Records |
Author |
Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.J.; Rötter, R.P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Naresh Kumar, S.; 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 |
Uncertainty in simulating wheat yields under climate change |
Type |
Journal Article |
Year |
2013 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
Volume |
3 |
Issue |
9 |
Pages |
827-832 |
Keywords |
crop production; models; food; co2; temperature; projections; adaptation; scenarios; ensemble; impacts |
Abstract |
Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking. |
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English |
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1758-678x |
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Notes |
CropM, ftnotmacsur, IPCC-AR5 |
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no |
Call Number |
MA @ admin @ |
Serial |
4599 |
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Author |
Yin, X.; Kersebaum, K.C.; Kollas, C.; Armas-Herrera, C.M.; Baby, S.; Beaudoin, N.; Bindi, M.; Charfeddine, M.; Conradt, T.; Cortazar-Atauri, I.G.D.; Ewert, F.; Ferrise, R.; Hoffmann, H.; Lana, M.; Launay, M.; Manderscheid, R.; Manevski, K.; Mary, B.; Mirschel, W.; Moriondo, M.; Müller, C.; Nendel, C.; Öztürk, I.; Palosuo, T.; Ripoche-Wachte, D.; Rötter, R.P.; Ruget, F.; Sharif, B.; Ventrella, D.; Weigel, H.-J.; Olesen, J.E. |
Title |
Uncertainty in simulating N uptakes, N leaching and N use efficiency in crop rotation systems across Europe |
Type |
Conference Article |
Year |
2016 |
Publication |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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no |
Call Number |
MA @ admin @ |
Serial |
4899 |
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Author |
Sándor, R.; Ma, S.; Acutis, M.; Barcza, Z.; Ben Touhami, H.; Doro, L.; Hidy, D.; Köchy, M.; Lellei-Kovács, E.; Minet, J.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G. |
Title |
Uncertainty in simulating biomass yield and carbon–water fluxes from grasslands under climate change |
Type |
Journal Article |
Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
Volume |
6 |
Issue |
01 |
Pages |
49-51 |
Keywords |
grassland productivity; carbon balance; model simulation; uncertainty; sensitivity |
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English |
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ISSN |
2040-4700 |
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Notes |
CropM, LiveM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4651 |
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Author |
Sándor, R.; Ma, S.; Acutis, M.; Barcza, Z.; Ben, T., H.; Doro, L.; Hidy, D.; Köchy, M.; Lellei-Kovács, E.; Minet, J.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G. |
Title |
Uncertainty in simulating biomass yield and carbon-water fluxes from Euro-Mediterranean grasslands under climate changes |
Type |
Conference Article |
Year |
2014 |
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LiveM |
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Conference |
International Livestock Modelling and Research Colloquium, Bilbao, Spain, 2014-10-14 to 2014-10-16 |
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Approved |
no |
Call Number |
MA @ admin @ |
Serial |
2788 |
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Author |
Webber, H.; Gaiser, T.; Oomen, R.; Teixeira, E.; Zhao, G.; Wallach, D.; Zimmermann, A.; Ewert, F. |
Title |
Uncertainty in future irrigation water demand and risk of crop failure for maize in Europe |
Type |
Journal Article |
Year |
2016 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
Volume |
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Issue |
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Pages |
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Keywords |
crop model; impact assessment; crop water use; evapotranspiration; irrigation; drought; uncertainty |
Abstract |
While crop models are widely used to assess the change in crop productivity with climate change, their skill in assessing irrigation water demand or the risk of crop failure in large area impact assessments is relatively unknown. The objective of this study is to investigate which aspects of modeling crop water use (reference crop evapotranspiration (ET0), soil water extraction, soil evaporation, soil water balance and root growth) contributes most to the variability in estimates of maize crop water use and the risk of crop failure, and demonstrate the resulting uncertainty in a climate change impact study for Europe. The SIMPLACE crop modeling framework was used to couple the LINTUL5 crop model in factorial combinations of 2-3 different approaches for simulating the 5 aspects of crop water use, resulting in 51 modeling approaches. Using experiments in France and New Zeland, analysis of total sensitivity revealed that ET0 explained the most variability in both irrigated maize water use and rainfed grain yield levels, with soil evaporation also imporatant in the French experiment. In the European impact study, net irrigation requirement differed by 36% between the Penman and Hargreaves ET0 methods in the baseline period. Average EU grain yields were similar between models, but differences approached 1-2 tonnes in parts of France and Southern Europe. EU wide esimates of crop failure in the historical period ranged between 5.4 years for Priestley-Taylor to every 7.9 years for the Penman ET0 methods. While the uncertainty in absolute values between models was significant, estimates of relative changes were similar between models, confirming the utility of crop models in assessing climate change impacts. If ET0 estimates in crop models can be improved, through the use of appropriate methods, uncertainty in irrigation water demand as well as in yield estimates under drought can be reduced. |
Address |
2016-09-13 |
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Newsletter July |
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CropM |
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Notes |
CropM; wos; ft=macsur; |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4778 |
Permanent link to this record |