The Potential Impacts of Climate Change on the Agricultural Sector of Fars Province

Over the coming decades, global change will have an impact on food and water security and there are strong indications that developing countries will bear the brunt of adverse consequences from climate change. Agricultural sector is the most vulnerable to climate change, because of its dependence on water and temperature conditions. Consequently, it is important to understand the impacts of climate change on agriculture and natural resources in developing countries. The goal of this study was to estimate the potential impacts of climate change on Fars province’s agricultural sector. To this end, this study was organized in three sections. In the first section, time series data covering 21 years (1988-2008) on crop yields, climate or non-climate related variables were used to estimate yield response functions. In the second section, the yield equations were used to investigate the physical impacts of alternative scenarios. In the final section, a price-endogenous mathematical programming model was used to simulate the welfare impacts of yield changes under various climate change scenarios. Sixteen combinations of alternative climate change scenarios which include 0°, 0.27°, 0.54°, 2.35°centigrade for temperature and -13, -6.5, 0, +20 percents for precipitation were made based on the findings of Ravan (2010). The results showed that both temperature and precipitation had a significant but non-monotonic impact on crop yields. The comparison results indicated that climate change impacts on welfare were mostly positive and the impacts on producers were much more significant than they were on consumers. Social welfare decreases by 1.5 percent if the reduction of precipitation is associated with no change in temperature but it increases by 13 percent at the most humid and warmest scenario. Finally, it was found that temperature is more significant factor than rainfall in the change of social welfare.

Keywords:

Climate change , Fars province , Price endogenous spatial equilibrium model