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	Author	Martre, P.; Wallach, D.; Asseng, S.; Ewert, F.; Jones, J.W.; Rötter, R.P.; Boote, K.J.; Ruane, A.C.; Thorburn, P.J.; Cammarano, D.; Hatfield, J.L.; Rosenzweig, C.; Aggarwal, P.K.; Angulo, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Brisson, N.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.F.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Kumar, S.N.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; White, J.W.; Wolf, J.
	Title	Multimodel ensembles of wheat growth: many models are better than one			Type	Journal Article
	Year	2015	Publication	Global Change Biology	Abbreviated Journal	Glob. Chang. Biol.
	Volume	21	Issue	2	Pages	911-925
	Keywords	Climate; Climate Change; Environment; Models, Biological; Seasons; Triticum/growth & development; ecophysiological model; ensemble modeling; model intercomparison; process-based model; uncertainty; wheat (Triticum aestivum L.)
	Abstract	Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1354-1013	ISBN		Medium	Article
	Area		Expedition		Conference
	Notes	CropM, ftnotmacsur			Approved	no
	Call Number	MA @ admin @			Serial	4665
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	Author	Angulo, C.; Gaiser, T.; Rötter, R.P.; Børgesen, C.D.; Hlavinka, P.; Trnka, M.; Ewert, F.
	Title	‘Fingerprints’ of four crop models as affected by soil input data aggregation			Type	Journal Article
	Year	2014	Publication	European Journal of Agronomy	Abbreviated Journal	European Journal of Agronomy
	Volume	61	Issue		Pages	35-48
	Keywords	crop model; soil data; spatial resolution; yield distribution; aggregation; us great-plains; climate-change; integrated assessment; simulating wheat; yields; scale; productivity; uncertainty; variability; responses
	Abstract	• Systematic analysis of the influence of spatial soil data resolution on simulated regional yields and total growing season evapotranspiration. • The responses of four crop models of different complexity are compared. • Differences between models are larger than the effect of the chosen spatial soil data resolution. • Low influence of soil data resolution due to: high precipitation amount, methods for calculating water retention and method of data aggregation. The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptake and drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form of frequency distributions, depicted by bean-plots. In both regions, soil data aggregation had very small influence on the shape and range of frequency distributions of simulated yield and simulated total growing season evapotranspiration for all models. Further analysis revealed that the small influence of spatial resolution of soil input data might be related to: (a) the high precipitation amount in the region which partly masked differences in soil characteristics for water holding capacity, (b) the loss of variability in hydraulic soil properties due to the methods applied to calculate water retention properties of the used soil profiles, and (c) the method of soil data aggregation. No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models. Our results support earlier recommendation to evaluate model results on the basis of frequency distributions since these offer quick and better insight into the distribution of simulation results as compared to summary statistics only. Finally, our results support conclusions from other studies about the usefulness of considering a multi-model approach to quantify the uncertainty in simulated yields introduced by the crop growth simulation approach when exploring the effects of scaling for regional yield impact assessments.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1161-0301	ISBN		Medium	Article
	Area		Expedition		Conference
	Notes	CropM, ft_macsur			Approved	no
	Call Number	MA @ admin @			Serial	4511
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	Author	Angulo, C.
	Title	Scaling methods in using crop moellingfor climate impactassessment			Type	Book Whole
	Year	2014	Publication		Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	University of Bonn	Place of Publication	Bonn	Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	CropM			Approved	no
	Call Number	MA @ admin @			Serial	5152
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	Author	Cammarano, D.; Rötter, P.; Ewert, F.; Palosuo, T.; Bindi, M.; Kersebaum, K.C.; Olesen, J.E.; Trnka, M.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Angulo, C.; Gaiser, T.; Nendel, C.; Martre, P.; de Wit, A.
	Title	Challenges for Agro-Ecosystem Modelling in Climate Change Risk Assessment for major European Crops and Farming systems			Type	Conference Article
	Year	2013	Publication		Abbreviated Journal
	Volume		Issue		Pages	555-564
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	Impacts World 2013, International Conference on Climate Change Effects, Potsdam, Germany, 2013-05-27 to 2013-05-30
	Notes				Approved	no
	Call Number	MA @ admin @			Serial	2765
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	Author	Rötter, R.P.; Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Basso, B.; Ruane, A.; Boote, K.J.; Thorburn, P.; Brisson, N.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Pertuzzi; Biernath, C.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.-C.; Müller, C.; Kumar, S.N.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J.
	Title	Quantifying Uncertainties in Modeling Crop Water Use under Climate Change			Type	Conference Article
	Year	2013	Publication		Abbreviated Journal
	Volume		Issue		Pages
	Keywords	CropM
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	Impacts World 2013, International Conference on Climate Change Effects, Potsdam, Germany, 2013-05-27 to 2013-05-30
	Notes				Approved	no
	Call Number	MA @ admin @			Serial	2767
Permanent link to this record