Testing CERES-wheat with free-air carbon dioxide enrichment (FACE) experiment data: CO2 and water interactions

Dynamic crop-growth models are used to project the effects of rising atmosp heric CO2 concentration and associated climate change on crop yields. Such model predictions are largely untested in the field, for lack of experiment al data. We tested the CERES-Wheat model, modified to include leaf-level ph otosynthesis response to elevated CO2, using field data from 2 yr of Free-A ir Carbon Dioxide Enrichment (FACE) experiments with spring wheat (Triticum aestivum L. cv. Yecora Rojo) in Mariclopa, AZ. Two irrigation treatments ( well-watered, WW; water-deficit stressed, WS) and two atmospheric CO2 conce ntrations (ambient, 350 mu mol mol(-1); elevated, 550 mu mol mol(-1)) were simulated. The model was evaluated using measurements of crop phenology, ab oveground dry matter (DM) production, grain yield, and evapotranspiration ( ET). Model calculations of crop phenology were within 2 to 3 d of observed values under WW, ambient CO2 conditions in both years. The model did not si mulate the accelerated crop phenology (5-8 d at physiological maturity) obs erved in the WW and elevated CO2 treatments, indicating the need to include effects of increased stomatal resistance on canopy temperature. Simulation s of DM and grain yield were within 10% of measured values, except for a te ndency to overcalculate DM response to CO2 by 10 to 15% in Year 1 for WS tr eatments. The model undercalculated cumulative ET under WW conditions by 15 %; model sensitivity analyses suggest that simulation of potential evapotra nspiration (PET) was too low for this arid site. The model reproduced measu red dynamics of CO2-water interactions. Simulated reductions in water loss due to elevated CO2 were about 4%, in agreement with measurements. The mode l simulated larger increases in DM production and yield due to elevated CO2 under WS than under WW conditions. In Year 1, simulated crop response to C O2 was 2% larger (measured: 3%) under WS than under WW conditions; in Year 2, it was 11% larger (measured: 9%). The ability to simulate CO2-water inte ractions, though it needs to be further evaluated with additional experimen tal datasets, is an important attribute of models used to project crop yiel ds under elevated CO2 and climate change.