Beyond the 100-Year Flood: Probabilistic Flood Hazard Assessment for King and Pierce Counties under Future Climate Scenarios

Abstract. Coastal areas, such as the Salish Sea, are becoming increasingly vulnerable to compound flooding due to the interaction between storm surge, tides, and river outflow. This hazard is anticipated to increase under sealevel rise and climate change. This research offers a high-resolution flood hazard mapping for King and Pierce Counties of Washington State (United States of America) using the SFINCS (Super-Fast INundation of CoastS) model to facilitate a Continuous Flood Response Modeling (CFRM) framework wherein decades of dynamic coastal and fluvial processes are simulated. By applying a cell-by-cell extreme value analysis, we predict flood areas for return periods of 1–100 years and compute the Expected Annual Flooded Area (EAFA) as a probability-weighted indicator of flood exposure. Model validation against National Oceanic and Atmospheric Administration (NOAA) and United States Geological Survey (USGS) gauge data demonstrates skill (RMSE: 14–17 cm for coastal water levels; unbiased RMSE: 49–116 cm for river water levels), and comparison with FEMA Special Flood Hazard Areas shows high spatial agreement of flooding (hit rates: 0.75–0.83). The timing statistics of the flooding reveal that the December 28, 2022, event was responsible for most historically observed flooding across the area. Climate simulations for today show EAFA ranges from 56 to 200 hectares in King County and from 250 to 644 hectares in Pierce County. Future projections show that sea level rise is the main contributor to increasing flood extent, whereas climate change drivers such as storm pattern change have little additional effect. We also identified a threshold around 100–150 cm of sea level rise at which the flood-exposed area increases substantially. Additionally, simplified deterministic flood maps can underestimate flood hazard by up to 0.5 m if not all relevant drivers are included. These results support the use of probabilistic, event-independent flood metrics such as EAFA to inform more rational and spatially responsive flood risk management.