Abstarct: Flood is one of the most important climatic events and the most serious dangerous natural disasters that threaten human societies. Today, urban development has led to land use change which is followed by impermeable surfaces. This causes less water to infiltrate into the ground, and as a result it increases the peak discharge and runoff volume. This causes a lot of human and financial risks in the city, so these runoffs must be controlled. For this purpose in this study using the SWMM model the flood runoff of Shahroud city was simulated. To predict runoff with this model the urban basin was first divided into 21 subbasins and then runoff from 8 rainfall was measured in 4 sub-basins that had two outlets next to Kabul Moghan and downstream of the University of Technology. The input parameters to the model were the equivalent width of the sub-basin, Sub-basin area, Manning coefficient of impermeable and impermeable areas, storage of impermeable and impermeable surfaces, storage of impermeable and impermeable surfaces, storage of impermeable and impermeable surfaces. For model calibration, 5 precipitation events on 10/4/2020, 11/4/2020 (Evening), 23/4/2020, 27/4/2020 (Evening) and 3/5/2020 and for validate the model, 3 precipitation events on 11/4/2020 (morning), 26/4/2020 and 27/4/2020 (morning) were used. Then the model was evaluated with RMSE, NRMSE, MAE and R^2 statistical indices. The results showed that the model was able to estimate the discharge in Moghan Kabul with R^2 =0.94, RMSE=0.25, NRMSE=0.3 and MAE = 0.17 and downstream of Industrial University with R^2= 0.93, RMSE = 0.14, NRMSE=0.27 and MAE = 0.08, at the calibration stage, and also it estimate discharge of the Kabul Moghan with R^2 = 0.93, RMSE = 0.17, NRMSE=0.22 and MAE = 0.12 and the downstream of the University of Technology with R^2= 0.93, RMSE = 0.18, NRMSE=0.23 and MAE = 0.12, at the verification. The results also showed that the model has an acceptable ability to simulate floods. The input parameters in order of the manning coefficient of the impermeable areas, storage of impermeable and impermeable surfaces, and the percentage of levels of impermeable areas are the most sensitive parameters that have the greatest impact on peak discharge and runoff volume. In addition, the capability of main surface water transmission networks in sub-basins with return periods of 2, 5, 10, 15, 20 and 25 years was investigated using the SWMM model. The results showed that some drainage canals with a return period of more than 5 years are not able to pass the volume of water flow and cause flooding of passages and streets drainage channels can be modified using the same model.