Modeling the exposure time in a tidal system: the impacts of external domain, tidal range, and inflows
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Exposure time is an important characteristic for hydrodynamics that has simultaneous impacts on the biochemical processes in tidal systems. To eliminate man-made errors, decrease computational effort, and increase simulation efficiency, exposure time was evaluated under different hydrodynamic conditions for a bay to investigate the impact of the external domain on the accuracy of the computational results for exposure time. The exposure time was explicitly defined and computed using a hydrodynamic model and tracer experiments for a set of ten external domain sizes (EDS), five external domain lengths (EDL), and three special hydrodynamic conditions. The results indicated that the external domain had a significant influence on the exposure time, and the intensity of this influence was related to hydrodynamic conditions. The sensitivity of the exposure time to the external domain increased with increasing tidal range, while freshwater inflows decreased this sensitivity. However, the variation trends for exposure time with different EDS and EDL were independent of the hydrodynamic conditions. Considering the computational efficiency (maximum), the calculated error (minimum) of the exposure time, and the impact of the boundary conditions (minimum), the recommended EDS and EDL range from 9 to 13 times the initial domain size and 1.30 to 1.45 times the length in the bay, respectively. The research regarding exposure time and external domains not only helps to eliminate the errors caused by man-made factors and reduce the computational effort but also provides a reference for understanding the interrelationship between coastal waters, reciprocating flow, and the water environment.
KeywordsExposure time External domain Extension length Hydrodynamic conditions
This research was supported by the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (No. 51621092), the National Natural Science Foundation of China (No. 51679160), and the Tianjin key research and development program (No. 16YFXTSF00310). Special thanks are addressed to the High Performance Computing Center of Tianjin University, China.
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