عنوان مقاله [English]
نویسندگان [English]چکیده [English]
The most reliable method for simulation of climatic changes in the future, based on the climatic changes is the use of General Circulation Models (GCMs) which are of large scales which needs to be downscaled. In this study, the daily temperature and precipitation data gathered in the Uremia synoptic station, located in the north west part of Iran, 1971- 2000, were used to be inserted in the fine-scale climate Input Software, DSM. Considering the two A2 and B2 scenarios for statistical period of2000- 2099, the temperature will increase by 0.45 and 0.35° C and rainfall will increase by10% and 9%, respectively in the future.
At the end of the study and under these scenarios, both the flow rate of the river and the conditions of the floods on the surface of the catchment were estimated for the future period. It was performed using the predicted precipitation and temperature data gathered from the local model and the runoff patterns of the Nazloochaei River within the base period as well as the artificial dynamic neural networks. These estimates suggested that the river runoff during the next period under the above dispersion scenarios increased by 48 and 49%.