Climate change is a typical scientific term representing the climatic variations across the globe, mainly resulting from the increase of the global average temperature Given the fundamental role that climate plays to form the natural ecosystems and the human economy as well as the civilizations on which they are based, the fight against this phenomenon is of great importance. For this reason, today the phenomenon of climate change is a matter of great concern to scientific and even political assemblies, contributing extensive studies to be done on its effects on water resources. Predicting the future amounts of precipitation and runoff subject to climate change impacts as well as increasing water use and the restrictions to exploit the water resources, are all serious challenges the water resources managers are engaged with. For this purpose, one of the management approaches to mitigate the negative effects of climate change is to predict how the reservoirs will be operated, as water supply and demand management will need to be different from what is already done, and a new approach should be adopted. This study was conducted to investigate the effects of climate change on the temperature and precepitation and consequently the amount of runoff generated upstream of Zayandehrood Dam. Then, the operation of the Zayandehrood Dam reservoir is optimized using grey wolf optimizer (GWO) and its improved version, proposed for the first time in this thesis, utilizing a velocity term in its updating procedure, and hence named Velocity-Aided GWO (VAGWO). Six GCM models have been used to investigate climate change over the 30 year period 2020-2049 under three climate change scenarios RCP2.6, RCP4.5 and RCP8.5. According to the accuracy of GCM models in predicting temperature and precipitation parameters, these models are weighted and then climate change scenarios were constructed using GCM data. In this study, the LARS-WG model was used for Downscaling of daily temperature and precipitation data. Two different HEC-HMS models have been used to simulate the runoff generated at the upstream of the Zayandehrood Dam which is measured in two main branches, named Ghale Shahrokh and Eskandari as well as the transferred surface water through the first and second Koohrang and the Langan spring tunnels. Downstream water use of the Zayandehrood basin has also been estimated through assuming three different scenarios. The first scenario represents extending the increasing trend of the water demands, the second scenario represents launching the third Koohrang tunnel water transfer to the first scenario, and the third scenario represents a water management scheme to reduce the water demands. Finally, the optimization of the Zayandroud reservoir operation is mainly aimed at reducing the difference between supply and demand. Generally, the VAGWO algorithm performs better than GWO in minimizing the objective function. The results also suggest that in all the scenarios, the VAGWO algorithm calculated the water demands to be met by more than 92%, while maintaining the reservoir storage at the end of each water year to be close to the storage target set to be 450 million cubic meters. Key Words: Climate change, Zayandehrood basin, Temperature and Precipitation, Runoff, HEC-HMS model, LARS-WG model, Reservoir Operation, Grey Wolf Optimizer.