Southeastern Section - 68th Annual Meeting - 2019

Paper No. 12-11
Presentation Time: 8:00 AM-12:00 PM


BURSTEIN, Joshua A., School of the Earth, Ocean, and Environment, University of South Carolina, Columbia, SC 29205 and WHITE, Scott, University of South Carolina, 700 Sumter St, Columbia, SC 29208

To improve understanding of the relationship between riverbed shape, sediments, and habitat in coastal-plain river systems, a bathymetric side-scan sonar was used to map the riverbed at sub-meter resolution in both depth and acoustic backscatter intensity. Using these data, we developed a quantitative approach to determine riverbed depositional environments and associated underwater habitats on the reach-scale of the river. We utilized QPS Qinsy sonar acquisition software and a PingDSP 3DSS-450DX sonar to collect simultaneous bathymetry and backscatter data of approximately 15 river-miles along the Congaree River in Congaree National Park, South Carolina, USA. We then used the QPS Qimera software to clean and correct the bathymetry and QPS Qinsy to mosaic the backscatter prior to export into ArcGIS.

We use the backscatter relative intensity, textures derived from backscatter imagery, and bathymetry to classify the riverbed in general categories of sediments commonly found in low gradient river systems: sand, mud, and gravel. We conducted spatial analysis in ArcGIS using machine-learning tools to identify unknown mussel habitats based on locations of a few previously known mussel beds and the riverbed characteristics. Freshwater mussels generally inhabit areas of soft sediments and low-slope for optimum mobility and live near the waterline. Sediment collection at recorded locations along the river, grain size analysis, and visual observations of mussel shoals provided the observational data that constrained the classification. Understanding the physical characteristics of the riverbed at this scale is crucial to developing policy to preserve endangered species habitats in fluvial systems.