Downscaled Analysis of Nature of Climate Changes and Determining the Climatic Scenarios of Agricultural Sector in Hamedan-Bahar Plain

The agricultural sector, as a biophysical-physical system, is heavily dependent on climatic conditions and climate is one of the main factors in determining the location, resources and productivity of agriculture. Hence, prediction of climate changes and evaluation of adaptive strategies to these changes will be effective in reducing damage. Atmospheric general circulation models are the perfect tools to long-term prediction of climatic parameters. But the main weakness of these models is their low spatial and temporal resolution that to overcome this problem, it is necessary in the process of downscaling, spatial and temporal scale model output is reduced. According to this approach, in this study, Downscaled analysis of climate change and determining the regional climatic scenarios in Hamedan-Bahar plain and also comparing them with national scenarios, with a blend of Positive Mathematical Programming model, yield-response regression model and LARS-WG model, were investigated. The results indicated that along with the increase in temperature at a rate of 0.54º C and decrease in rainfall at a rate of 3.4% in Hamedan-Bahar plain, value added of agricultural sector by 2020, will be reduced by 35 billion riyals. But if the average climatic conditions of Iran would be generalized to the plain, value added of agricultural sector by 2020, will increase by 21 billion riyals in the region. These results reveal the need for downscaling of climate forecasts and existence of mismatch between regional studies and national climatic scenarios.