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Theoretical and Applied Climatology

, Volume 67, Issue 1–2, pp 45–63 | Cite as

Vulnerability and adaptation assessments of agriculturalcrops under climate change in the Southeastern USA

  • V. A. Alexandrov
  • G. Hoogenboom

Summary

 It is expected that a change in climatic conditions due to global warming will directly impact agricultural production. Most climate change studies have been applied at very large scales, in which regions were represented by only one or two weather stations, which were mainly located at airports of major cities. The objective of this study was to determine the potential impact of climate change at a local level, taking into account weather data recorded at remote locations. Daily weather data for a 30-year period were obtained for more than 500 sites, representing the southeastern region of the USA. Climate change scenarios, using transient and equilibrium global circulation models (GCM), were defined, created and applied to the daily historical weather data. The modified temperature, precipitation and solar radiation databases corresponding to each of the climate change scenarios were used to run the CERES v.3.5 simulation model for maize and winter wheat and the CROPGRO v.3.5 model for soybean and peanut. The GCM scenarios projected a shorter duration of the crop-growing season. Under the current level of CO2, the GCM scenarios projected a decrease of crop yields in the 2020s. When the direct effects of CO2 were assumed in the study, the scenarios resulted in an increase in soybean and peanut yield. Under equilibrium \(\), the GCM climate change scenarios projected a decrease of maize and winter wheat yield. The indirect effects of climate change also tended to decrease soybean and peanut yield. However, when the direct effects of CO2 were included, most of the scenarios resulted in an increase in legume yields. Possible changes in sowing data, hybrids and cultivar selection, and fertilization were considered as adaptation options to mitigate the potential negative impact of potential warming.

Keywords

Winter Wheat Climate Change Scenario Weather Data Adaptation Option Sowing Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag/Wien 2000

Authors and Affiliations

  • V. A. Alexandrov
    • 1
  • G. Hoogenboom
    • 2
  1. 1. National Institute of Meteorology and Hydrology, Sofia, BulgariaBG
  2. 2. The University of Georgia, Griffin, Georgia, USAUS

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