4.7 Article

Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions

期刊

FIELD CROPS RESEARCH
卷 216, 期 -, 页码 75-88

出版社

ELSEVIER
DOI: 10.1016/j.fcr.2017.11.005

关键词

Heat stress; Crop model improvement; Heat and drought interactions; Climate change impact assessments; Canopy temperature; Wheat

类别

资金

  1. AgMIP
  2. Federal Ministry of Education and Research (BMBF) through WASCAL (West African Science Service Center on Climate Change and Adapted Land Use)
  3. German Science Foundation [EW 119/5-1, KA 3046/8-1]
  4. FACCE JPI MACSUR project through the German Federal Ministry of Education and Research [2812ERA115]
  5. International Food Policy Research Institute (IFPRI) through the Global Futures and Strategic Foresight project
  6. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS)
  7. CGIAR Research Program on Wheat
  8. German Federal Ministry of Economic Cooperation and Development (Project: PART)
  9. FACCE JPI MACSUR project through the meta program Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA) [031A103B]
  10. Biotechnological and Biological Sciences Research Council of the UK
  11. FACCE MACSUR project by Innovation Fund Denmark
  12. JPI FACCE MACSUR2 through the German Ministry of Education and Research [03180039C]
  13. JPI FACCE MACSUR2 through the Italian Ministry for Agricultural, Food and Forestry Policies
  14. BBSRC [BBS/E/C/000I0220, BBS/E/C/00005202] Funding Source: UKRI
  15. Biotechnology and Biological Sciences Research Council [BBS/E/C/00005202, BBS/E/C/000I0220] Funding Source: researchfish

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Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating Tc simulations from nine crop models at six locations across environmental and production conditions. Each crop model implemented one of an empirical (EMP), an energy balance assuming neutral stability (EBN) or an energy balance correcting for atmospheric stability conditions (EBSC) approach to simulate Tc. Model performance in predicting Tc was evaluated for two experiments in continental North America with various water, nitrogen and CO2 treatments. An empirical model fit to one dataset had the best performance, followed by the EBSC models. Stability conditions explained much of the differences between modeling approaches. More accurate simulation of heat stress will likely require use of energy balance approaches that consider atmospheric stability conditions.

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