Low-lying coastal cities across the world are vulnerable to the combined impact of rainfall and storm tide. However, existing approaches lack the ability to model the combined effect of these flood mechanisms, especially under climate change and sea level rise (SLR). Thus, to increase flood resilience of coastal cities, modeling techniques to improve the understanding and prediction of the combined effect of these flood hazards are critical. To address this need, this study presents a modeling system for assessing the combined flood impact on coastal cities under selected future climate scenarios that leverages ocean modeling with land surface modeling capable of resolving urban drainage infrastructure within the city. The modeling approach is demonstrated in quantifying the impact of possible future climate scenarios on transportation infrastructure within Norfolk, Virginia, USA. A series of combined storm events are modeled for current (2020) and projected future (2070) climate scenarios. The results show that pluvial flooding causes a larger interruption to the transportation network compared to tidal flooding under current climate conditions. By 2070, however, tidal flooding will be the dominant flooding mechanism with even nuisance flooding expected to happen daily due to SLR. In 2070, nuisance flooding is expected to cause a 4.6% total link close time (TLC), which is more than two times that of a 50-year storm surge (1.8% TLC) in 2020. The coupled flood model was compared with a widely used but physically simplistic bathtub method to assess the difference resulting from the more complex modeling presented in this study. The results show that the bathtub method overestimated the flooded area near the shoreline by 9.5% and 3.1% for a 10-year storm surge event in 2020 and 2070, respectively, but underestimated the flooded area in the inland region by 9.0% and 4.0% for the same events. The findings demonstrate the benefit of sophisticated modeling methods compared to more simplistic bathtub approaches, in climate adaptive planning and policy in coastal communities.

Flood risk analyses often focus on a single flooding source, typically storm surge or rainfall‐driven flooding, depending on the predominant threat. However, hurricanes frequently cause compound flooding through significant storm surges accompanied by heavy rainfall. This study employs a hydrodynamic model based on Delft3D‐Flexible Mesh that couples flow, waves, and rainfall‐driven flow to simulate five historical tropical cyclones in Virginia's southeast coastal region. These storms produced varying intensities of storm surge and rainfall in the study area. Model simulations, incorporating rainfall through a rain‐on‐grid approach, account for the dynamic interaction between storm tides, and pluvial flow and enable the definition of flood zones as hydrologic, transitional, and coastal zones. This compound flooding model was validated with water level data from in‐water and overland gauges. The results indicate that the magnitude of the coastal zone correlates strongly with the extent of the surge‐inundated area (SIA) obtained from simulations that only considered storm surges. The extent of the transitional zone correlates strongly with the product of SIA and total rainfall. As an additional measure for flood hazards besides water depth, we calculated flow momentum flux at different flood zones to assess potential damage from hydrodynamic loads on structures, vehicles, and pedestrians. A strong correlation was found between the magnitude of the surge and momentum flux. Furthermore, high rainfall rates and winds can cause a significant increase in momentum flux locally. Understanding flood zones and their flow dynamics helps to identify effective flood risk management strategies that address the dominant flood driver.