为揭示不同设计暴雨条件下城市内涝演化特征及危险性分布规律，以上海市浦西七区为研究对象，基于TELEMAC-2D二维水动力模型构建内涝仿真框架，在20、50、100 a一遇设计暴雨情景下对区域内涝过程进行数值模拟，分析最大淹没水深、洪水流速分布、淹没面积及积水量特征，并基于洪水危险性开展内涝危险性分区。结果显示，研究区内涝整体由浅水、低洪水流速和低危险占主导，随降雨重现期由20 a增加至100 a，深水区（淹没水深>0.5 m）面积占比由1.63%升至4.06%，高洪水流速区（>0.4 m/s）由0.66%增至1.30%，最大淹没面积与积水量增幅分别达15.8%与33.8%；中、高及以上危险区面积占比由17.35%提高至30.77%，高、超高危险区呈斑块零散分布，集中于低洼、排水受限区域。研究结果可为上海中心城区内涝风险识别与精细化防治提供科学依据。

[Objective] Urban waterlogging has become an increasingly critical issue in highly urbanized coastal megacities，where flat terrain，high imperviousness，and limited drainage capacity amplify flood hazards under extreme rainfall. Quantitative comparisons of hazard evolution under multiple design rainfall scenarios remain limited. This study focuses on the central districts of Shanghai，a representative coastal megacity，and aims to （1） analyze the evolution characteristics of urban waterlogging under different rainfall return periods，and （2） identify the spatial distribution patterns of flood hazard based on hydrodynamic simulation results，providing a quantitative reference for urban flood risk management. [Methods] A two-dimensional hydrodynamic model based on TELEMAC-2D was applied to simulate urban waterlogging processes in the central districts of Shanghai，covering seven densely built districts with nearly 100% impervious surfaces. Design rainfall events corresponding to 20-，50-，and 100-year return periods were constructed according to local standards. Surface runoff generation was represented using the Horton infiltration model，while drainage processes were approximated through an equivalent parameterization approach due to the lack of detailed pipe network data. Model outputs included time-series water depth and flow velocity fields. Based on these，maximum inundation depth，peak flow velocity，inundation extent，and total water volume were derived. Flood hazard was evaluated using the Flood Hazard Rate （HR），which integrates water depth，flow velocity，and a depth-dependent adjustment factor. Hazard levels were further classified to enable spatial comparison across scenarios. Model performance was evaluated by comparing simulated inundation areas with historical waterlogging points and by assessing simulated water depths against observed data from a typical rainfall event. [Results] （1） Model performance： The comparison with historical waterlogging records shows that the model effectively captures the spatial distribution of inundation-prone areas. Simulated water depths are in good agreement with observed values for typical rainfall events，indicating that the model can well reproduce the main characteristics of urban waterlogging processes. （2） Hydrodynamic characteristics： Urban waterlogging in the study area is predominantly characterized by shallow water depths （<0.15 m），low flow velocities，and overall low hazard levels across all scenarios，reflecting the flat terrain and existing drainage capacity. （3） Response to rainfall intensity： As the rainfall return period increases from 20 to 100 years，the proportion of deep inundation areas （>0.5 m） increases from 1.63% to 4.06%，while high-velocity areas （>0.4 m/s） increase from 0.66% to 1.30%. The maximum inundation area expands by 15.8%，and total water volume increases by 33.8%，indicating that flood intensification is mainly reflected in increased water depth and accumulation rather than spatial expansion.（4） Hazard distribution： The proportion of medium，high，and above hazard zones increases from 17.35% to 30.77% with increasing rainfall intensity. High and very high hazard areas exhibit fragmented and patchy spatial patterns and are mainly concentrated in low-lying areas and regions with limited drainage capacity. （5） Spatial heterogeneity： Hazard escalation is highly heterogeneous. Instead of uniform expansion，localized amplification dominates，where minor topographic depressions and drainage constraints lead to disproportionately high hazard levels. [Conclusions] Urban waterlogging in central Shanghai is generally dominated by shallow depth and low hazard under typical rainfall conditions； however，increasing rainfall intensity leads to a clear amplification of high-hazard areas. This intensification is primarily driven by increased water depth and localized accumulation rather than uniform spatial expansion.The results highlight that flood hazard distribution is strongly influenced by local terrain and drainage conditions，and mitigation efforts should prioritize low-lying and drainage-limited areas. The TELEMAC-2D model can well reproduce both the spatial pattern and magnitude of urban waterlogging，supporting its applicability for scenario-based flood analysis in highly urbanized areas.