In response to the problem of urban waterlogging caused by short-term heavy rainfall, a risk assessment index system for waterlogging in the central urban area of Zhengzhou was constructed based on multi-source data and SWMM simulation, considering rainfall characteristics, underlying surface attributes, socio-economic attributes, and pipeline operation attributes. Two-dimensional joint distribution models of precipitation, rainfall intensity, and waterlogging risk were established by introducing the Copula function. The results indicate that precipitation, rainfall intensity, impermeability rate, average slope, and population density are important factors affecting the risk of waterlogging in the central urban area of Zhengzhou. Insufficient drainage capacity of the pipeline network will exacerbate the risk of waterlogging. Among 155 short duration rainfall events, the proportion of medium risk and high-risk events was 53.5% and 22.6%, respectively, indicating that the drainage system in the study area needs to improve its carrying capacity for moderate and above intensity rainfall. The calculation results of the Copula joint distribution model show that the synchronous encounter probability between precipitation and waterlogging risk is 87.2%, and the synchronous encounter probability between rainfall intensity and waterlogging risk is 59%, indicating that both precipitation and rainfall intensity are important influencing factors of waterlogging risk.