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Hoffmann, H.* ; Zhao, G.* ; Asseng, S.* ; Bindi, M.* ; Biernath, C.J. ; Constantin, J.* ; Coucheney, E.* ; Dechow, R.* ; Doro, L.* ; Eckersten, H.* ; Gaiser, T.* ; Grosz, B.* ; Heinlein, F. ; Kassie, B.T.* ; Kersebaum, K.C.* ; Klein, C. ; Kuhnert, M.* ; Lewan, E.* ; Moriondo, M.* ; Nendel, C.* ; Priesack, E. ; Raynal, H.* ; Roggero, P.P.* ; Rötter, R.P.* ; Siebert, S.* ; Specka, X.* ; Tao, F.* ; Teixeira, E.* ; Trombi, G.* ; Wallach, D.* ; Weihermüller, L.* ; Yeluripati, J.* ; Ewert, F.*

Impact of spatial soil and climate input data aggregation on regional yield simulations.

PLoS ONE 11:e0151782 (2016)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Systems Simulation; Nitrogen Dynamics; Winter-wheat; Crop Models; Data Resolution; Scale; Water; Variability; Calibration; Weather
Sprache englisch
Veröffentlichungsjahr 2016
HGF-Berichtsjahr 2016
ISSN (print) / ISBN 1932-6203
Zeitschrift PLoS ONE
Quellenangaben Band: 11, Heft: 4, Seiten: , Artikelnummer: e0151782 Supplement: ,
Verlag Public Library of Science (PLoS)
Verlagsort Lawrence, Kan.
Begutachtungsstatus Peer reviewed
Institut(e) Research Unit Environmental Simulation (EUS)
POF Topic(s) 30202 - Environmental Health
Forschungsfeld(er) Environmental Sciences
PSP-Element(e) G-504912-001
PubMed ID 27055028
DOI 10.1371/journal.pone.0151782
WOS ID WOS:000373608000007
Scopus ID 84963759428
Erfassungsdatum 2016-04-14
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