[Objective] With urban flooding getting more frequently，assessing the resulting disruption of traffic networks is essential for urban resilience and emergency planning. This study develops a tightly coupled modeling and evaluation framework to quantify how urban flooding affects road network performance over time. The aim is to capture not only localized flooding impacts but also the system-wide and delayed effects on traffic efficiency and network structure. [Methods] An integrated framework was established by coupling a one-dimensional drainage model （SWMM），a two-dimensional surface flooding model based on Cellular Automata （CA），and the microscopic traffic simulation platform SUMO （Simulation of Urban Mobility）. The proposed Urban Road-masked Cellular Automata-SWMM coupled model （URCA） enables bidirectional interaction between underground pipe flow and surface road inundation at minute-level time steps. Exchange flows between the drainage system and road surface are calculated through manholes and gullies using modified hydraulic equations. Runoff from sub-catchments is simulated within SWMM，while road-related surface flow is represented in the CA model，which incorporates land-use-based infiltration，Manning-based routing，and adaptive time stepping for numerical stability. Simulated water depth on road grids is translated into traffic control rules in SUMO using predefined depth thresholds that trigger speed reduction or road closure，ensuring dynamic feedback between flood evolution and traffic redistribution. The road network is represented as a weighted directed graph integrating static road attributes and dynamic traffic indicators. Flood impacts are evaluated using average travel time increase （T_E%），OD-based time expansion rates，network coverage，and the 0th Betti number to quantify changes in connectivity under different time budgets. The framework is applied to a 3.89 km² urban area in Wuhan under a 20-year return-period rainfall event. [Results] Model calibration shows stable hydraulic performance，with a mass balance error of 2.97% and a Nash-Sutcliffe efficiency of 0.88. Under the 20-year rainfall scenario，flooding produces strong nonlinear traffic impacts. Although only 37 road segments （approximately 6% of 618 links） are significantly inundated，the average network travel time increases to 508% of the baseline level，equivalent to an effective network radius expansion of about 700 meters. This indicates that limited localized flooding can induce substantial system-wide degradation. Travel time exhibits multiple peaks during and after rainfall，with the maximum delay occurring after rainfall cessation，demonstrating a clear lag effect. Time-budget analysis shows that approximately 12 additional minutes are required to achieve baseline coverage，corresponding to a time expansion factor of 2.23. Network coverage declines sharply during critical periods，while Betti-0 analysis indicates increased fragmentation，especially within shorter time budgets. Trips within 40 minutes are the most affected. A small number of fully blocked or severely congested links account for most of the performance decline. [Conclusions] Urban flooding can cause significant increases in travel time，structural fragmentation of road networks，and delayed peak disruption after rainfall ends. A limited proportion of critical links can trigger large-scale performance degradation，and short-distance travel is particularly vulnerable. By tightly coupling drainage and traffic processes and integrating functional and structural network indicators，this study provides a comprehensive approach for assessing flood impacts and supporting resilience-oriented urban planning.