eprintid: 14232 rev_number: 16 eprint_status: archive userid: 353 dir: disk0/00/01/42/32 datestamp: 2017-01-09 14:46:40 lastmod: 2021-08-27 17:28:23 status_changed: 2017-01-09 14:46:40 type: article metadata_visibility: show item_issues_count: 1 creators_name: Folberth, C. creators_name: Elliott, J. creators_name: Müller, C. creators_name: Balkovic, J. creators_name: Chryssanthacopoulos, J. creators_name: Izaurralde, R.C. creators_name: Jones, C.D. creators_name: Khabarov, N. creators_name: Liu, W. creators_name: Reddy, A. creators_name: Schmid, E. creators_name: Skalsky, R. creators_name: Yang, H. creators_name: Arneth, A. creators_name: Ciais, P. creators_name: Deryng, D. creators_name: Lawrence, P.J. creators_name: Olin, S. creators_name: Pugh, T.A.M. creators_name: Ruane, A.C. creators_name: Wang, X. creators_id: 2033 creators_id: 1977 creators_id: 1850 creators_id: 1986 creators_orcid: 0000-0002-6738-5238 creators_orcid: 0000-0003-2955-4931 creators_orcid: 0000-0001-5372-4668 creators_orcid: 0000-0002-0983-6897 title: Uncertainties in global crop model frameworks: effects of cultivar distribution, crop management and soil handling on crop yield estimates ispublished: submitted divisions: prog_esm keywords: agricultural management; agro-ecologic systems; evapotranspiration; soil data; global agriculture abstract: 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 40 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 45 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 50 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 55 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. date: 2016-12-20 date_type: published publisher: European Geosciences Union (EGU) id_number: doi:10.5194/bg-2016-527 creators_browse_id: 92 creators_browse_id: 23 creators_browse_id: 151 creators_browse_id: 287 full_text_status: public publication: Biogeosciences Discussions pagerange: 1-30 refereed: TRUE issn: 1810-6285 projects: Land use change: assessing the net climate forcing, and options for climate change mitigation and adaptation (LUC4C, FP7 603542) projects: Effects of phosphorus limitations on Life, Earth system and Society (IMBALANCE-P, FP7 610028) coversheets_dirty: FALSE fp7_project: yes fp7_project_id: info:eu-repo/grantAgreement/EC/FP7/603542/EU/Land use change: assessing the net climate forcing, and options for climate change mitigation and adaptation/LUC4C; info:eu-repo/grantAgreement/EC/FP7/610028/EU//IMBALANCE-P fp7_type: info:eu-repo/semantics/article access_rights: info:eu-repo/semantics/openAccess citation: Folberth, C. ORCID: https://orcid.org/0000-0002-6738-5238 , Elliott, J., Müller, C., Balkovic, J. ORCID: https://orcid.org/0000-0003-2955-4931 , Chryssanthacopoulos, J., Izaurralde, R.C., Jones, C.D., Khabarov, N. ORCID: https://orcid.org/0000-0001-5372-4668 , et al. (2016). Uncertainties in global crop model frameworks: effects of cultivar distribution, crop management and soil handling on crop yield estimates. Biogeosciences Discussions 1-30. 10.5194/bg-2016-527 . (Submitted) document_url: https://pure.iiasa.ac.at/id/eprint/14232/1/Uncertainties%20in%20global%20crop%20model%20frameworks.pdf