Journal of Arid Land

, Volume 9, Issue 6, pp 797–809 | Cite as

Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data

  • Nasrin Salehnia
  • Amin AlizadehEmail author
  • Hossein Sanaeinejad
  • Mohammad Bannayan
  • Azar Zarrin
  • Gerrit Hoogenboom


Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can represent all facets of meteorological drought, we took a multi-index approach for drought monitoring in this study. We assessed the ability of eight precipitation-based drought indices (SPI (Standardized Precipitation Index), PNI (Percent of Normal Index), DI (Deciles index), EDI (Effective drought index), CZI (China-Z index), MCZI (Modified CZI), RAI (Rainfall Anomaly Index), and ZSI (Z-score Index)) calculated from the station-observed precipitation data and the AgMERRA gridded precipitation data to assess historical drought events during the period 1987–2010 for the Kashafrood Basin of Iran. We also presented the Degree of Dryness Index (DDI) for comparing the intensities of different drought categories in each year of the study period (1987–2010). In general, the correlations among drought indices calculated from the AgMERRA precipitation data were higher than those derived from the station-observed precipitation data. All indices indicated the most severe droughts for the study period occurred in 2001 and 2008. Regardless of data input source, SPI, PNI, and DI were highly inter-correlated (R2=0.99). Furthermore, the higher correlations (R2=0.99) were also found between CZI and MCZI, and between ZSI and RAI. All indices were able to track drought intensity, but EDI and RAI showed higher DDI values compared with the other indices. Based on the strong correlation among drought indices derived from the AgMERRA precipitation data and from the station-observed precipitation data, we suggest that the AgMERRA precipitation data can be accepted to fill the gaps existed in the station-observed precipitation data in future studies in Iran. In addition, if tested by station-observed precipitation data, the AgMERRA precipitation data may be used for the data-lacking areas.


severe drought degree of dryness MDM (Meteorological Drought Monitoring) software precipitation intensity Middle East 


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We would like to thank Dr. Carol WILKERSON (Independent Consultant, Gainesville, Florida, USA) and K. Grace CRUMMER (Institute for Sustainable Food Systems, University of Florida, USA) for editing and improving the language of the manuscript.


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Copyright information

© Xinjiang Institute of Ecology and Geography, the Chinese Academy of Sciences and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Nasrin Salehnia
    • 1
  • Amin Alizadeh
    • 1
    Email author
  • Hossein Sanaeinejad
    • 1
  • Mohammad Bannayan
    • 1
  • Azar Zarrin
    • 2
  • Gerrit Hoogenboom
    • 3
  1. 1.Faculty of AgricultureFerdowsi University of MashhadMashhadIran
  2. 2.Department of GeographyFerdowsi University of MashhadMashhadIran
  3. 3.Institute for Sustainable Food SystemUniversity of FloridaGainesvilleUSA

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