Data & Analytics play a vital role in the realization of the Sustainable Development Goals (SDGs). SDG 17 (Partnerships for the Goals) specifically emphasizes the need to enhance the availability of high-quality, timely, and reliable data. Accurate data and insightful analytics are essential for assessing progress, identifying gaps, making informed decisions, and creating effective policies related to each of the SDGs. For instance, they can help enhance education systems (SDG 4), optimize health services (SDG 3), reduce poverty (SDG 1), and mitigate climate change impacts (SDG 13). Moreover, advances in data collection methods, including mobile technology and remote sensing, can provide valuable insights for achieving sustainability. Therefore, robust data and analytics are integral to monitoring and accomplishing the SDGs.
This paper develops a coupling between SWAN and Thetis models to account for wave–current interactions occurring by the co-existence of wave and current flows. The different grids and time-steps employed by the model components allow greater flexibility. The two models run consecutively, and communicate internally to exchange the necessary parameters. These are the significant wave height, mean wave direction, mean wavelength and percentage of wave-breaking calculated by SWAN necessary for calculating radiation stress and wave roller effects, while Thetis provides water elevation and current velocity fields.