عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Nowaday, the impact of global warming and climate change because of the increased effects of greenhouse gases in the atmosphere has been observed in many natural systems. All the general circulation models of the atmosphere predict warmer future for the earth. Hydrological processes such as rainfall and river flows as one of the main sources of water supply basins could be affected in such circumstances. Due to the low spatial resolution or simplification of some micro-scale phenomena in atmospheric general circulation models, these models cannot be employed for accurate approximation of the climate of the considered area, therefore, their output must be down scaled to the meteorological station range. In this study, the data of HadCM3 general circulation model down scaling with the use of LARS-WG model under two scenarios A2 and A1B and Parameters of daily rainfall, minimum temperature and maximum temperature of the Sufi-Chi basin generated for three periods (2011-203, 2046-2065-, 2080-2099). To assess the effect of climate change on runoff is used from artificial neural networks and genetic programming of intelligent model. The results indicate that the rainfall will increase in 2011-2030 and will decrease in the further future. Also the maximum and minimum temperatures will gradual increase in three periods of future and the amount of runoff will decrease in future than current time.