Incorporation of Wheat Canopy Temperatures into Agroecosystem Models by Using a Meta-model

Abstract

The canopy temperature is an important variable for predicting the impact of heat stress on grain yield. However, established agroecosystem models often use strongly simplified approaches, e.g., based on the air temperature, to estimate the response of canopy/canopy-within temperature to ambient conditions. Consequently, large model uncertainties are caused. Since phenomena affecting crop growth, such as heat stress, can often only be considered by resolving the diurnal cycle, methods are needed to gain & integrate these information into existing plant growth models using daily time steps.In our study, we aim at presenting an approach to include the impact of the diurnal variability of canopy temperatures in crop growth models, if these data are not available. A model simulating hourly canopy temperatures is validated using IR radiometer observations of winter wheat plants obtained during a field trial for three different irrigation treatments during two growing seasons at the Hohenschulen experimental farm of the University of Kiel. More specifically we aim at (I) identifying parameters from the diurnal cycles that are suitable to characterize and aggregate information on the canopy temperature response in models using a daily time step, II) using the model output to estimate the statistical relations between daily meteorological data, plant characteristics and the identified parameters and, based on these relations, (III) deriving a meta-model to simulate these parameters on the basis of existing meteorological data. We suggest that incorporating the resulting meta-model in agroecosystem models will lead to more realistic scenario analysis by improved predictions of the impact of heat and drought stress on crop yield.