The City of Raleigh, North Carolina recognizes the prevalence of streambank erosion within its jurisdiction. To guide effective mitigation efforts, a comprehensive approach to identify streambank erosion hotspots is needed. Current approaches, such as stream walks or citizen complaints, can be inefficient, inconsistent, and expensive. New tools are needed to remotely identify streambank erosion hotspots throughout the city. The U.S. Geological Survey and the City of Raleigh have partnered to test new methods to identify streambank erosion hotspots and guide stabilization efforts throughout the city’s stream network.

High-resolution lidar-derived topographic metrics were developed from aerial lidar surveys conducted in 2015 and 2022 and paired with field geomorphic assessments. These datasets will be used to develop a streambank erosion model to remotely map streambank erosion potential. Digital elevation models (DEM) at 1-meter resolution were used to develop topographic metrics such as channel slope and positive landscape openness. The raster datasets were differenced to characterize changes in elevation and topographic metrics between 2015 and 2022. In this presentation, we highlight lidar-derived datasets that may have the most potential for improving streambank erosion and water quality modeling. The findings from this study, including these datasets and a model to predict streambank erosion potential, will help the City of Raleigh prioritize stream reaches for future stabilization or restoration efforts.