The short- and long-term impacts of climate change on the irrigated barley yield in Iran: an application of dynamic ordinary least squares approach

Environ Sci Pollut Res Int. 2022 Jun;29(26):40169-40177. doi: 10.1007/s11356-022-19046-9. Epub 2022 Feb 4.

Abstract

Given the extensive impacts of climate change on the agricultural sector and their interactions, the climate change is known as one of the main factors influencing agricultural production. The present study aims to explore the short- and long-term impacts of climate change on the yield of irrigated barley in 28 Iranian provinces over the 1999-2015 period. The research uses panel data and dynamic ordinary least squares (DOLS) method. The study also estimated the threshold levels of temperature and rainfall which confirmed an inverted U-shaped relationship between climate change variables and irrigated barley yield. The threshold levels of temperature and rainfall are estimated to be 15.48 °C and 239 mm, respectively; beyond these threshold levels, the increase in temperature and rainfall have negative impact on barley yield in Iran. The long-term elasticity of temperature shows that the yield will be reduced with the increase in temperature in the long run. Same is the case with the precipitation and barley yield. The findings of the study suggest the need of a comprehensive national climate change policy and alignment of sectoral policies with it mitigate and adapt the climate change and global warming. Moreover, it also provided the guidelines for the government and policy-makers to introduce the use of modern eco-friendly and resource saving technologies such as water-saving methods of irrigation, use of fertilizer in required quantities, and improved seeds use. The government should also introduce the climate change awareness programs especially for farmers.

Keywords: Agricultural yield; Climate change; DOLS; Iran; Irrigated barley; Panel data; Precipitation; Temperature rise.

MeSH terms

  • Agriculture
  • Climate Change*
  • Hordeum*
  • Iran
  • Least-Squares Analysis