The work conducted during WP1 was the most fundamental of the Fellowship and aimed at deriving a universal relationship between incident wave properties and the mean water depth h. The “universal” character of this relationship means that it should work within most of the nearshore region, both in the shoaling and breaking wave regions, and for a wide range of beach and wave conditions. In total, three different approaches have been investigated using existing laboratory datasets of irregular and unidirectional waves. A Boussinesq (non-linear) wave theory was found to be the most accurate for predicting waves dispersive properties across both the shoaling and breaking wave regions.
Based on this Boussinesq theory, a new depth-inversion method was developed. This new method was assessed with laboratory datasets that offer a more controlled environment compared to the field. The three datasets exhibited different beach morphologies and varying wave conditions. Overall, the proposed methodology allowed to estimate the mean water depth with unprecedented accuracy, seamlessly from the shoaling region up to the shoreline (errors typically below 5-10%). The development and finalisation of the new methodology has been achieved during the Outgoing phase of the Fellowship at the Water Research Laboratory (WRL). This work has been published in Geophysical Research Letters (Martins et al., 2023), and was presented at the International Conference on Coastal Engineering held in December 2022 in Sydney, Australia.
The last phase of the Fellowship focused on collecting field data adapt the depth-inversion tool to the case of directionally-broad ocean waves. In September 2022, a comprehensive 3 week field campaign was organised in collaboration with Katherine Brodie from the US Army Corps of Engineers at the Field Research Facility (FRF) at Duck NC. During these experiments, surface elevation measurements were collected by three lidar systems: a long-range lidar from the dune station, complemented by two 3D lidars mounted on Unmanned Autonomous Vehicles. During the following months, major complications arose and consequently delayed the data analysis. This is explained by the size of the data to be processed (1Gb per minute of data) and the three dimensionality of lidar point clouds: noise, interpolations, computation of bispectral products for the Boussinesq theory etc. The analysis of the data is still ongoing, nonetheless, preliminary results show that the methodology developed in the lab is also accurate in the field, except in regions with strong surface currents. Following these first results, efforts were made to simplify the Boussinesq-based depth-inversion procedure, especially avoid computing bispectral products on lidar data. Theoretical simplifications were performed, and a simpler formula only requiring bulk parameters was derived. The assessment of this simpler formula is ongoing work. Lastly, new deployments of 3D lidar systems were conducted in May 2023 from the Hazaki Oceanographical Research Station, an experimental pier located along the Ibaraki coast of Japan. Lidar and bathymetric data collected at this site will help elucidating the limitations of the proposed depth-inversion approaches and inform on the site-specificity of physical processes affecting the accuracy of the proposed methodology. Given that the newly-proposed methodology is still at a development stage, and its robustness (e.g. site-specific or not) remains to be explored, the objective O3 proved to be overly ambitious. Nonetheless, this Fellowship paved the way to the derivation of a universal nearshore depth-inversion method. Efforts to further develop the new depth-inversion method and apply it to study sandy beaches response to storms will be pursued as part of the Experienced Researcher CNRS project.
