Fundamental to ECFAS’ commitment to capacity building for coastal flood awareness and resilience is training the next generation of end users, flood risk managers, and early-career researchers. The ECFAS Traineeship Programme is aimed at European and international post-graduate scientists, engineers and researchers, with the goal of providing professional working experience on modelling/algorithms development for coastal flood awareness systems.
ECFAS has allocated a total of three traineeships for young professionals, the first of which was awarded to Maialen Irazoqui Apecechea (MSc/MEng). Maialen is a dedicated research engineer working on coastal management and climate change impacts, with emphasis on numerical modelling.
From November to December 2021, Maialen joined researchers from the University of Cádiz, in a traineeship facilitated by Consorzio Futuro in Ricerca. The internship addressed the characterization and evaluation of the propagation of uncertainties in marine forcing into flood model, focusing on the pre-defined test cases for extreme events. This work explored the contributions of the different water-level components and their uncertainties to the resulting flooding (recurrence). These uncertainties included modelling choices such as the choices of parameterization for wave-setup (different empirical formulations of varying complexity and applicability, different choices for local slopes, etc.) and the inclusion of mean sea level variability. Additionally, she explored the differences in flooding obtained between marine forcing derived from operational forecast products and hindcast products, providing the first insights into the correspondence between forecasts and the hindcast-derived flood catalogue (contributing to ECFAS WP4 – Hindcast/forecast forcing of total water levels and identification of thresholds).
Through the traineeship, Maialen gained experience in general flood modelling (relevant physical processes, manipulation of input datasets and interpretation of results) using the flood model LISFLOOD, and knowledge on best-practices to couple marine-forcing and coastal inundation models to serve coastal flood forecasting applications.