Assessing the Uncertainty of SWMM Urban Flood Model Using GLUE Method Case Study: 2nd District Municipality of Tabriz

摘要: Given the complexity of urban environments, flood risk has increased in urban areas in recent years. In order to establish a correct urban management and the control and optimal use of surface water, the complex rainfall-runoff process in urban environments should be thoroughly understood. When dealing with urban basins, the shortcomings can list as the lack of precise input parameters, the lack of knowledge on the runoff producing processes, the lack of flow measurement system at the outlet of sub-basins needed for model calibration, and the Uncertainty in input parameters and results of mathematical and numerical models such as SWMM. This research investigated and analyzed the Uncertainty of SWMM Urban Flood model in District 2 of the Metropolitan Municipality of Tabriz, using the GLUE Method. In order to quantify the Uncertainty, the initial range of input parameters including CN, fraction of impervious surface, N (roughness) for pervious and impervious area were determined. Using the GLUE algorithm, initial sampling operations were performed using parametric space by lattice square sampling. According to the results of simulations and the magnitudes of observational events, 20% of the total outputs and the series of generated parameters were extracted as acceptable simulations. According to the results of the evaluation of the distribution diagrams, the input parameters of Imperv% and N Imperv were identified as sensitive parameters affecting the model simulation and the optimal range of parameters was obtained.