Abstarct: The current study was carried out to investigate the impacts of climate change on the hydrological parameters including precipitation, temperature, and runoff as well as the quality of surface water resources in the Balikhli-Chai basin in Ardabil province, Iran. In this study, by downscaling the model of LARS-WG, the outputs of HADCM3 model under the A2 scenario across Balikhli-Chai basin in the time intervals of 2011-2030, 2046-2065, and 2080-2099 were scaled down. The results indicate a temperature rise of about 5 °C and an annual precipitation reduction of 14 mm in the period of 2080 to 2099. Then, using the Artificial neural network approach, the input runoff of Yamchi dam in the three intervals of interest was assessed and its hydrograph was plotted. The obtained results suggest 11, 13, and 17% reduction in the dam input runoff for the three given intervals. In the final step, by employing the parameters of temperature, precipitation, and runoff and using the neural network model, the variations of TDS and EC values, which are considered as important parameters for the water quality in the drinking and agricultural water, respectively, were assessed under climate change conditions. The corresponding results showed an increase (3%) in all parameters. The increasing rate of TDS and EC in summer would be more severe as hotter and more arid summers is predicted for the years to come. Therefore, baxsed on the results of this study, a more effective water resource management and application of suitable policies for the surface water is suggested for the future.