Comparing the performance of 11 crop simulation models in predicting yield response to nitrogen fertilization
2016
Salo, Tapio J. | Palosuo, Taru | Kersebaum, Kurt Christian | Nendel, Claas | Angulo, Carlos | Ewert, Frank | Bindi, Marco | Calanca, Pierluigi | Klein, Tommy | Moriondo, Marco | Ferrise, Roberto | Olesen, Jørgen Eivind | Patil, Rasmi H. | Ruget, Francoise | Takac, Jozef | Hlavinka, Petr | Trnka, Miroslav | Röttter, Reimund P. | Natural Resources Institute Finland (LUKE) | Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF) | Institute of Crop Science and Resource Conservation [Bonn] (INRES) ; Rheinische Friedrich-Wilhelms-Universität Bonn | Department of Agrifood Production and Environmental Sciences (DISPAA) ; Università degli Studi di Firenze = University of Florence (UniFI) | Agroscope | Istituto di Biometeorologia [Firenze] (IBIMET) ; National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR) | Department of agroecology ; Aarhus University [Aarhus] | Department of Agroecology ; Aarhus University [Aarhus] | Department of Agronomy ; University of Agricultural Sciences | Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH) ; Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | National Agricultural and Food Centre ; Soil Science and Conservation Research Institute | Global Change Research Centre (CzechGlobe) | Institute of Agrosystems and Bioclimatology ; Mendel University in Brno (MENDELU) | The authors wish to acknowledge the financial assistance provided under the umbrella of COST action 734 'Impacts of Climate Change and Variability on European Agriculture (CLIVAGRI)' and the work of individual researchers was funded by various bodies: T. Palosuo, T. Salo and R. Rotter, the strategic project MODAGS funded by MTT Agrifood Research Finland, and projects FACCE MACSUR and NORFASYS (decision nos. 268277 and 292944) funded by the Ministry of Agriculture and Forestry and the Academy of Finland, respectively; K. C. Kersebaum performed parts of the current study under the umbrella of FACCE MACSUR funded by the German Federal Office for Agriculture and Food and COST ES1106; C. Nendel was supported by ZALF in-house funds; J.E. Olesen and R.H. Patil, CRES funded by Danish Strategic Research Council; P. Hlavinka was supported by the Ministry of Education, Youth and Sports of CR within the National Sustainability Program I (NPU I), grant number LO1415; M. Trnka, Crop modelling as a tool for increasing the production potential and food security of the Czech Republic funded by National Agency for Agricultural Research (QJ1310123) and project LD 13030 - Water resources in the Czech Agriculture under the Climate Change conditions - CZECH-AGRIWAT
Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area index (LAI) and yield observations. The models were then tested against new data for 2009 and their performance was assessed and compared with both the two calibration years and the test year. For the calibration period, root mean square error between measurements and simulated grain dry matter yields ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi-model mean could not correct systematic errors in model simulations. Variation in soil N mineralization and LAI development due to differences in weather not captured by the models most likely was the main reason for their unsatisfactory performance. This suggests the need for model improvement in soil N mineralization as a function of soil temperature and moisture. Furthermore, specific weather event impacts such as low temperatures after emergence in 2009, tending to enhance tillering, and a high precipitation event just before harvest in 2008, causing possible yield penalties, were not captured by any of the models compared in the current study.
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