Parameter uncertainty analysis of rainfall-runoff models is very important especially in urban watersheds due to the high flood risk in these areas. Among the different methods available for uncertainty analysis, bootstrap method gained popularity in view of its flexibility. Hence, this study aims to conduct the parameter uncertainty analysis of the urban storage function (USF) model, a storage function model specifically developed for the urban watersheds, using the model-based bootstrap method. We successfully evaluated the uncertainty of USF model parameters and the results exhibited that the 95% confidence interval of all parameters is wide compared with the search range during parameter estimation except for two parameters. Moreover, the parameters with the highest and least uncertainties were identified. Further, model simulation efficiency using the estimated parameters was found to be high with a Nash-Sutcliffe Efficiency value of 97%. Lastly, the effect of parameter uncertainty on model simulation uncertainty was analysed and found that the SCE-UA method along with the model-based bootstrap method can predict, on an average, 68% of observed data within the simulation uncertainty range of USF model.