| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.5194/bg-2016-527 |
| Uncertainties in global crop model frameworks: effects of cultivar distribution, crop management and soil handling on crop yield estimates. | |
| Folberth C; Elliott J; Müller C; Balkovic J; Chryssanthacopoulos J; Izaurralde RC; Jones CD; Khabarov N | |
| 发表日期 | 2016 |
| 出处 | Biogeosciences Discussions : 1-30 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | 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. |
| 主题 | Ecosystems Services and Management (ESM) |
| 关键词 | agricultural management agro-ecologic systems evapotranspiration soil data global agriculture |
| URL | http://pure.iiasa.ac.at/id/eprint/14232/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/130706 |
| 推荐引用方式 GB/T 7714 | Folberth C,Elliott J,Müller C,et al. Uncertainties in global crop model frameworks: effects of cultivar distribution, crop management and soil handling on crop yield estimates.. 2016. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Uncertainties%20in%2（2208KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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