Often parameters in hydrologic models cannot be measured directly and can only be inferred by a calibration process. This work addresses the application and comparison of three parameter uncertainty methods and their effects on the prediction of streamflow in Qezel Ozan watershed (43,000 km ) located in northwestern Iran. Methods of Partcle Swarm Optimization (PSO), DiffeRential Evolution Adaptive Metropolis (DREAM) and Sequential Uncertainty Fitting ver. 2 (SUFI2) were used in this study to calibrate a rainfall-runoff model created using the Soil and Water Assessment Tool (SWAT). The calibration and validation results indicated statistically insignificant differences among the three algorithms. The main difference was in their number of runs, where DREAM converged after 36000 runs, PSO after 6000 runs and SUFI2 after 1500 runs. SUFI2 proved to be a very efficient optimization algorithm, while PSO had the largest NS for calibration (0.59) and validation (0.74) periods.

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