Urban agglomeration polders (UAPs) are often used to control flooding in eastern China. The impacts of UAPs on individual flood events have been extensively examined, but how flood risks are influenced by UAPs is much less examined. This study aimed to explore a three-dimensional joint distribution of annual flood volume, peak flow and water level to examine UAPs’ impact on flood risks based on hydrological simulations. The dependence between pairwise hydrological characteristics are measured by rank correlation coefficients and graphs. An Archimedean Copula is applied to model the dependence structure. This approach is applied to the Qinhuai River Basin where UAPs are used proactively for flood control. The result shows that the Frank Copula can better represent the dependence structure in the Qinhuai River Basin. UAPs increase risks of individual flood characteristics and integrated risks. UAPs have a relatively greater impact on water level than the other two flood characteristics. It is noted that the impact on flood risk levels off for greater floods.

Based on the constructed SWAT model in the Qinhuai River Basin, the hydrological response of flooding under different scenarios of temperature and rainfall change is analyzed. The Copula function is then used to calculate and analyze the multivariate flood risk. The results show that the flood peaks increase with the increase of precipitation and decrease with the increase of temperature. The hydrological response of light floods to temperature changes is stronger than that of medium and heavy floods. Additionally, the temperature drop and the precipitation increase lead to a higher flood risk. The flood risk of flood peaks is more sensitive to changes in precipitation.