1. How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?
- Author
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Durand, Jean-Louis, Delusca, Kenel, Boote, Ken, Lizaso, Jon, Manderscheid, Remy, Weigel, Hans Johachim, Ruane, Alexander Clark, Rosenzweig, Cynthia E, Jones, Jim, Ahuja, Laj, Anapalli, Saseendran, Basso, Bruno, Baron, Christian, Bertuzzi, Patrick, Biernath, Christian, Deryng, Delphine, Ewert, Frank, Gaiser, Thomas, Gayler, Sebastian, Heilein, Florian, Kersebaum, Kurt Christian, Kim, Soo-Hyung, Muller, Christoph, Nendel, Claas, Olioso, Albert, Priesack, Eckart, Villegas, Julian Ramirez, Ripoche, Dominique, Rotter, Reimund P, Seidel, Sabine I, Srivastava, Amit, Tao, Fulu, Timlin, Dennis, Twine, Tracy, Wang, Enli, Webber, Heidi, and Zhao, Zhigan
- Subjects
Earth Resources And Remote Sensing ,Statistics And Probability ,Meteorology And Climatology - Abstract
This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.
- Published
- 2017
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