How frequent is storm-induced flooding in the central part of the Bay of Biscay?

Abstract

This study analyzes historical archives to produce a database of storm-induced coastal flooding in the French central part of the Bay of Biscay since 1500AD. From this new database, 46 coastal floods have been reported for the last 500years (1 event every 11yr on average), which demonstrates the high vulnerability of this region to coastal flooding. The limitations of historical archives prevent concluding to a change in storminess over the period. The six largest coastal floods that occurred since 1900 are further investigated because numerous informations are available in terms of meteorological conditions as well as maximum water levels reached. Associated storm surges are also modeled using a simplified methodology, relying on a fully coupled wave and circulation modeling system directly forced by the available meteorological data. The analysis of modeling results and historical archives reveals firstly that several meteo-oceanic settings can lead to extensive coastal flooding in the studied area. The analyzed events allow distinguishing three main settings: (1) a small storm surge associated with the highest astronomical tidal levels, (2) a large storm surge, induced either by extreme winds or a particular sea-state and associated with high astronomical tidal levels and, (3) a large storm surge enhanced by extreme wave conditions. Second, maximum water levels reached during these 6 coastal floods were shown to be higher than the 100years return period water level estimated in several recently published studies. This inconstancy can be explained mainly by the lack of extreme water level records in tide gauge datasets used in these previous studies. To a slightest degree, this study questions the validity of classical statistical approaches when analyzing extreme water levels data resulting from contrasting meteo-oceanic settings. It is concluded that historical archives combined with storm surge modeling could be a valuable approach to better estimate the return period of extreme sea levels and improve the understanding on the vulnerability of mixed-energy coastal environments such as the study area.