Records |
Author |
Sándor, R.; Ehrhardt, F.; Basso, B.; Bellocchi, G.; Bhatia, A.; Brilli, L.; Migliorati, M.D.A.; Doltra, J.; Dorich, C.; Doro, L.; Fitton, N.; Giacomini, S.J.; Grace, P.; Grant, B.; Harrison, M.T.; Jones, S.; Kirschbaum, M.U.F.; Klumpp, K.; Laville, P.; Léonard, J.; Liebig, M.; Lieffering, M.; Martin, R.; McAuliffe, R.; Meier, E.; Merbold, L.; Moore, A.; Myrgiotis, V.; Newton, P.; Pattey, E.; Recous, S.; Rolinski, S.; Sharp, J.; Massad, R.S.; Smith, P.; Smith, W.; Snow, V.; Wu, L.; Zhang, Q.; Soussana, J.F. |
Title |
C and N models Intercomparison – benchmark and ensemble model estimates for grassland production |
Type |
Journal Article |
Year |
2016 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
Volume |
7 |
Issue |
03 |
Pages |
245-247 |
Keywords |
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Abstract |
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Place of Publication |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2040-4700 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
LiveM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4868 |
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Author |
Coucheney, E.; Buis, S.; Launay, M.; Constantin, J.; Mary, B.; García de Cortázar-Atauri, I.; Ripoche, D.; Beaudoin, N.; Ruget, F.; &rianarisoa, K.S.; Le Bas, C.; Justes, E.; Léonard, J. |
Title |
Accuracy, robustness and behavior of the STICS soil–crop model for plant, water and nitrogen outputs: Evaluation over a wide range of agro-environmental conditions in France |
Type |
Journal Article |
Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
Volume |
64 |
Issue |
|
Pages |
177-190 |
Keywords |
soil-crop model; stics; model performances; plant biomass; soil nitrogen; soil water; remote-sensing data; goodness-of-fit; hydrological model; simulation-models; solar-radiation; regional-scale; climate-change; generic model; data set; validation |
Abstract |
Soil-crop models are increasingly used as predictive tools to assess yield and environmental impacts of agriculture in a growing diversity of contexts. They are however seldom evaluated at a given time over a wide domain of use. We tested here the performances of the STICS model (v8.2.2) with its standard set of parameters over a dataset covering 15 crops and a wide range of agropedoclimatic conditions in France. Model results showed a good overall accuracy, with little bias. Relative RMSE was larger for soil nitrate (49%) than for plant biomass (35%) and nitrogen (33%) and smallest for soil water (10%). Trends induced by contrasted environmental conditions and management practices were well reproduced. Finally, limited dependency of model errors on crops or environments indicated a satisfactory robustness. Such performances make STICS a valuable tool for studying the effects of changes in agro-ecosystems over the domain explored. (C) 2014 Elsevier Ltd. All rights reserved. |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1364-8152 |
ISBN |
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Medium |
Article |
Area |
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Conference |
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Notes |
CropM |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4554 |
Permanent link to this record |