EGU22-5729, updated on 22 Nov 2023
EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

European Coastal Flood Awareness System (ECFAS): forecasting extreme coastal water-levels at European scale

Maialen Irazoqui Apecechea1, Angélique Melet1, Clara Armaroli2, Paolo Ciavola3, and Tomas Fernandez Montblanc4
Maialen Irazoqui Apecechea et al.
  • 1Mercator Ocean International, Toulouse, France
  • 2University School for Advances Studies Pavia IUSS, Pavia, Italy
  • 3Consorzio Futuro in Ricerca CFR, Ferrara, Italy
  • 4University of Cadiz UCA, Cadiz, Spain

European coasts are often exposed to severe storms that trigger extreme water-level conditions, leading to coastal flooding and erosion. With the objective to provide useful and timely information on coastal flood risk from extreme sea level events at European scale, a proof-of-concept for a European Coastal Flood Awareness System (ECFAS) is being developed as part of a European Union’s Horizon 2020 project. ECFAS could contribute to the evolution of the Copernicus Emergency Management Service.

ECFAS uses state-of-the-art coastal monitoring and forecasting technologies and datasets suited to regional-to-local scale assessments. For its early-warning component, ECFAS capitalizes on the ocean forecasting systems operated by the Copernicus Marine Service (CMEMS). Such forecasts are combined with a coastal-stretch-specific, pre-computed flood catalog to provide a mapping of the inundation depth and extent. Consecutively, the ECFAS-Rapid and Risk and Recovery Mapping component is activated which allows an operational assessment of the socio-economic impact of marine storms.

In this presentation, we focus on the skill of the CMEMS ocean hydrodynamic models that provide the marine hazard component to the system. We apply a methodology to detect storm-driven extreme sea level events from tide-gauge records and validate the event peak representation and forecast lead time impact. For best analyses, results show satisfactory results but a general underprediction of peak magnitudes of 10% for water levels and 18% for surges across the detected storm events. In average, the models are capable of independently flagging 76% of the observed events. Forecasts show insignificant lead time impact up to a 4-day lead time, demonstrating the suitability of the systems for early warning applications. Finally, by separating the surge and tidal contributions to the extremes, we identify the source of the prediction misfits and provide recommendations for the evolution of the CMEMS forecasting models for coastal flooding applications.

The ECFAS (European Coastal Flood Awareness System) project has received funding from the EU H2020 research and innovation programme under Grant Agreement No 101004211.

How to cite: Irazoqui Apecechea, M., Melet, A., Armaroli, C., Ciavola, P., and Fernandez Montblanc, T.: European Coastal Flood Awareness System (ECFAS): forecasting extreme coastal water-levels at European scale, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5729,, 2022.