Impact of small-scale structures on estuarine circulation
We present a novel and challenging application of a 3D estuary-shelf model to the study of the collective impact of many small-scale structures (bridge pilings of 1 m × 2 m in size) on larger-scale circulation in a tributary (James River) of Chesapeake Bay. We first demonstrate that the model is capable of effectively transitioning grid resolution from ~ 400 m down to ~ 1 m near the pilings without introducing undue numerical artifact. We then show that despite their small sizes and collectively small area as compared to the total channel cross-sectional area, the pilings exert a noticeable impact on the large-scale circulation, and also create a rich structure of vortices and wakes around the pilings. As a result, the water quality and local sedimentation patterns near the bridge piling area are likely to be affected as well. However, when evaluating over the entire waterbody of the project area, the near field effects are weighed with the areal percentage which is small compared to that for the larger unaffected area, and therefore the impact on the lower James River as a whole becomes relatively insignificant. The study highlights the importance of the use of high resolution in assessing the near-field impact of structures.
KeywordsSCHISM Cross-scale Bridge pilings Upscaling
The authors would like to thank Mr. Scott Smizik and Ms. Heather Williams of the Virginia Department of Transportation for providing detailed GIS data and technical guidance on the project. We also acknowledge Dr. Ping Wang’s assistance in providing EPA’s Bay and tributary monitoring data, and Dr. Wolfgang Vogelbein for providing the photo on plume around the Coleman Bridge. We have also benefited from the comments made by the anonymous reviewers. Simulations in this paper were conducted using the following computational facilities: (1) Sciclone at the College of William and Mary, which was provided with the assistance of the National Science Foundation, the Virginia Port Authority, and Virginia’s Commonwealth Technology Research Fund; (2) the Extreme Science and Engineering Discovery Environment (XSEDE; Grant TG-OCE130032), which is supported by National Science Foundation grant number OCI-1053575; (3) NASA’s Pleiades Supercomputer.
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