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  Performance of process-based models for simulation of grain N in crop rotations across Europe

Yin, X., Kersebaum, K. C., Kollas, C., Manevski, K., Baby, S., Beaudoin, N., Öztürk, I., Gaiser, T., Wu, L., Hoffmann, M., Charfeddine, M., Conradt, T., Constantin, J., Ewert, F., Garcia de Cortazar-Atauri, I., Giglio, L., Hlvalinka, P., Hoffmann, H., Launay, M., Louarn, G., Manderscheid, R., Mary, B., Mirschel, W., Nendel, C., Pacholski, A., Palosuo, T., Ripoche-Wachter, D., Rötter, R. P., Ruget, F., Sharif, B., Trnka, M., Ventrella, D., Weigel, H.-J., Olesen, J. E. (2017): Performance of process-based models for simulation of grain N in crop rotations across Europe. - Agricultural Systems, 154, 63-77.
https://doi.org/10.1016/j.agsy.2017.03.005

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Yin, X.1, Autor
Kersebaum, K. C.1, Autor
Kollas, Chris2, Autor              
Manevski, K.1, Autor
Baby, S.1, Autor
Beaudoin, N.1, Autor
Öztürk, I.1, Autor
Gaiser, T.1, Autor
Wu, L.1, Autor
Hoffmann, M.1, Autor
Charfeddine, M.1, Autor
Conradt, Tobias2, Autor              
Constantin, J.1, Autor
Ewert, F.1, Autor
Garcia de Cortazar-Atauri, I.1, Autor
Giglio, L.1, Autor
Hlvalinka, P.1, Autor
Hoffmann, H.1, Autor
Launay, M.1, Autor
Louarn, G.1, Autor
Manderscheid, R.1, AutorMary, B.1, AutorMirschel, W.1, AutorNendel, C.1, AutorPacholski, A.1, AutorPalosuo, T.1, AutorRipoche-Wachter, D.1, AutorRötter, R. P.1, AutorRuget, F.1, AutorSharif, B.1, AutorTrnka, M.1, AutorVentrella, D.1, AutorWeigel, H.-J.1, AutorOlesen, J. E.1, Autor mehr..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, iii) under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. Generally, the results showed that the accuracy of the simulations in predicting grain N increased under detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordeum vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena sativa L.), winter rye (Secale cereale L.), pea (Pisum sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism.

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 Datum: 2017
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.agsy.2017.03.005
PIKDOMAIN: Climate Impacts & Vulnerabilities - Research Domain II
eDoc: 7587
Research topic keyword: Food & Agriculture
Model / method: SWIM
Regional keyword: Europe
Organisational keyword: RD2 - Climate Resilience
Working Group: Hydroclimatic Risks
 Art des Abschluß: -

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Titel: Agricultural Systems
Genre der Quelle: Zeitschrift, SCI, Scopus
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 154 Artikelnummer: - Start- / Endseite: 63 - 77 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/agricultural-systems