Abstract: To explore the impact of rainfall patterns on the waterlogging resilience of urban rainwater systems based on the MIKE FLOOD platform, this paper conducts a study by using the bridge partition in the starting area of converting the new and old kinetic energy in Jinan.The waterlogging process scenarios are derived for 7 return periods, 3 rainfall durations, and 3 rainfall peak coefficients of the design rainfall. The system’s waterlogging resilience is quantified by using the Analytic Hierarchy Process（AHP） based on the amount, area, and average depth of waterlogging. The results show that the peak water accumulation and peak water accumulation area both increase with the increase in the return period and rainfall duration, and the average water accumulation depth fluctuates greatly. The system performance mainly fluctuates twice. The first fluctuation is caused by changes in rainfall intensity and the shallow depths cause the second in most of the depressions in the study area. As the return period increases, the system’s waterlogging resilience decreases, and the difference in rainfall corresponding to the extreme value of waterlogging resilience caused by the unit rainfall peak coefficient increases. Overall, the more centered the rainfall peak and the longer the rainfall duration, the lower the system’s waterlogging resilience.