Urban flooding significantly impacts transport networks and the mobility of people and associated air quality. This paper introduces a new dynamic framework to quantify and analyse the indirect economic and environmental impacts of flooding on transport networks from multiple perspectives, including time delay, fuel consumption, and pollutant emissions. This was implemented by dynamic coupling of flood propagation from a hydrodynamic model (CADDIES-2D) with traffic simulations from an agent-based transport model (SUMO). This framework was applied over 2267 km2 area of Beijing, far exceeding the spatial scale and complexity of other urban flood disruption studies. Economic impacts across various flood scenarios were quantified by comparing baseline traffic with the impacts of three rainfall scenarios. Our analysis shows that a 1-in-5-year storm at 7am doubles the baseline traffic cost, while the same intensity storm at 8 a.m. and 9 a.m. increases costs by 60.32 % and 35.82 %, respectively, highlighting the critical role of timing in traffic disruption and the importance of early warning. The impacts of disruption from flooding are shown to be non-linearly related to both rainfall intensity and traffic volumes. This large-scale, integrated approach enables a more detailed evaluation of flood-related transport disruptions, helping identify the most vulnerable areas, supporting real-time traffic management strategies, and allowing decision-makers to prioritise adaptation investments to manage flood risk. Ultimately, this framework provides a robust, transferable tool for enhancing transport network resilience to urban flooding impacts.