| dc.description.abstract | Vessel-generated waves are well-documented sources for a substantial amount of the energy impacting shorelines and embankments lining shipping channels. An approximately year-long study was conducted in Galveston Bay, Texas adjacent to the Houston Ship Channel, one of the busiest commercial navigation lanes in the United States. Hydrodynamic data were collected at two research platforms just offshore of a beneficial-use dredge material dike approximately one kilometer eastward of the ship channel. The hydrodynamic data were then analyzed through time-localizing signal analysis techniques known as wavelet transforms. Wavelet transforms facilitate the use of time-frequency domain transformations on nonstationary data (i.e., hydrodynamic bursts containing vessel wake signatures). Time-localizing abilities are the major shortcoming to the standard signal-analysis techniques utilizing Fourier-based transformations. An algorithm was constructed with the wavelet analysis results to identify wake events in the measured data via usage of multiple statistical measures, linear wave theory principles, and hydrodynamic signal behaviors unique to wake events. Data were then investigated for correlations with vessel traffic information, thereby providing direct associations between the observed wake effects and the specific deep-draft vessel inducing the wake event. Results confirmed that wake events, particularly those from inbound traveling deep-draft vessels, were responsible for an outsized portion of the total wave energy impacting the site. Although occurring during less than 5% of the study period, inbound wake events accounted for just over 20% of the total measured wave energy. The median maximum wave energy per minute of inbound and outbound wake events were about 9 and 1.5 times larger than that of wind-only periods, respectively. The strongest correlation between wake events and vessel traffic was by the nondimensional velocity head and length Froude number for inbound vessels with an R2 between 0.44 and 0.52 depending on the tidal elevation. The presented data analysis helps quantify the hydrodynamic energy resulting from vessel traffic available to drive shallow-bay sediment dynamics and shoreline erosion and enables predictions based on expected future vessel traffic volumes and patterns. In addition, this extensive data set is being used to improve our capability to numerically model ship wakes and their impacts in shallow-bay systems. | en |
