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Climate change is a complex and long-term global atmospheric-oceanic phenomenon which can be influenced by natural factors such as volcanoes, solar, oceans and atmosphere activities which they have interactions between or may be as a result of human activities. Atmospheric general circulation models are developed for simulation of current climate of the earth and are able to predict the earth's future climate change. In this paper, the performance of GFDL CM2.1, CSIRO Mk3 and HadCM3 AOGCMs were assessed and evaluated in the study of the climate change effects on temperature and precipitation in Taleghan basin. The results show that HadCM3 model in comparison with CSIRO Mk3 and GFDL CM2.1 models has indicated the better performance in this region.

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Dam reservoir operation plays a fundamental role in water management studies and planning. This study examined three policies to improve the performance of reservoirs: Standard Operation Policy (SOP), Hedging Rule (HR) and Multi-Objective Optimization (MOO). The objective functions were to minimize the LSR (Long-term Shortage Ratio) for HR and to minimize MAE (Mean Absolute Errors of released water) for SOP. MOO’s objective function was to reduce vulnerability and maximize reliability indexes. The research was conducted in two time periods (1985–2005 and 2025–2045). Combining EPO (Empire Penguin Optimization) algorithm and Gene Expression Programming (GEP) with elementary arithmetic (EOPba) and logical operators (EPOad) modified HR and SOP policies. Multi-Objective EPO (MPOEPO) and GEP with trigonometric functions were used to create a multi-objective policies formula. The results showed that the generation of the operation rules with EPOad increased the dam reservoir Performance Indexes (Vulnerability and Reliability Indexes) compared to EPOba. Moreover, HR application compared to SOP improves the mean dam reservoir’s Performance Indexes by about 12 and 33% in the baseline and 12 and 21% in the future period (climate change conditions), respectively. The MOO method (MOEPO) improved the Vulnerability and Reliability Indexes by about 36 and 25% in the baseline and by 31 and 26% in the future, respectively, compared to SOP.

Among the solutions to climate change’s harmful effects, AS (Adaptation Strategies) are more feasible. In this study, four AS, Changing Cultivation Dates (CCD), Deficit Irrigation (DI), Improving Irrigation Performance (IIP), and Optimizing the Crop Pattern (OCP), were investigated. The results showed that the WUE (Water Use Efficiency) was declined when the cultivation date was changed for all crops in the baseline and increased after the cultivation date was brought forward to 7,14,14,28,28 days for tomato, wheat, corn, barley and cucumber, respectively, in the future period. Deficit irrigation of 30% increased the WUE in all crops. A 48% increase in irrigation performance reduced demand by 10%. Following the OCP and diminishing the cultivation area by 30% increased farmers’ total profit and reduced the water consumption volume by 9% and 11%, respectively, in the baseline and future periods. To study the effect of these AS on crop yield and allocated volume, a combination of crop model programming and the MOEPO (Multi-Objective Emperor Penguin Optimizer) was employed to minimize Vulnerability and maximize Reliability Indexes (Performance Indexes). In the supply section, three scenarios were examined. The results showed that DI, IIP, CCD and OCP were classified from the most to the least option based on improving the Performance Indexes.