Predictive value of Keetch-Byram Drought Index for cereal yields in a semi-arid environment
Meteorological drought indices associated with soil moisture status have potential for varying applications including predictive power for crop yields estimation. The Keetch-Byram Drought Index (KBDI) was initially developed to estimate forest flammability, based on quantification of the moisture deficiency in upper soil layer as a function of daily precipitation and maximum air temperature. In this study, we characterized the utility of KBDI to accurately trace and monitor vegetation change and crop yield fluctuation in a semi-arid environment. It is tried to find any temporal association for both the 16-day MODIS-derived NDVI and KBDI from 2002 to 2012 and the correlation between KBDI and wheat and barley yield from 1984 to 2010. Correlation between KBDI and NDVI showed a general seasonal pattern with strongest correlation in mid-growing season, but this varied across study locations. Warmer locations with very sparse vegetation showed weaker association between KBDI and NDVI. Although a robust correlation between KBDI and winter cereal crop yield was not achieved based on winter (wet and cold season) data, spring cereal crop yield was correlated with KBDI.
We would like to thank K. Grace Crummer (Institute for Sustainable Food Systems, University of Florida) for editing the manuscript to improve the language.
- Ciais P, Reichstein M, Viovy N, Granier A, Ogee J, Allard V, Aubinet M, Buchmann N, Bernhofer C, Carrara A, Chevallier F, De Noblet N, Friend AD, Friedlingstein P, Grunwald T, Heinesch B, Keronen P, Knoh A, Krinner G, Loustau D, Manca G, Matteucci G, Miglietta F, Ourciva JM, Papale D, Pilegaard K, Rambal S, Seufert G, Soussana JF, Sanz MJ, Schulze ED, Vesala T, Valentini R (2005) Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437(7058):529–533. https://doi.org/10.1038/nature03972 CrossRefGoogle Scholar
- Gausman HW (1974) Leaf reflectance of near-infrared. Photogramm Eng 10:183–191Google Scholar
- Keetch J J, Byram O M (1968) A drought index for forest fire control. USDA For Serv Southeastern For and Range Exp Stn Res Pap SE-38Google Scholar
- Kogan FN (1995) Droughts of the late 1980s in the United States as derived from NOAA polar orbiting satellite data. Bull Am Meteorol Soc 76(5):655–668. https://doi.org/10.1175/1520-0477(1995)076<0655:DOTLIT>2.0.CO;2 CrossRefGoogle Scholar
- Miller TD (1999) Growth stages of wheat: identification and understanding improve crop management. SCS-1999-16. Texas Agricultural Extension Service, the Texas A&M University System, College StationGoogle Scholar
- Nazemosadat MJ (2000) Winter drought in Iran: association with ENSO. Drought Netw News 13:1Google Scholar
- Rouse JW, Hass RH, Schell JA (1974) Monitoring vegetation systems in the Great Plains with ERTS. In: The third earth resources technology Satellite-1 symposium, Greenbelt, MD, 309–317Google Scholar
- Trnka M, Dubrovsky M, Zalud Z (2004) Climate change impacts and adaptation strategies in spring barley production in the Czech Republic. Clim Chang 64(1/2):227–255. https://doi.org/10.1023/B:CLIM.0000024675.39030.96 CrossRefGoogle Scholar