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• A systematic framework was proposed to assess urban flood resilience (UFR). • Each resilience phase (e.g., resistance, adaptation, & recovery) were considered. • The system framework incorporated hybrid flood model and system performance curve. Urban flooding can seriously threaten urban ecological security and human life, and therefore urban flood resilience (UFR) is important for urban safety and stability. To comprehensively evaluate urban system performance during the entire process of rainfall, runoff, flooding, and drainage, we developed a systematic framework for UFR assessment covering runoff simulation, flood estimation, and resilience assessment, which broadly corresponded to the phases of resistance, adaptation, and recovery. The UFR in the phases of resistance, adaptation, and recovery was simulated and assessed using a system performance curve (SPC) and technically combining with the hybrid flood model while mainly considering the total simulation time and inundated urban proportion in SPC. Because the extent of urban flooding can be influenced by climate change and the rate of urbanization, we chose the corresponding representative factors of precipitation and infiltration rate and considered 21 simulation scenarios (seven rainfall return periods and three infiltration rates) for which UFR was quantified according to urban system performance. The effectiveness of this framework was demonstrated in application to a typical highly urbanized area (i.e., Dongguan, China). The following results were derived: (1) The inundated area under the pessimistic scenario (i.e., S19) would be nearly four times greater than that under the optimistic scenario (i.e., S3); (2) The values of UFR in Dongguan were 0.9494–0.9863, locating at the high and very high level; (3) The lowest UFR value was 0.6552 in the Shuixiang New City district; and (4) The rainfall return period was the main factor influencing UFR under relatively short rainfall return periods (i.e., S1–S9), while infiltration rate was the principal influencing factor under relatively long rainfall return periods (i.e., S10–S21). The proposed systematic framework could be applied in other cities and large-scale regions like urban agglomerations and provinces. [ABSTRACT FROM AUTHOR]