For the calibration of rainfall-runoff model, automatic calibration methods are used insteadof manual calibration to obtain the reliable modeling results. When mathematical programmingtechniques such as linear programming and nonlinear programming are applied, there is apossibility to arrive at the local optimum. To solve this problem, genetic algorithm is introducedin this study. It is very simple and easy to understand but also applicable to any complicatedmathematical problem, and it can find out the global optimum solution effectively. Theobjective of this study is to develope a parameter optimization program that integrate a geneticalgorithm and a rainfall-runoff model. The program can calibrate the various parametersrelated to the runoff process automatically. As a rainfall-runoff model, SWMM is applied. Theautomatic calibration program developed in this study is applied to the Jangcheon watershedflowing into the Youngrang Lake that is in the eutrophic state. Runoff surveys were carried outfor two storm events on the Jangcheon watershed. The peak flow and runoff volume estimatedby the calibrated model with the survey data shows good agreement with the observed values.