Strengthening coastal flood forecasting through event-based data capitalization: a case study from the December 2022 storm surge in Québec City

The maritime conditions due to climate change such as sea level rise, storm surge, and river discharge, will worsen coastal risks, including submersion and erosion, to lowlands. Flood risk mapping is necessary to help decision-makers in coastal management. Compared to the standard GIS-based (or Bathtub) model assessing flooded zone expansion from a stationary approach, hydrodynamic models enable a dynamic description of water level and velocity during the flooding. Such information is particularly relevant for evaluating the depth-velocity flood danger level to define an optimal crisis management or evacuation plan. This research aims to validate a 2D hydrodynamic model of Saint-Lawrence Fluvial Estuary (SLFE) for coastal flooding risk management in Quebec City and use it to analyze the flood event of December 23rd, 2022. The model results from an integration of multisource data for the topography and bathymetry, as well as their fusion and interpolation. With a computational grid and variable resolution from 2 m in the urbanized area to 250 m in the SLFE, the model captures flow patterns in the inundated urban zone during macro-tidal or spring tide. Results indicates that the wind can influence water levels in urban area, and that urban configuration in Quebec City can also affect the flooding process.