Evaluation of Corn Evapotranspiration Predictions of STICS Crop Model using Eddy Covariance Fluxes Measured in Corn Fields of Eastern Canada

Corn is the third largest grain crop in Canada (after wheat and canola), and the most important crop in Eastern Canada (AAFC, 2010). In this region, extending from Southwestern Quebec to Southern Ontario, annual precipitations were almost equally distributed (comprised between 800 and 1000 mm), and were sufficient to allow rainfed cropping. However, water deficits may occur some years and affect and biomass and final yield, particularly when it happens during the grain filling period. The influence of climatic variations on crop production can be detected, in theory, by daily changes in the accumulation of biomass and evapotranspiration during the growing season. To assess the temporal resolution of the response of STICS crop model (Brisson et al., 1998) predictions to weather variations, daily and ten-day data sets of predicted and measured evapotranspiration were compared. Both methods of ET calculation available in STICS were evaluated (the crop coefficient approach and the resistive approach). The soil parameters were estimated from analysis of soil texture and moisture profiles made by TDR (time domain reflectometry). Daily and ten-day corn ET were calculated from flux measured in the Ottawa area using the eddy covariance technique during several growing seasons (1996, 1998, 2000, 2002 and 2006) following the approach presented in Pattey et al. (2001). A water balance has also been established to estimate evapotranspiration from TDR measurements of volumetric moisture in the soil profile. Two years exhibited significant water stress period, one year had a deficit of CHU and the two others did not have any abiotic stress. The years 1996, 2000, and 2006 were wet, but while 2000 was cool, 1996 and 2006 had cumulated thermal units close to the average. We analysed separately the years with water stress (1998, and 2001) and the years without water stress (1996, 2000, and 2006). The daily ET dynamic predictions of STICS were very good for years without water stress (1996, 2000 and 2006). However, ET predictions of STICS were overestimated by 12 to 34% during dry years, both at decadal and daily time step. The resistive approach provided better results than the crop coefficient approach that strongly overestimated predictions of ET. The soil water balance has been established for two dry years and two wet years. It also overestimated the ET measured by the eddy covariance technique. Partitioning between soil evaporation and plant transpiration was also analysed. ET measured on bare soil, before crop seeding and after harvest, was compared with STICS model predictions. The recommended value of the Q0 parameter of the STICS crop model, which represents the maximum potential soil evaporation, was reduced from 10 mm to 2 mm in order to give good prediction of soil evaporation after rainy conditions. Finally the predicted and measured water use efficiency was analyzed by calculating two indices WUE_ET (= biomass / evapotranspiration) and WUE_T (= biomass / transpiration). These indices were calculated at several time steps (daily, ten-day, average growing season), in order to analyze the response of the model to water stress and to calibrate the parameters which control the crop water requirement in the STICS crop model using the crop coefficient and resistive approach.

References Agriculture and Agri-Food Canada (AAFC). 2010. Canada: grains and oilseeds outlook. Publ. 1496-967X. AAFC, Ottawa, ON. Brisson N., Mary B., Ripoche D., Jeuffroy M.H., Ruget F., Nicoullaud B., Gate P., Devienne-Barret F., Antonioletti R., Durr C., Richard G., Beaudoin N., Recous S., Tayot X., Plenet D., Cellier P., Machet J.M.,. Meynard J.M, Delécolle R. (1998) STICS: A generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agronomie 18, (5-6), 311-346. Pattey, E., Strachan, I.B., Boisvert, J.B., Desjardins, R.L. and McLaughlin, N.B., 2001. Detecting effects of nitrogen rate and weather on corn growth using micrometeorological and hyperspectral reflectance measurements. Agric. For. Meteorol., 108: 85-99.