Document Type : Original Article

Authors

• Mostafa Yaghoobzadeh ¹
• Alireza Moghri friz ²
• omid khorashadizadeh ³
• hamed javadi ⁴
• Elham ghochanian haghverdi ⁵

¹ 2- Department of Water Science and Engineering & Drought and Climate Change Research Group, Faculty of Agriculture, University of Birjand, Birjand, Iran

² water and soil research department, South Khorasan Agriculture and Natural Resources Research and Education Center, AREEO, Birjand, Iran

³ 3- Regional Water Company of south Khorasan, Water Resources Management Company, Birjand, Iran

⁴ 1- Soil and Water Research Department, South Khorasan Agriculture and Natural Resources Research and Education Center, AREEO, Birjand, Iran

⁵ water and soil research department, South Khorasan Agriculture and Natural Resources Research and Education Center, AREEO, Birjand, Iran 2- PhD student in Water Resources, Department of Water Science and Engineering, Faculty of Agriculture and Natura

Abstract

The agricultural is one of the first sectors to be affected by changing climate. The reduction of water resources, the use of new methods in water consumption management in the farm and determining the real needs of the plant are occurred more than in the past to changing climate adaptation. One of the most important parameters for precise management of agricultural water is called vapor pressure deficiency, which is used in climatology, agriculture and other related fields due to its effect on the flow of moisture from the surface to the atmosphere and the water balance globally. In this research, firstly, the estimation of vapor pressure deficiency was done from the reanalysis data of JRA-55 database during 1958 - 2023. In the next step, a long-term study of changes in vapor pressure deficiency and its effect on saffron yield was conducted in four areas of South Khorasan province, including Birjand, ghaen, Sarayan, and Tabas. The results in the above mentioned areas over the past 60 years showed a gradual increase in the average annual vapor pressure deficiency with an average rate of about 60 pascals per decade and an annual decrease in saffron yield of about 0.16 kg per hectare. finally,the yield of saffron was predicted based on vapor pressure deficiency using artificial intelligence algorithms including generalized additive model, random Subspace, random Forest and M5P. The performance of the random forest model was better than other models in the training and testing stages, respectively This research recommends the use of random forest model for future studies of saffron yield prediction based on vapor pressure deficiency in water consumption management

Keywords

• Saffron
• Vapor Pressure Deficit
• Climate Change
• Artificial Intelligence
• Random Forest