Parameter estimation of hydrological models is an important matter of hydrological forecasting. As the structure of the model isestablished, the calibration of parameters has great influence on the performance of the hydrological model. Practice experience suggeststhat the conventional calibration of hydrological models with single objective function is often inadequate to properly measure all of thecharacteristic of the observed data deemed to be important. To deal with this defect, the multi-objective evolution algorithm was employedto optimize the parameters of the Xinanjiang model with three runoff components in this paper. The results of the case study indicated thatwith well chosen objective functions, the multi-objective optimization can achieve better results than the single objective optimization. Furthermore, by analyzing the achieved the parameter combination, it is obvious that the phenomenon of same effect of different parametersexists, so as to do some preparations for the uncertainty analysis of the model parameters.