Investigating future flood exposure risk and associated mitigation strategies is vital for sustainable urban development. This study coupled hydrological modeling with future climate and urbanization scenarios from Representative Concentration Pathways and Shared Socioeconomic Pathways (SSP), to spatiotemporally investigate the risk of flood exposure and the effectiveness of mitigation strategy at the city scale. A highly urbanized (80% of built-up areas) and densely populated (7500 per km²) region in downtown Chaohu, China was selected as the study case. Results showed that the current hydrological pattern brought 4.64 × 10⁶ m³ of annual runoff and 292.00 l s⁻¹ of peak flow to the given area, thereby causing 41.03% of the population to be exposed to flooding threats and putting 51.17% of Gross Domestic Product (GDP) at risk. Scenario analysis demonstrated that population and GDP exposures to flood increased to at most 61.11 and 71.30% in high-carbon emission scenarios (SSP3-7.0/SSP5-8.5), respectively. The green infrastructure (GI) strategy captured at most 81.43% of runoff volume and 54.53% of peak flow, thereby decreasing population and GDP exposures to at least 18.38 and 33.04% in low-carbon emission scenarios (SSP1-2.6/SSP2-4.5), respectively. According to the uncertainty analysis, population and GDP exposures showed wide uncertainty ranges of 18.38–61.11 and 33.04–71.30% in future scenarios, and the GI strategy effectively decreased the flood exposure uncertainty ranges to 15.56–42.70 and 17.35–43.60%, respectively. In addition, the spatial analysis indicated that the population- and GDP- intensive regions were more vulnerable to flood exposure than other regions, while GI strategy in these regions showed limited effectiveness in mitigation of exposure risk. The data of this study could assist sustainable urban development in response to climate change and urbanization.