As demonstrated by recent tropical cyclone events, including U.S. Hurricanes Harvey, Irma, and Maria (2017), and Florence (2018), the destructive potential of flooding driven by wind, precipitation, and coastal surge coupled with growing exposure of people and property along coastlines is leading to unprecedented damage from coastal storms. In this paper, we demonstrate the ability of the recently developed Super-Fast INundation of CoastS (SFINCS) model to delineate the depth and extent of flooding during Hurricane Harvey in Houston, Texas. The model was validated against water level time-series at twenty-one United States Geological Survey (USGS) observation points and 115 high water mark locations. FEMA depth-damage curves were used to estimate building and content damages from the combined flood sources (e.g., pluvial, fluvial, and marine) and total losses are compared against insurance claims registered with the U.S. National Flood Insurance Program (NFIP) and a depth grid produced during the U.S. Federal Emergency Management Agency’s (FEMA) Preliminary Damage Assessment (PDA). The results suggest that Harvey may have caused upwards of $8.3 billion USD in uninsured residential loss within the model domain. Comparison against FEMA’s PDA indicates that the SFINCS model predicts much larger total losses, indicating that the incorporation of spatially-distributed pluvial hazards into the modeling method is critical for identifying high-risk areas and supports the need for further flood risk analyses in the region.