Accurate analysis of water flow pathways from rainfall to streams is critical for simulating water use, climate change impact, and contaminants transport. In this study, we developed a new scheme to simultaneously calibrate surface flow (SF) and baseflow (BF) simulations of soil and water assessment tool (SWAT) by combing evolutionary multi-objective optimization (EMO) and BF separation techniques. The application of this scheme demonstrated pronounced trade-off of SWAT's performance on SF and BF simulations. The simulated major water fluxes and storages variables (e.g. soil moisture, evapotranspiration, and groundwater) using the multiple parameters from EMO span wide ranges. Uncertainty analysis was conducted by Bayesian model averaging of the Pareto optimal solutions. The 90% confidence interval (CI) estimated using all streamflows substantially overestimate the uncertainty of low flows on BF days while underestimating the uncertainty of high flows on SF days. Despite using statistical criteria calculated based on streamflow for model selection, it is important to conduct diagnostic analysis of the agreement of SWAT behaviour and actual watershed dynamics. The new calibration technique can serve as a useful tool to explore the trade-off between SF and BF simulations and provide candidates for further diagnostic assessment and model identification. Copyright © 2011 John Wiley & Sons, Ltd.