This study examines the influence of rainfall data with different time resolutions on urban waterlogging simulations using a 1D-2D coupling model

namely GAST-SWMM (GPU Accelerated Surface Water Flow coupled with Transport Model-Storm Water Management Model). Different interpolation methods are used to improve time resolution

and the best one is determined. Nash coefficients and peak errors are compared to evaluate the simulated flow hydrographs against the measurements for Tianfu Heyuan District

Xi'an City. We examine three methods－fractal interpolation

Lagrange interpolation and linear interpolation－using a time interval range of 5 min to 60 min. The results show the Nash coefficient of the model is 0.85 and 0.81 for two rainfall events

indicating its high accuracy. Of the five sets of different rainfall time resolutions studied

the one of 5min gives the highest simulation accuracy. A lower resolution results in a greater deviation of the simulation from measurements

and the worst case occurs when the interval is 60 min. We find that fractal interpolation has the best agreement with measurements

followed by Lagrange interpolation

and linear interpolation is the poorest. This study can provide a basis for the selection and processing of rainfall data for urban waterlogging simulation.