Crop rotation modelling - a European model intercomparison

Chris Kollas (1, 2) , Kurt Christian Kersebaum (1) , Claas Nendel (1) , Kiril Manevski (3) , Christoph Müller (2) , Taru Palosuo (4) , Cecilia Armas-Herrera (5) , Nicolas N. Beaudoin (5) , Marco Bindi (6) , Monia Charfeddine (7) , Tobias Conradt (2) , Julie J. Constantin (8) , Josef Eitzinger (9) , Frank Ewert (10) , Roberto Ferrise (6) , Thomas Gaiser (10) , Inaki Garcia de Cortazar Atauri (11) , Luisa Giglio (7) , Petr Hlavinka (12, 13) , Holger Hoffmann (10) , Munir P. Hoffmann (14) , Marie Launey (11) , Remy Manderscheid (15) , Bruno B. Mary (5) , Wilfried Mirschel (16) , Marco Moriondo (17) , Jørgen E. Olesen (3) , Isik Ozturk (3) , Andreas Pacholski (18, 15) , Dominique Ripoche-Wachter (11) , Pier Paolo Roggero (19) , Svenja Roncossek (3) , Reimund P. Rotter (4) , Francoise Ruget (20) , Behzad Sharif (3) , Mirek Trnka (12, 13) , Domenico Ventrella (7) , Katharina Waha (2, 21) , Martin Wegehenkel (22) , Hans-Joachim Weigel (15) , Lianhai Wu (23)

1 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
2 PIK - Potsdam Institute for Climate Impact Research
3 Department of Agroecology
4 LUKE - Natural Resources Institute Finland
5 AgroImpact - Agroressources et Impacts environnementaux
6 Department of Agri-Food Production and Environmental Sciences
7 CREA - Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics
8 AGIR - AGroécologie, Innovations, teRritoires
9 BOKU - Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche]
10 INRES - Institut für Nutzpflanzenwissenschaften und Ressourcenschutz
11 AGROCLIM - Agroclim
12 CzechGlobe - Global Change Research Centre
13 Institute of Agrosystems and Bioclimatology
14 Crop Production Systems in the Tropics
15 Johann Heinrich von Thünen Institut
16 Institute of landscape systems analysis
17 CNR - National Research Council of Italy | Consiglio Nazionale delle Ricerche
18 Graduate School/Inkubator
19 UNISS - Università degli Studi di Sassari = University of Sassari [Sassari]
20 EMMAH - Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes
21 CSIRO - Commonwealth Scientific and Industrial Research Organisation [Canberra]
22 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung
23 Rothamsted Research

Diversification of crop rotations is considered an option to increase the resilience of European crop pro-duction under climate change. So far, however, many crop simulation studies have focused on predictingsingle crops in separate one-year simulations. Here, we compared the capability of fifteen crop growthsimulation models to predict yields in crop rotations at five sites across Europe under minimal calibration.Crop rotations encompassed 301 seasons of ten crop types common to European agriculture and a diverseset of treatments (irrigation, fertilisation, CO2concentration, soil types, tillage, residues, intermediate orcatch crops).We found that the continuous simulation of multi-year crop rotations yielded results of slightly higherquality compared to the simulation of single years and single crops. Intermediate crops (oilseed radishand grass vegetation) were simulated less accurately than main crops (cereals). The majority of modelsperformed better for the treatments of increased CO2and nitrogen fertilisation than for irrigation andsoil-related treatments. The yield simulation of the multi-model ensemble reduced the error comparedto single-model simulations. The low degree of superiority of continuous simulations over single year simulation was caused by (a)insufficiently parameterised crops, which affect the performance of the following crop, and (b) the lackof growth-limiting water and/or nitrogen in the crop rotations under investigation. In order to achieve asound representation of crop rotations, further research is required to synthesise existing knowledge ofthe physiology of intermediate crops and of carry-over effects from the preceding to the following crop,and to implement/improve the modelling of processes that condition these effects.

Mots clés: catch crop Intermediate; crop Treatment

Mots clés: model ensemble; crop simulation models; multi-year

Domaines: Autre [cs.OH]; Sciences agricoles

Chris Kollas, Kurt Christian Kersebaum, Claas Nendel, Kiril Manevski, Christoph Müller, et al.. Crop rotation modelling - a European model intercomparison. European Journal of Agronomy, 2015, 70, pp.98-111. ⟨10.1016/j.eja.2015.06.007⟩. ⟨hal-02638180⟩