Abstract: Coastal storm-induced flooding threatens millions of people and infrastructures, highlighting the need for comprehensive flood risk assessments. A key component of these assessments is the spatial characterization of total water level (TWL), the primary driver of coastal flooding. We propose a flexible methodology for developing large-scale TWL hindcasts to estimate extreme events, considering possible spatial variabilities in marine dynamics. This methodology is applied to the European coastline, integrating downscaled nearshore waves, storm surges, and tides. The resulting hourly time series of the TWL have a spatial resolution of 1 km and covers the period from 1985 to 2021. Spatial variability is considered in foreshore slopes and extreme value detection thresholds, addressing common simplifications in large-scale studies. In addition to a characterization of extreme events based on the relative contributions of TWL components, sensitivity analyses of the wave contribution, wave data resolution, foreshore slopes, and wave setup formulations are conducted. The tide-dominated Atlantic coast is where the TWL is most affected by the wave dataset. The storm surge-dominated Baltic region exhibits the lowest confidence in estimating TWL return levels, partially due to the data and methods used. The Mediterranean Sea, characterized as a mixed environment, is the most sensitive to the inclusion of wave contribution. A classification of TWL extremes revealed that no regions have extreme events dominated by wave setup when compared to the remaining components, while those dominated by tides show the highest return levels.

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