Abstarct: Climate change affects many climatic phenomena, hydrological cycles, etc. This research investigated changes in surface water resources due to climate change in the Gorganrood basin. For this purpose, the monthly rainfall and temperature data of three models GFDL-ESM4, MRI-ESM2-0, and BCC-CSM2-MR from the set of CMIP6 models under SSP245 and SSP585 scenarios were used for the baxse period from 1975 to 2014 and the future period from 2020 to 2059. By comparing observational data and similar data in the baxse period, the best models were identified by NRMSE, R2, and KGE statistical measures. GFDL-ESM4 model for the precipitation variable and MRI-ESM2-0 model for the temperature variable showed the best performance in simulation. Generally, general cycle models have a good performance in temperature simulation in Iran; But they have a weak ability to simulate precipitation. In the following, the best top models were downscaled using the change factor method for the future period, and monthly time series of precipitation and temperature data were generated. The results of the climate simulation under the SSP245 and SSP585 scenarios will show a decrease in the annual rainfall of this basin from about -2 to -9 percent and an increase in the annual temperature of about 13 to 15 percent compared to the observation period. To generate the future runoff, the IHACRES model was used, and after calibrating the observed runoff data from 1975 to 1998, the downscaled data of future precipitation and temperature from 2020 to 2059 were entered into it under the SSP245 and SSP585 scenarios. Its results indicate that the greatest increase in future runoff compared to the observation period is related to the spring and winter seasons, which is related to the melting of snow in these seasons. Also, the greatest decrease in runoff in both scenarios is related to the fall season. To investigate the effect of climate change on the allocation of surface water resources, the WEAP model was used. The results showed that in the future we are facing an increase in the unmet demand for agriculture. Also, baxsed on the reliability index, the lowest value is related to the SSP585 scenario and the highest value is related to the SSP245 scenario, which depends on the pessimistic order of the scenarios.