Simulation of maize evapotranspiration: An inter-comparison among 29 maize models

Kimball Bruce A., Boote Kenneth J., Hatfield Jerry L., Ahuja Lajpat R., Stöckle Claudio, Archontoulis Sotirios, Baron Christian, Basso Bruno, Bertuzzi Patrick, Constantin Julie, Deryng Delphine, Dumont Benjamin, Durand Jean-Louis, Ewert Franck, Gaiser Thomas, Gayler Sebastian, Hoffmann Munir P., Jiang Qianjing, Kim Soo-Hyung, Lizaso Jon, Moulin Sophie, Nendel Claas, Parker Philip, Palosuo Taru, Priesack Eckart, Qi Zhiming, Srivastava Amit Kumar, Stella Tommaso, Tao Fulu, Thorp Kelly R., Timlin Dennis, Twine Tracy E., Webber Heidi, Willaume Magali, Williams Karina E.. 2019. Simulation of maize evapotranspiration: An inter-comparison among 29 maize models. Agricultural and Forest Meteorology, 271 : 264-284.

Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/JSAHFB

Quartile : Outlier, Sujet : FORESTRY / Quartile : Outlier, Sujet : AGRONOMY / Quartile : Q1, Sujet : METEOROLOGY & ATMOSPHERIC SCIENCES

Résumé : Crop yield can be affected by crop water use and vice versa, so when trying to simulate one or the other, it can be important that both are simulated well. In a prior inter-comparison among maize growth models, evapotranspiration (ET) predictions varied widely, but no observations of actual ET were available for comparison. Therefore, this follow-up study was initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Observations of daily ET using the eddy covariance technique from an 8-year-long (2006–2013) experiment conducted at Ames, IA were used as the standard for comparison among models. Simulation results from 29 models are reported herein. In the first “blind” phase for which only weather, soils, phenology, and management information were provided to the modelers, estimates of seasonal ET varied from about 200 to about 700 mm. Subsequent three phases provided (1) leaf area indices for all years, (2) all daily ET and agronomic data for a typical year (2011), and (3) all data for all years, thus allowing the modelers to progressively calibrate their models as more information was provided, but the range among ET estimates still varied by a factor of two or more. Much of the variability among the models was due to differing estimates of potential evapotranspiration, which suggests an avenue for substantial model improvement. Nevertheless, the ensemble median values were generally close to the observations, and the medians were best (had the lowest mean squared deviations from observations, MSD) for several ET categories for inter-comparison, but not all. Further, the medians were best when considering both ET and agronomic parameters together. The best six models with the lowest MSDs were identified for several ET and agronomic categories, and they proved to vary widely in complexity in spite of having similar prediction accuracies. At the same time, other models with apparently similar approaches were not as accurate. The models that are widely used tended to perform better, leading us speculate that a larger number of users testing these models over a wider range of conditions likely has led to improvement. User experience and skill at calibration and dealing with missing input data likely were also a factor in determining the accuracy of model predictions. In several cases different versions of a model within the same family of models were run, and these within-family inter-comparisons identified particular approaches that were better while other factors were held constant. Thus, improvement is needed in many of the models with regard to their ability to simulate ET over a wide range of conditions, and several aspects for progress have been identified, especially in their simulation of potential ET.

Mots-clés Agrovoc : maïs, Zea mays, évapotranspiration, modèle mathématique, besoin en eau

Mots-clés libres : Maize, Simulation, Evapotranspiration, Water use, Model, Yield

Classification Agris : F60 - Physiologie et biochimie végétale
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 2 (2019-) - Transitions agroécologiques

Auteurs et affiliations

• Kimball Bruce A., USDA (USA) - auteur correspondant
• Boote Kenneth J., University of Florida (USA)
• Hatfield Jerry L., USDA (USA)
• Ahuja Lajpat R., USDA (USA)
• Stöckle Claudio, Washington State University (USA)
• Archontoulis Sotirios, Iowa State University (USA)
• Baron Christian, CIRAD-ES-UMR TETIS (FRA)
• Basso Bruno, MSU (USA)
• Bertuzzi Patrick, INRA (FRA)
• Constantin Julie, INRA (FRA)
• Deryng Delphine, Leibniz Centre for Agricultural Landscape Research (DEU)
• Dumont Benjamin, Université de Liège (BEL)
• Durand Jean-Louis, INRA (FRA)
• Ewert Franck, Universität Bonn (DEU)
• Gaiser Thomas, Universität Bonn (DEU)
• Gayler Sebastian, Universität Hohenheim (DEU)
• Hoffmann Munir P., Georg-August University of Göttingen (DEU)
• Jiang Qianjing, McGill University (CAN)
• Kim Soo-Hyung, University of Washington (USA)
• Lizaso Jon, UPM (ESP)
• Moulin Sophie, INRA (FRA)
• Nendel Claas, Leibniz Centre for Agricultural Landscape Research (DEU)
• Parker Philip, Spatial Business Integration (DEU)
• Palosuo Taru, Natural Resources Institute Finland (FIN)
• Priesack Eckart, Institute of Biochemical Plant Pathology (DEU)
• Qi Zhiming, McGill University (CAN)
• Srivastava Amit Kumar, Universität Bonn (DEU)
• Stella Tommaso, Leibniz Centre for Agricultural Landscape Research (DEU)
• Tao Fulu, CAS (CHN)
• Thorp Kelly R., USDA (USA)
• Timlin Dennis, USDA (USA)
• Twine Tracy E., University of Minnesota (USA)
• Webber Heidi, Universität Bonn (DEU)
• Willaume Magali, Université de Toulouse (FRA)
• Williams Karina E., Hadley Centre (GBR)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/592866/)

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