Based on the C-Vine Copula, a high-dimensional joint distribution model was constructed for three hazard factors in the main urban area of Wuxi City, including precipitation, water level, and upstream flow, with durations of 1,3, and 7 d. The complex nonlinear structures and dependencies between variable combinations were verified using correlation coefficients and tail dependence coefficients. The joint encounter risk rates and joint encounter return periods of variable combinations under different scenarios were calculated to explore the synergistic effects and dynamic feedback of multi-disaster-causing factors on urban flood disasters. The results show that the 7d three-variable combination in the main urban area of Wuxi City has the highest correlation, particularly demonstrating strong dependence in high extreme-value risks, with an upper tail dependence coefficient as high as 0.6718. The joint encounter risk rate is the highest for the three-variable combination, followed by the two-variable combination, and the lowest for the single-variable combination. When the return periods of precipitation, water level, and flow are all 10 a, the joint encounter risk rate for the 7d three-variable combination is 21.26%, while those for the two-variable combinations are 18.39%, 18.37%, and 13.27%, respectively. For the joint return period reduction rate of the three-variable combination, the 1 d combination is mainly influenced by upstream flow, with a maximum joint return period reduction rate of 29.2%, while the 3d and 7d combinations are primarily influenced by precipitation, with maximum joint return period reduction rates of 29.4% and 32.7%, respectively. Keywords: urban flood; hazard factor; C-Vine Copula; tail dependency; joint encounter risk rate; joint encounter recurrence period; Wuxi City 〖FL