Google Scholar: cites,
Uncertainties in global crop model frameworks : effects of cultivar distribution, crop management and soil handling on crop yield estimates
Folberth, Christian (International Institute for Applied Systems Analysis, Ecosystem Services and Management Program)
Elliot, Joshua (University of Chicago)
Müller, Christoph (Postdam-Institut für Klimafolgenforschung)
Balkovic, Juraj (International Institute for Applied Systems Analysis, Ecosystem Services and Management Program)
Chryssanthacopoulos, James (Columbia University. Center for Climate Systems Research)
Izaurralde, Roberto C. (University of Maryland. Department of Geographical Sciences)
Khabarov, Nikolay (International Institute for Applied Systems Analysis, Ecosystem Services and Management Program)
Liu, Wenfeng (Eawag)
Reddy, Ashwan (University of Maryland. Department of Geographical Sciences)
Schmid, Erwin (Universität für Bodenkultur Wien)
Skalský, Rastislav (International Institute for Applied Systems Analysis, Ecosystem Services and Management Program)
Yang, Hong (Eawag)
Arneth, Almut (Karlsruher Institut für Technologie)
Ciais, Philippe (Laboratoire des Sciences du Climat et de l'Environnement)
Deryng, Delphine (Columbia University Center for Climate Systems Research)
Lawrence, Peter J. (National Center for Atmospheric Research. Earth System Laboratory)
Olin, Stefan (Lunds Universitet. Department of Physical Geography and Ecosystem Science)
Pugh, Thomas A.M. (Karlsruher Institut für Technologie)
Ruane, Alex C. (Columbia University Center for Climate Systems Research)
Wang, Xuhui (Laboratoire des Sciences du Climat et de l'Environnement)

Data: 2016
Resum: Global gridded crop models (GGCMs) combine field-scale agronomic models or sets of plant growth algorithms with gridded spatial input data to estimate spatially explicit crop yields and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different bio-physical models, setups, and input data. While algorithms have been in the focus of recent GGCM comparisons, this study investigates differences in maize and wheat yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison (GGCMI) project. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, geographic distribution of cultivars, and selection of subroutines e. g. for the estimation of potential evapotranspiration or soil erosion. The analyses reveal long-term trends and inter-annual yield variability in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. Absolute yield levels as well depend not only on nutrient supply but also on the parameterization and distribution of crop cultivars. All GGCMs show an intermediate performance in reproducing reported absolute yield levels or inter-annual dynamics. Our findings suggest that studies focusing on the evaluation of differences in bio-physical routines may require further harmonization of input data and management assumptions in order to eliminate background noise resulting from differences in model setups. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions in setups appears the best solution for bracketing such uncertainties as long as comprehensive global datasets taking into account regional differences in crop management, cultivar distributions and coefficients for parameterizing agro-environmental processes are lacking. Finally, we recommend improvements in the documentation of setups and input data of GGCMs in order to allow for sound interpretability, comparability and reproducibility of published results.
Ajuts: European Commission 603542
European Commission 610028
Nota: Agraïments: We acknowledge the support and data provision by the Agricultural Intercomparison and Improvement Project (AgMIP). AA and TAMP were funded by the European Commission's 7th Framework Programme, under Grant Agreement number 603542 (LUC4C).
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: article ; recerca ; Versió sotmesa a revisió
Matèria: Agricultural management ; Agro-ecologic systems ; Evapotranspiration ; Soil data ; Global agriculture
Publicat a: Biogeosciences Discussions, 20 Dec. 2016

DOI: 10.5194/bg-2016-527

30 p, 2.2 MB

El registre apareix a les col·leccions:
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències > CREAF (Centre de Recerca Ecològica i d'Aplicacions Forestals) > Imbalance-P
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 Registre creat el 2017-10-18, darrera modificació el 2021-07-19

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