Prediction of Evapotranspiration and Yields of Maize: An Inter-comparison among 29 Maize Models

Autor: Kimball, Bruce A., Boote, Kenneth J., Hatfield, Jerry L., Ahuja, Laj R., Stöckle, Claudio O., Archontoulis, Sotiris V., Christian Baron, Bruno Basso, Patrick Bertuzzi, Julie Constantin, Delphine Deryng, Benjamin Dumont, Franck Ewert, Thomas Gaiser, Griffis, Timothy J., Hoffmann, Munir P., Qianjing Jiang, Soo-Hyung Kim, Jon Lizaso, Sophie Moulin, Philip Parker, Taru Palusuo, Zhiming Qi Z., Amit Srivastava, Tao, F., Thorp, K., Dennis Timlin, Heidi Webber, Magali Willaume, Williams, K., Ming Chen, Jean-Louis Durand, Sebastian Gayler, Eckart Priesack, Tracy Twine
Přispěvatelé: USDA-ARS : Agricultural Research Service, Agronomy Department, University of Florida [Gainesville] (UF), Agricultural Systems Research Unit, USDA, Biological Systems Engineering, University of Wisconsin-Madison, Department of Agronomy, Purdue University [West Lafayette], Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS), Department of Geological Sciences and W. K. Kellogg Biological Station, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Agroclim (AGROCLIM), Institut National de la Recherche Agronomique (INRA), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Computation Institute, Loyola University of Chicago, Dpt. Agronomy, Bio- Engineering and Chemistry, Crop Science Unit, Université de Liège, Gembloux Agro-Bio Tech [Gembloux], Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF), Leibniz Association, Institute of Crop Science and Resource Conservation [Bonn] (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Department of Soil, Water, and Climate, University of Minnesota System, Crop Production Systems in the Tropics, Georg-August-University [Göttingen], Department of Bioresource Engineering [Montréal] (BIOENG), McGill University = Université McGill [Montréal, Canada], Center for Urban Horticulture, University of Washington, Dept. Producción Agraria-CEIGRAM, Universidad Politécnica de Madrid (UPM), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Natural resources institute Finland, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences [Beijing] (CAS), Crop Systems and Global Change Research Unit, Climate Adaptation Scientist Meteorological Office, Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institute of Soil Science and Land Evaluation, Biogeophysics, University of Hohenheim, Institute of Biochemical Plant Pathology, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Department of Soil, Water and Climate, University of Florida [Gainesville], Agricultural Research Service, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), UE Agroclim (UE AGROCLIM), UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Institute of Crop Science and Resource Conservation, University of Bonn-Division of Plant Nutrition, Georg-August-Universität Göttingen, McGill University, Natural Resources Institute Finland, United States Department of Agriculture - Agricultural Research Service
Jazyk: francouzština
Rok vydání: 2016
Předmět:
Zdroj: ASA, CSSA and SSSA International Annual Meetings (2016)
ASA, CSSA and SSSA International Annual Meetings (2016), Nov 2016, Phoenix, États-Unis. 3p
2016; ASA, CSSA and SSSA International Annual Meetings (2016), Phoenix, USA, 2016-11-06-2016-11-09
ASA, CSSA and SSSA International Annual Meetings (2016), Nov 2016, Phoenix États-Unis. 3p
HAL
Popis: An important aspect that determines the ability of crop growth models to predict growth and yield is their ability to predict the rate of water consumption or evapotranspiration (ET) of the crop, especially for rain-fed crops. If, for example, the predicted ET rate is too high, the simulated crop may exhaust its soil water supply before the next rain event, thereby causing growth and yield predictions that are too low. In a prior inter-comparison among maize growth models, ET predictions varied widely, but no observations of actual ET were available for comparison. Therefore, another study has been initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). This time observations of ET using the eddy covariance technique from an 8-year-long experiment conducted at Ames, IA are being used as the standard. Simulation results from 29 models have been completed. In the first “blind” phase for which only weather, soils, and management information were furnished to the modelers, estimates of seasonal ET varied from about 200 to about 700 mm. A detailed statistical analysis of the daily ET data from 2011, a “typical” rainfall year, showed that, as expected, the median of all the models was more accurate across several criteria (correlation, root mean square error, average difference, regression slope) than any particular model. However, some individual models were better than the median for a particular criteria. Predictions improved somewhat in later stages when the modelers were provided additional leaf area and growth information that allowed them to “calibrate” some of the parameters in their models to account for varietal characteristics, etc.
Databáze: OpenAIRE
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