[Objective] Conventional watershed delineation methods often fail to capture surface heterogeneity. To address this limitation，this study proposes a dynamic-scale zoning method for delineating catchment units and develops a flood risk identification framework integrating land cover and dynamic-scale zoning. This framework couples high-precision simulation with large-scale risk identification，aiming to provide a transferable technical pathway for flood risk management and early warning in large Chinese cities. [Methods] The established methods adopted in this study include：（1） a coupled 1D-2D hydrological and hydrodynamic model based on SWMM and LISFLOOD-FP；（2） parameter sensitivity analysis using the Morris screening method；and （3） spatial pattern evolution analysis of flood risk based on Moran’s I index. The novel approaches proposed in this study include：（1） a dynamic-scale zoning method that accounts for surface heterogeneity for precise catchment delineation； and （2） a road-network topology-based generalization strategy for underground drainage networks，providing reliable support for simulations lacking actual pipe network data.Based on the above SWMM 1D pipe network model and the LISFLOOD-FP 2D hydrodynamic model，a coupled 1D-2D urban surface flood risk assessment model was constructed，which not only accounts for underground drainage facilities but also fully simulates the flood evolution process.The coupled model was validated using three extreme storm events in the Wuhan Shahu small watershed. [Results] （1） The model constructed using the dynamic-scale zoning method exhibited significant performance，with over 85% agreement between simulated and observed inundation points，and good synchronization in rainfall-runoff trends. （2） Spatiotemporal analysis of flood risk across different years revealed a phased improvement in the risk pattern under the influence of changing underlying surface conditions： the area of low-risk clusters expanded from 6.2% to 26.4%，while the proportion of high-risk clusters decreased substantially and stabilized. The SWMM-LISFLOOD-FP coupled 1D-2D modeling framework based on the dynamic-scale zoning method demonstrated good effectiveness in identifying key high-risk areas and provided a reliable technical pathway for accurate flood risk identification in cities lacking underground pipe network data. （3） Parameter sensitivity analysis indicated that the sensitivity of all parameters gradually decreased with increasing storm intensity and slope. In highly urbanized areas，the surface runoff coefficient alone is insufficient to characterize surface ponding processes and must be calibrated in conjunction with physical hydrological parameters. [Conclusions] The dynamic-scale zoning method proposed in this study can effectively account for surface heterogeneity. Regional empirical results demonstrate the reliability of the coupled modeling framework in addressing long-term spatial changes and hydrodynamic coupling simulations，providing practical technical support for accurate flood risk assessment in highly urbanized areas. A limitation of this study is the lack of simulation for water accumulation at overpasses and subsurface flow in underground spaces. Future research should focus on more comprehensive and detailed validation of the applicability of this assessment framework in complex environments at larger scales.