| description abstract | Studies and models of sediment transport in the bottom boundary layer require knowledge of the bottom roughness as a parameter affecting the suspension and transport of sediment. Knowledge of this has often been quite imprecise since measurements could only be made from diver observations or camera pictures at times when the water was clear. A self-contained, tripod-mounted rotating-beam sonar system has been developed, which allows bottom topography to be imaged on scales of a few square centimeters out to 4-m radius at regular intervals in time. Most importantly, this system produces images during high suspended sediment concentration transport events, when knowledge of the bottom structure and movement is most crucial. To accomplish this, a Simrad/Mesotech sonar head was adapted as the sensing element for remote use. A separate self-contained controller/recorder was constructed and housed in its own pressure case with sufficient battery and storage capacity for up to six months deployment with hourly imaging. The controller/recorder was based on the PC/104 family of components. It digitized the acoustic signal to 12 bits at 75 kHz and stored the 450-kbyte images on 2 Gbytes of hard disk. After recovery, the data were retrieved from the instrument via an ethernet link for analysis. Three deployments were made with the system on the east and west coasts of the United States, and three distinctly different types of bottom topography were observed. STRESS III on the northern California shelf in 90 m of water showed random, small amplitude features due to biologically formed structures in the bottom. The STRATAFORM experiment, farther north by the mouth of the Eel River in 50 m of water, showed 10-cm wavelength anorbital ripples. A deployment at the LEO-15 site off the New Jersey coast in 12 m of water showed large orbital ripples, which were well correlated with wave direction and wave particle excursions. The acoustic system was able to image these ripples as they moved and changed direction during storm events. This unique view of how the bottom feature evolution relates to the forcing will enable improvements to be made in modeling and sediment transport predictions. | |
