Simulating canopy temperature for modelling heat stress in cereals. (March 2016)

• Record Type: Journal Article
• Authors: Webber, H.; Ewert, F.; Kimball, B.A.; Siebert, S.; White, J.W.; Wall, G.W.; Ottman, M.J.; Trawally, D.N.A.; Gaiser, T.
• Is Part Of: Environmental modelling & software. Volume 77(2016:Mar.)
• Page Start: 143
• Page End: 155
• Publication Date: 2016-03
• Subjects: Canopy temperature -- Heat stress -- Cereals -- Crop models; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.12.003
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Crop models must be improved to account for the effects of heat stress events on crop yields. To date, most approaches in crop models use air temperature to define heat stress intensity as the cumulative sum of thermal times (TT) above a high temperature threshold during a sensitive period for yield formation. However, observational evidence indicates that crop canopy temperature better explains yield reductions associated with high temperature events than air temperature does. This study presents a canopy level energy balance using Monin–Obukhov Similarity Theory (MOST) with simplifications about the canopy resistance that render it suitable for application in crop models and other models of the plant environment. The model is evaluated for a uniform irrigated wheat canopy in Arizona and rainfed maize in Burkina Faso. No single variable regression relationships for key explanatory variables were found that were consistent across sowing dates to explain the deviation of canopy temperature from air temperature. Finally, thermal times determined with simulated canopy temperatures were able to reproduce thermal times calculated with observed canopy temperature, whereas those determined with air temperatures were not. Highlights: Crop canopy temperature is needed to explain yield losses due to high temperatures. A canopy level energy balance using Monin–Obukhov Similarity Theory (MOST) is presented. Simplifications about the canopy resistance render it suitable for application in crop models. The model is evaluated for a irrigated wheat canopy in Arizona and rainfed maize in Burkina Faso.