Propagation of radar rainfall uncertainties into urban pluvial flood modeling during the North American monsoon

Pluvial flooding in urban regions is a natural hazard that has been rarely investigated. Here, we evaluate the utility of three radar (Stage IV, Multi-Radar Multi-Sensor or MRMS, and gauge-corrected MRMS or GCMRM) quantitative precipitation estimates (QPEs) and the Storm Water Management Model (SWMM) hydrologic–hydraulic model to simulate pluvial flooding during the North American monsoon in Phoenix. We focus on an urban catchment of 2.38 km² and, for four storms, we simulate a set of flooding metrics using the original QPEs and an ensemble of 100 QPEs characterizing radar uncertainty through a statistical error model. We find that Stage IV QPEs are the most accurate, while MRMS QPEs are positively biased and their utility to simulate flooding increases with the gauge correction done for GCMRMS. For all radar products, simulated flood metrics have lower uncertainty than QPEs as a result of rainfall–runoff transformation. By relying on extensive precipitation and basin datasets, this work provides useful insights for urban flood predictions.