The relationship between drought indicators and greenhouse gas emissions in Iran's agricultural sector

Evaluating the relationship between drought events and greenhouse gas emissions from agricultural activities is of particular importance due to their wide-ranging effects on the environment and economy. The purpose of this study is to investigate the relationship between the emission of GHGs resulting from the production of 18 main crops in the form of five dominant categories including; cereals (wheat, barley, rice and maize), legumes (alfalfa, bean, pea and lentil), oil seeds (soybean, sunflower, canola, safflower, castor, sesame and peanut), tubers (potato and sugar beet) and fiber (cotton) with drought indices including; Standard Precipitation Index (SPI), Standard Precipitation Evaporationtranspiration Index (SPEI), Standard Soil Moisture Index of the two upper soil layers (SSI1 and SSI2), Standard multivariable Drought Index including; MSDI1 based on precipitation and reference evapotranspiration (P&ETref), MSDI2 based on precipitation and soil moisture in the first soil layer (P&SM1) and MSDI3 based on precipitation and soil moisture in the second soil layer (P&SM2) in different climates of Iran (coastal wet, mountain, semi mountain, semi desert, desert and coastal desert) during the years 1980-2020. The results showed that the climatic variables of precipitation have no significant relationship with the increase in GHG emissions in different climates of Iran. If the ETref values during the years investigated in this study showed a significant trend. Also, the highest GHG emissions in 2019 were reported as equal to 443 million tons, and the highest GHG emissions were related to electric energy (47.1%) and nitrogen fertilizer (25.75%), respectively. Also, the evaluation of the effectiveness of drought indices for monitoring the effect of climate on GHG emissions showed a better display of SPI, SPEI and MSDI1 indices. The ability to calculate these indices in different time scales makes the effects of drought to be defined more accurately than using indices without this feature.