Prediction of Evapotranspiration and Yields of Maize: An Inter-comparison among 31 Maize Models

Bruce Kimball (1) , K. Boote (2) , J. Hatfield (1) , L. Ahuja (3) , C. Stöckle (4) , S. Archontoulis (5) , C. Baron (6) , Bruno Basso (7) , Patrick Bertuzzi (8) , M. Chen (9) , Julie Constantin (10) , D. Derying (11) , B. Dumont (12) , Jean-Louis Durand (13) , F. Ewert (14, 15) , T. Gaiser (15) , S. Gayler (16) , T. Griffis (9) , M. Hoffmann (17) , Q. Jiang (18) , Soo-Hyung Kim (19) , J. Lizaso (20) , Sophie Moulin (21) , C. Nendel (14) , P. Parker (14) , T. Palosuo (22) , E. Priesack (23) , Zhiming Qi Z. (18) , A. Srivastava (15) , T. Stella (14) , F. Tao (22, 24) , K. Thorp (1) , D. Timlin (25) , T. Twine (9) , Heidi Webber (15) , Magali M. Willaume (10) , K. Williams (26)

1 USDA-ARS : Agricultural Research Service
2 Agronomy Department
3 Agricultural Systems Research Unit, USDA, Agricultural Research Service
4 Biological Systems Engineering
5 Department of Agronomy
6 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale
7 Michigan State University [East Lansing]
8 AGROCLIM - Agroclim
9 Department of Soil, Water and Climate
10 AGIR - AGroécologie, Innovations, teRritoires
11 Computation Institute
12 ULg-GxABT, Gembloux Agro-Bio Tech Faculty, Dpt. Agronomy, Bio-Engineering and Chemistry, Crop Science Unit
13 P3F - Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères
14 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
15 Institute of Crop Science and Resource Conservation [Bonn]
16 Institute of Soil Science and Land Evaluation, Biogeophysics
17 Crop Production Systems in the Tropics
18 Department of Bioresource Engineering, Macdonald Campus
19 Center for Urban Horticulture [Seattle]
20 Dept. Producción Agraria-CEIGRAM
21 EMMAH - Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes
22 LUKE - Natural Resources Institute Finland
23 BIOP - Institute of Biochemical Plant Pathology
24 IGSNRR - Institute of Geographic Sciences and Natural Resources Research
25 Crop Systems and Global Change Research Unit
26 Climate Adaptation Scientist Meteorological Office

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 31 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 in later stages when the modelers were provided additional leaf area, growth, and the actual ET observations that allowed them to “calibrate” some of the parameters in their models to account for varietal characteristics, etc. Bruce

Mots clés: Crop model; Maize

Mots clés: Evapotranspiration

Domaines: Sciences du Vivant [q-bio]; Sciences de l'environnement; Sciences de l'Homme et Société; Biologie végétale

Bruce Kimball, K. Boote, J. Hatfield, L. Ahuja, C. Stöckle, et al.. Prediction of Evapotranspiration and Yields of Maize: An Inter-comparison among 31 Maize Models. 7. Global Workshop AgMIP, Agricultural Model Intercomparison and Improvement Project (AgMIP). USA., Apr 2018, San Jose, Costa Rica. pp.1. ⟨hal-02788024⟩