Abstract: In order to investigate the evolution law of flood processes and the status of flood risk in upstream Huangtaiqiao area of the Xiaoqinghe River basin, Jinan City, a coupled flood model integrating SWMM and Infoworks ICM-2D was developed. The main parameters of the SWMM model were calibrated using a genetic algorithm with an elite retention strategy. The model was applied to simulate and analyze the pipeline network drainage capacity, surface inundation status, and hazard distribution under different rainfall with various return periods. The results showed that the improved genetic algorithm could quickly optimize the model accuracy to a high level in a short time, significantly improving the efficiency of parameter calibration; the coupled model exhibited good applicability in the study area. With the increase of rainfall return period, the number of overloaded pipes and overflow nodes in the pipeline network increased significantly; the capacity of the underground pipeline network was basically saturated at the 10 a return period, and the waterlogging risk rose rapidly when the return period exceeded 10 years; The total inundated area of the river basin increased from 573.38 hm² at the 5 a return period to 956.26 hm² at the 100 a return period, with areas of high water depth concentrated on major roads such as the Erhuan Road.(S), Jingshi Road, and Lashan Interchange; the flood risk level continuously increased with the extension of return period, and the area of high-risk areas continued to increase — during the return period from 5 a to 100 a, the area of relatively high-risk zones and high-risk zones increased by 151.11 hm² and 263.50 hm², respectively. The study area showed a certain risk resistance capacity against short-return-period rainfall, but targeted waterlogging prevention measures should be prioritized under extreme rainfall conditions.