Field Measurements II

The results of the analysis of the wave measurement campaigns on the Pacific coast of Costa Rica are presented. After analyzing more than 14000 spectral shapes from sea states, it has been determined that many of them present 2 or more swell peaks, so it was proposed to perform a wave characterization in which 8 different types of spectra were defined to include all the data collected. Also, verifications were carried out in these sea states to check the reliability of many of the approximations usually used in coastal engineering that assume narrow-band spectra, such as the JONSWAP type.

During berthing operations, the bow thruster jet reflecting on the quay wall and the bed can lead to high flow velocities near the bed. This may scour the nearby bed when it is left unprotected, causing instability of the adjacent quay wall. Due to the complex flow field of the reflected jet, the decay in near-bed flow velocities perpendicular to the quay wall is unknown. Resulting in uncertainties in the design of bed protections, especially in the required width.
In this research, the decay of the near-bed flow velocity in x- and y-direction to the quay wall induced by a 4-channel bow thruster is researched. Field measurements have been conducted with one of the largest inland vessels in the Netherlands. The flow velocities near the bed have been measured with Acoustic Doppler Velocimeters (ADV), and Ott meters (Ott) at multiple locations perpendicular to the quay wall. 

Industrial outfalls usually contain effluent of a different temperature with additives such as metals, microplastic, and increased salt concentration. To prevent ecological problems, it is essential to monitor environmental conditions and mixing. Accordingly, this research proposes the application of remote sensing technologies for analyzing and monitoring industrial outfalls, with a particular focus on satellite data. These technologies enable quick and cheap analysis of a larger coastal area. The methodology for applying remote sensing data on outfalls, including image analysis with machine learning algorithms, is presented. The study shows the advantages and disadvantages of the remote sensing data and provides an overview of the detection possibilities and available technologies.