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Hydrodynamic characterization of Corpus Christi Bay through modeling and observation. | LitMetric

Hydrodynamic characterization of Corpus Christi Bay through modeling and observation.

Environ Monit Assess

Department of Civil and Environmental Engineering, Clarkson University, 8 Clarkson Ave, Potsdam, NY, 13699-5764, USA,

Published: November 2014

Christi Bay is a relatively flat, shallow, wind-driven system with an average depth of 3-4 m and a mean tidal range of 0.3 m. It is completely mixed most of the time, and as a result, depth-averaged models have, historically, been applied for hydrodynamic characterization supporting regulatory decisions on Texas coastal management. The bay is highly stratified during transitory periods of the summer with low wind conditions. This has important implications on sediment transport, nutrient cycling, and water quality-related issues, including hypoxia which is a key water quality concern for the bay. Detailed hydrodynamic characterization of the bay during the summer months included analysis of simulation results of 2-D hydrodynamic model and high-frequency (HF) in situ observations. The HF radar system resolved surface currents, whereas an acoustic Doppler current profiler (ADCP) measured current at different depths of the water column. The developed model successfully captured water surface elevation variation at the mouth of the bay (i.e., onshore boundary of the Gulf of Mexico) and at times within the bay. However, large discrepancies exist between model-computed depth-averaged water currents and observed surface currents. These discrepancies suggested the presence of a vertical gradient in the current structure which was further substantiated by the observed bi-directional current movement within the water column. In addition, observed vertical density gradients proved that the water column was stratified. Under this condition, the bottom layer became hypoxic due to inadequate mixing with the aerated surface water. Understanding the disparities between observations and model predictions provides critical insights about hydrodynamics and physical processes controlling water quality.

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Source
http://dx.doi.org/10.1007/s10661-014-3973-5DOI Listing

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