When trying to analyze water resources supply and demand balance under climate change for river basin and irrigation district, the annual runoff of river and its monthly distribution in representative hydrological years are necessary and basic data to evaluate the available surface water supply. In order to predict the impacts of future climate change on runoff of Jinghe River, a SWAT model was developed by collecting and processing large amounts of data such as the hydrological, geological and meteorological data. The model was calibrated and validated by using 11 years monthly runoff data from Zhangjiashan hydrological station and evaluated with two targets (the Nash-Sutcliffe coefficient (Ns) and determination coefficient (R2)). Values of Ns and R2 in calibration and validation stages were both greater than 0.7, which meant that the model was capable of simulating runoff responses to climate change. Three representative hydrological years were chosen after analyzing and calculating the precipitation frequency, which were the wet year (25%), normal year (50%) and dry year (75%). Two future climate change scenarios were developed based on previous study, in which precipitation and temperature trends of future three periods (2020s, 2050s and 2080s) in Jinghe River were predicted by statistically downscaling the output data of HadCM3 under A2 and B2 scenarios, and the river annual runoff and its monthly distribution for representative hydrological years in three future periods were forecasted. The results showed that the annual runoff of representative hydrological years in three future periods of both scenarios were decreased, comparing with base years. The changing rates were 26%～42% and 25%～35%, respectively in wet year, 23%～37% and 21%～25% in normal year, 23%～38% and 20%～31% in the dry year. Under both scenarios, the distributions of monthly runoff of representative hydrological years in three future periods had the same trends as base years. And the changing trends of monthly runoff were basically conformed to the tendencies of monthly precipitation in corresponding scenarios and times. The major amplitudes of monthly runoff were appeared in the peak. In scenarios A2 and B2, the changing rates of peak value in three future periods respectively were 41%, 43%, 61% and 34%, 37%, 56% in August of the wet year, 15%, 23%, 38% and 21%, 18%, 31% in July of the normal year, 20%, 36%, 46% and 24%, 31%, 28% in June of the dry year. But the monthly runoff of February in three future periods under scenario B2 was increased from 17.71m3/s to 24.93m3/s, 38.79m3/s and 63.63m3/s, respectively. By calculating the nonuniform coefficient of the runoff annual distribution (Cvy), it was showed that the value of Cvy in wet year was decreased from 1.06 to 0.71 (scenario A2) and 0.74 (scenario B2).