This study aims to assess the performance of raster-based flood modeling methods on a wide diversity of coastal marshes. These methods are applied to the flooding associated with the storm Xynthia, which severely hit the western coast of France in February 2010. Static and semi-dynamic methods are assessed using a combination of LiDAR data, post-storm delineation of flooded areas and sea levels originating from both tide gauge measurements and storm surge modeling. Static methods are applied to 27 marshes showing a wide geomorphological diversity. It appears that these methods are suitable for marshes with a small distance between the coastline and the landward boundary of the marsh, which causes these marshes to flood rapidly. On the contrary, these methods overpredict flooded areas for large marshes where the distance between the coastline and the landward boundary of the marsh is large, because the flooding cannot be considered as instantaneous. In this case, semi-dynamic methods based on surge overflowing volume calculations can improve the flooding prediction significantly. This study suggests that static and semi-dynamic flood modeling methods can be attractive and quickly deployed to rapidly produce predictive flood maps of vulnerable areas under certain conditions, particularly for small distances between the coastline and the landward boundary of the low-lying coastal area.