SWMM (storm water management model) has been widely used in the world as a typical model for runoff analysis and water quality. However, there are many uncertain parameters in the watershed runoff continuous simulation module and water quality module, which make it difficult to use SWMM. Model calibration and verification are mostly necessary to improve model results. Calibration of model, however, may be an obstacle to easy application. To help these problems, we developed an automated calibration module of SWMM linked with SCE-UA (shuffled complex evolution-University of Arizona) that is a global optimization algorithm developed by Duan (1991). In the study, the automatic calibration module of SWMM was validated by calibration and verification of the watershed runoff continuous simulation and water quality simulation model for Donghyang Stage Station Basin, Korea. The procedure for calibrating watershed runoff continuous and water quality simulation were divided into two steps. The watershed runoff continuous simulation model was automatically calibrated first, with twenty-two estimation parameters of watershed runoff including twelve parameters in the groundwater module. Second, the automatic calibration tool estimated water quality parameters with fixed watershed runoff parameters estimated from the first step. In the study, four water quality constituents were simulated (BOD, COD, TN and TP). The number of water quality simulation parameters for estimation was nine, four of them are pollutant information and five of them are about buildup and washoff. We used the objective function of root mean square error in the automatic calibration. Three assessment indexes for the model calibration result were used: NSE (Nash-Sutcliffe efficiency), PBIAS (percent bias), RSR(RMSE-observation standard deviation ratio). The calibration results for watershed runoff continuous simulation model were excellent and those for water quality simulation model were generally satisfactory. The automatic calibration module for SWMM could be used in various studies and designs for watershed runoff and water quality analyses. This research was supported by a grant (11-TI-C06) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.