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Author Constantin, J.; Bergez, J.-E.; Raynal, H.; Hoffmann, H.; Ewert, F.
Title (up) Impact of maize management variability modeled as decision rules on yield and Drainage at the regional scale Type Conference Article
Year 2016 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Berlin (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium poster
Area Expedition Conference International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany
Notes Approved no
Call Number MA @ admin @ Serial 4913
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Author Hoffmann, H.; Zhao, G.; Asseng, S.; Bindi, M.; Biernath, C.; 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.
Title (up) Impact of spatial soil and climate input data aggregation on regional yield simulations Type Journal Article
Year 2016 Publication PLoS One Abbreviated Journal PLoS One
Volume 11 Issue 4 Pages e0151782
Keywords systems simulation; nitrogen dynamics; winter-wheat; crop models; data resolution; scale; water; variability; calibration; weather
Abstract 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.
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 1932-6203 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4725
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Author Kuhnert, M.; Yeluripati, J.; Smith, P.; Hoffmann, H.; Constantin, J.; Coucheney, E.; Dechow, R.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kersebaum, K.-C.; Kiese, R.; Klatt, S.; Lewan, E.; Nendel, C.; Raynal, H.; Sosa, C.; Specka, X.; Teixeira, E.; Wang, E.; Weihermüller, L.; Zhao, G.; Zhao, Z.; Ewert, F.
Title (up) Impacts of soil and weather data aggregation in spatial modelling of net primary production of croplands Type Conference Article
Year 2016 Publication Abbreviated Journal
Volume Issue Pages
Keywords CropM;
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Belrin (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference International Crop Modelling Symposium iCropM 2016, 2016-03-15 to 2016-03-17, Belrin
Notes Approved no
Call Number MA @ admin @ Serial 2579
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Author Rodriguez, A.; Ruiz-Ramos, M.; Palosuo, T.; Carter, T.R.; Fronzek, S.; Lorite, I.J.; Ferrise, R.; Pirttioja, N.; Bindi, M.; Baranowski, P.; Buis, S.; Cammarano, D.; Chen, Y.; Dumont, B.; Ewert, F.; Gaiser, T.; Hlavinka, P.; Hoffmann, H.; Hohn, J.G.; Jurecka, F.; Kersebaum, K.C.; Krzyszczak, J.; Lana, M.; Mechiche-Alami, A.; Minet, J.; Montesino, M.; Nendel, C.; Porter, J.R.; Ruget, F.; Semenov, M.A.; Steinmetz, Z.; Stratonovitch, P.; Supit, I.; Tao, F.; Trnka, M.; de Wit, A.; Roetter, R.P.
Title (up) Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations Type Journal Article
Year 2019 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 264 Issue Pages 351-362
Keywords Wheat adaptation; Uncertainty; Climate change; Decision support; Response surface; Outcome confidence; Climate-Change Impacts; Response Surfaces; Wheat; Uncertainty; Yield; Simulation; 21St-Century; Productivity; Temperature; Projections
Abstract unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivwn L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.
Address 2019-01-07
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 0168-1923 ISBN Medium
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5214
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Author Kollas, C.; Kersebaum, C.; Bindi, M.; Wu, L.; Sharif, B.; Öztürk, I.; Trnka, M.; Hlavinka, P.; Nendel, C.; Palosuo, T.; Müller, C.; Waha, K.; Herrera, C.; Olesen, E.; Eitzinger, J.; Roggero, P.-P.; Conradt, T.; Martre, P.; Ferrise, R.; Moriondo, M.; Ramos, M.; Ventrella, D.; Rötter, P.; Wegehenkel, M.; Eckersten, H.; Torres, I.; Hernandez, C.; Launay, M.; Witt, A.; Hoffmann, H.
Title (up) Improving yield predictions by crop rotation modelling? a multi-model comparison Type Conference Article
Year 2014 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
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ISSN ISBN Medium
Area Expedition Conference MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12
Notes Approved no
Call Number MA @ admin @ Serial 2560
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