Rising concentration of greenhouse gases may have significant consequences for the global climate with highest effect in human life and agricultural sector. Therefore, forecast of climate changes in future is essential. The climate changes was known to force local hydrology, through changes in the pattern of precipitation, temperature and other hydrological variables. Global climate models (GCMs) have been made for estimation of future climate changes. However, the coarse resolution of GCMs are generally greater than 2.0 for both latitude and longitude. Therefore, there is a need to downscale the prediction of GCMs to local and regional scale. In this study, ASD software based on statistical downscaling have been used for estimating the daily precipitation and temperature (maximum and minimum) on stations of Zayandehrud Dam basin. Outputs of two GCM models (HadCM3 and CGCM3) under two climate change scenarios (A2 and B2) for two period times of 2020-2049 and 2070-2099 were used in ASD. The results indicate the simulated minimum and maximum temperature has increased in future periods and the rate of increasing is much higher in maximum temperature than in minimum temperature. Predicted mean annual precipitation has decreased for all scenarios and the pattern of precipitation will change in various seasons. Maximum decrease in precipitation were expected for HadCM3-A2 in 2070-2099 period equal 10.55 percent and minimum decrease in precipitation were expected for HadCM3-A2 in 2020-2049 period equal 4.04 percent. In the next phase outputs of ASD have been get with the SWAT model. We use SUFI-2 algoritm for calibrating SWAT model’s parameters. The results show that streamflow increases in autumn because of more precipitation. Although the amount of precipitation decreases in winter the amount of runoff will increase because of more rainfall due to highest temperature. The results also show that earlier snowmelt resulting in an earlier spring runoff caused shift in peakflow for all scenarios and both periods. Predicted annual runoff will decrease for all scenarios and both periods. Maximum decrease in runoff were expected for HadCM3-A2 in 2070-2099 period equal 18.35 percent and minimum decrease in runoff were expected for CGCM3-A2 in 2020-2049 period equal 7.06 percent. Keywords: Climate Change, General Circulation Models, Statistical Downscaling, ASD, SWAT, SUFI-2
