A coastal flood map catalogue will be developed according to the Rapid Mapping approach described in Dottori et al. (2017). Areas prone to flooding will be identified along the European coastline, using the Total Water Level (TWL) hindcast dataset, including the wave contribution to the TWL (Paprotny, 2018; Marcos et al., 2019), using the a high resolution European DEM (10×10 m) kindly provided by JRC. The work will also incorporate previous
analysis carried out by Vousdoukas et al. (2016).
In a second phase, these flood-prone coastlines will be segmented into 50-100 km stretches, and LISFLOOD-FP will be implemented with 25-50 m resolution. For each coastal segment a flood map catalogue will be created, storing the results of several simulations. Each simulation will be based on the ANYEU-SSL hindcast dataset corrected by the CMEMS hindcast, and accounting for local variability in the main factors that control coastal flooding (TWL, infiltration, event duration, etc.).
Finally, the ECFAS Expert System will apply an algorithm to forecast the event-based flood extension on the basis of the coastal flood map catalogue similar to the current EFAS approach (Dottori et al., 2017). AI-based solutions will be considered, e.g. supervised machine learning. ECFAS AI-based approaches will produce probabilistic flood maps (water depth and velocity) based on the entire catalogue of coastal sectors.
Dottori, F., Kalas, M., Salamon, P., Bianchi, A., Alfieri, L., and Feyen, L., 2017. An operational procedure for rapid flood risk assessment in Europe. Nat. Hazards Earth Syst. Sci. 17, 1111–1126. https://doi.org/10.5194/nhess-17-1111-2017
Vousdoukas, M.I., Voukouvalas, E., Annunziato, A., Giardina, A. and Feyen, L., 2016. Projections of extreme storm surge levels along Europe. Clim. Dyn. 47(9-10), 3171–3190. https://doi.org/10.1007/s00382-016-3019-5