A real-time gridded crop model for assessing spatial drought stress on crops in the Southeastern United States

Richard T. Mcnider, John R. Christy, Don Moss, Kevin Doty, Cameron Handyside, Ashutosh Limaye, Axel Garcia y Garcia, Gerrit Hoogenboom

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


The severity of drought has many implications for society. Its impacts on rain-fed agriculture are especially direct, however. The southeastern United States, with substantial rain-fed agriculture and large variability in growing-season precipitation, is especially vulnerable to drought. As commodity markets, drought assistance programs, and crop insurance have matured, more advanced information is needed on the evolution and impacts of drought. So far many new drought products and indices have been developed. These products generally do not include spatial details needed in the Southeast or do not include the physiological state of the crop, however. Here, a new type of drought measure is described that incorporates high-resolution physical inputs into a crop model (corn) that evolves based on the physical-biophysical conditions. The inputs include relatively high resolution (as compared with standard surface or NOAA Cooperative Observer Program data) (5 km) radar-derived precipitation, satellite-derived insolation, and temperature analyses. The system (referred to as CropRT for gridded crop real time) is run in real time under script control to provide daily maps of crop evolution and stress. Examples of the results fromthe systemare provided for the 2008-10 growing seasons. Plots of daily crop water stress show small subcounty-scale variations in stress and the rapid change in stress over time. Depictions of final crop yield in comparison with seasonal average stress are provided.

Original languageEnglish (US)
Pages (from-to)1459-1475
Number of pages17
JournalJournal of Applied Meteorology and Climatology
Issue number7
StatePublished - Jul 2011


  • Crop growth
  • Drought
  • Stress


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