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Modified version for SPEI to evaluate and modeling the agricultural drought severity

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Abstract

Drought is a climatic phenomenon that can occur in various regions with different climate conditions. Generally, drought has negative impacts on different fields such as environment, rangelands, and water resources. The agricultural section (especially rain-fed agriculture) is one of the parts that is directly affected by different types of drought especially meteorological and agricultural droughts. The standardized precipitation evapotranspiration index (SPEI) is one of the newest and most applied indices to assess drought characteristics. In this paper, a modification is suggested for SPEI with the substitution of observed precipitation (OP) with effective precipitation (EP) to evaluate drought, with an emphasis on consideration of drought effects on agricultural section. To calculate EP, Food and Agriculture Organization of the united nation method (FAO), US Bureau of Reclamation (USBR), the Simplified version of Soil Conservation Service of the US Department of Agriculture method (USDA-SCS simplified), and the CROPWAT version of USDA-SCS method (USDA-SCS CROPWAT) were used. To compare the calculated SPEI based on OP (SPEIOP) and EP (SPEIEP) (based on different EP calculation methods), the correlation coefficients (CC) between SPEIOP and SPEIEP in four synoptic stations with at least 30 years of climatic data and annual yield loss (%) in winter wheat (Triticum sativum) (simulated using AquaCrop model) in the suitable reference periods for agricultural drought were used. Results showed, in Fasa, Drodzan, and Zarghan stations, the CC between SPEI based on EP using the USBR method (SPEIUSBR) and annual YL% had the highest values (in 42.11%, 68.42%, and 36.84% of Triticum sativum all reference periods, respectively). In Shiraz station, the CC between SPEI based on EP using the FAO method (SPEIFAO) and annual YL% had the highest values (in 47.37% of all reference periods). In all stations, the SPEIUSBR had the most reference periods with significant CC at 0.05 or 0.01 levels.

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Acknowledgments

Authors of this paper would like to thank the national meteorological organization of Iran (www.irimo.ir) and water meteorological organization of Fars province for providing the necessary meteorological information.

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  1. Department of Range and watershed management (Nature engineering), College of Agricultural Science, Fasa University, Fasa, Iran

    Abdol Rassoul Zarei

  2. Department of Water Engineering, College of Agriculture, Fasa University, Fasa, Iran

    Mohammad Mehdi Moghimi

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Correspondence to Abdol Rassoul Zarei.

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Zarei, A.R., Moghimi, M.M. Modified version for SPEI to evaluate and modeling the agricultural drought severity. Int J Biometeorol 63, 911–925 (2019). https://doi.org/10.1007/s00484-019-01704-2

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