R. Carballo

Performance of artificial neural networks in nearshore wave power prediction

In this paper the assessment of the wave energy potential in nearshore coastal areas is investigated by means of artificial neural networks (ANNs). The performance of the ANNs is compared with in situ measurements and spectral numerical modelling (the conventional tool for wave energy assessment). For this purpose, 13 years of records of two buoys, one offshore and one inshore, with an hourly frequency are used to develop an ANN model for predicting the nearshore wave power. The best suited architecture was selected after assessing the performance of 480 ANN models involving twelve different architectures. The results predicted by the ANN model were compared with the measured data and those obtained by means of the SWAN (Simulating Waves Nearshore) spectral model. The quality in the predictions of the ANN model shows that this type of artificial intelligence models constitutes a powerful tool to forecast the wave energy potential at particular coastal site with great accuracy, and one that overcomes some of the disadvantages of the conventional tools for nearshore wave power prediction.

Floating boom performance under waves and currents.

Floating booms constitute a fundamental tool for the protection of marine and coastal ecosystems against accidental oil spills. Their containment performances in exposed areas are often impaired by the action of waves, currents and winds in a manner which is dependent on the booms response as a floating body, and which is not fully understood at present. In this work the relationship between the design parameters of a floating boom section and its efficiency against the mode of failure by drainage under a variety of wave and current combinations is investigated by means of physical modelling. Seven boom models with different geometries and buoyancy-weight ratios are tested with an experimental setup that allows them to have and rotate freely. The model displacements under waves (both regular and irregular) and currents, as well as those of the free surface adjacent to the model, are measured with a Computer Vision system developed ad hoc. Two efficiency parameters are defined-the significant and minimum effective boom drafts-and applied to the results of an experimental campaign involving 315 laboratory tests. Thus, the manner in which the design parameters influence the booms efficiency under different wave and current conditions is established.

Can the Seasonality of a Small River Affect a Large Tide-Dominated Estuary? The Case of Ria de Viveiro, Spain

Abstract River runoff into Ría de Viveiro presents great seasonal variability due to the regions climate—but always in the context of discharge values that are small relative to the size of the estuary. This work has two main objectives: (i) to implement the first numerical model of ría hydrodynamics and (ii) to determine whether the river discharge variability has significant effects on the system and, if so, which. The numerical model, which takes into account all driving agents (tides, river discharge, and winds), is successfully validated based on sea level and flow velocity observations, with very high correlation coefficients. It is then applied to different study cases representative of typical summer and winter scenarios. Three main conclusions can be drawn: (i) The flow is primarily tide driven. (ii) However, the river discharge is not without significance—it causes ebb–flood asymmetry with ebb dominance. (iii) The main consequence of the seasonal variability of river discharge is the seasonality of the ebb–flood asymmetry itself. Weak and essentially confined to the inner ría in summer, it gains strength in winter and extends to the outer ría, where different flood and ebb patterns arise.