Process-oriented SWMM real-time correction and urban flood dynamic simulation

The real-time calibration of SWMM runoff parameters is of great significance for the accurate simulation and prediction of urban flooding. Many studies correct SWMM based on the characteristic indicators of the flood. The model parameters do not change during the flooding process, making the model effective in simulating historical flooding but poor performance in the prediction process. By analyzing the distribution characteristics of urban waterlogging points, a real-time model calibration method is proposed to adjust the model parameters from time to time during the flooding process to minimize the error between the water depth of the waterlogging point and the measured water depth. A practical application in the central area of Zhengzhou, China, the results show that the method can accurately fit the water depth process within 4 iterations and final Nash efficiency coefficients (NSE) are all above 0.8. The process-oriented real-time calibration of SWMM runoff parameters can endow the model with dynamic correction capability and improve the simulation accuracy of the flooding process, which has important fundamental significance for flood loss assessment and risk assessment.