The coincidence of floods in the mainstream and its tributaries may lead to a large flooding in the downstream confluence area, and the flood coincidence risk analysis is very important for flood prevention and disaster reduction. In this study, the multiple regression model was used to establish the functional relationship among flood magnitudes in the mainstream and its tributaries. The mixed von Mises distribution and Pearson Type III distribution were selected to fit the probability distribution of the annual maximum flood occurrence dates and magnitudes, respectively. The joint distributions of the annual maximum flood occurrence dates and magnitudes were established using copula function. Fuhe River in the Poyang Lake region was selected as a study case. The joint probability, co-occurrence probability and conditional probability of flood magnitudes were calculated and compared with the simulated results of the observed data. The results show that the selected marginal and joint distributions perform well in simulating the observed flood data. The coincidence probabilities of flood occurrence dates in the upper mainstream and its tributaries mainly occur from May to early July. Among the three coincidence probability calculation methods, the conditional probability is the most consistent with the flood coincidence risk in the mainstream and its tributaries, which is more reliable and rational in practice. The results reflect the actual flood coincidence situation in the Fuhe River basin and can provide technique support for flood control decision-making.