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Author |
Rasche, L.; Sos Del Diego, R. |
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Title |
How does a crop model calibrated to national yield data perform on the field scale |
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Conference Article |
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2014 |
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Crop models used as parts of integrated assessments often need to be run on regional, national and global scales. Calibration is an important step in the application procedure, yet on scales like this the process needs to be simplified in order to meet data requirements and computational limits. The question arises if a model calibrated in such a “simple” fashion still performs adequately at field scale, and if parameters not calibrated in the process can nevertheless be used with some confidence in later stages of the assessment. To answer this question, we applied the crop model EPIC to the simulation of sugarcane in Sao Paulo, Brazil. We once calibrated the model using Bayesian calibration to data on yield, aboveground biomass, and root weight measured in four years on two field trials in Sao Paulo. For the second calibration we used a simplified approach and calibrated the model only to FAOSTAT yield data for the whole of Brazil. Both calibrated models were applied to the simulation of stalk yield, aboveground biomass and root weight on a third field trial, and to the simulation of mean yields in Sao Paulo. The results showed that both models were able to adequately depict yields on both scales, but that the model calibrated to only national yield data was not able to accurately simulate root biomass, and to a lesser degree aboveground biomass. We conclude that a simplified calibration performs adequately on both scales, but that non-calibrated parameters may only be used with caution. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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no |
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MA @ admin @ |
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5085 |
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Author |
Köchy, M.; Banse, M.; Tiffin, R.; Ewert, F.; Rötter, R.; Van den Pol-van Dasselaar, A.; Brouwer, F.; Sinabell, F.; Jorgenson, J.; Sætnan, E.; Kipling, R. |
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Title |
General outline of plans for an extension phase of MACSUR |
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Conference Article |
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2014 |
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FACCE MACSUR has indicated a possible extension of funding by two years until May 2017 (phase 2).For phase 2, hub and theme coordinators suggest the following main activities, that will be discussed during the remainder of the meeting and in the coming months.Evolution, upscaling, and transfer of knowledge gained in regional case studies.Assessment of additional scenarios of socio-economic and climate trends.Further development of an interdisciplinary scientific community.Extending scaling methods for crop models to the European and global scale.Intensification of feed quality and animal health modelling with climate change.Economic models from farm to global level capable of reflecting climate change. |
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Series Editor |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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no |
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MA @ admin @ |
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5084 |
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Author |
Hutchings, N. |
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Title |
Farm-scale modelling |
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Conference Article |
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2014 |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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no |
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MA @ admin @ |
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5082 |
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Author |
Rolinski, S.; Weindl, I.; Heinke, J.; Bodirsky, B.L.; Biewald, A.; Lotze-Campen, H. |
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Title |
Environmental impacts of grassland management and livestock production |
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Conference Article |
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2014 |
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The potential of grasslands to sequester carbon and provide feed for livestock production depends on the one hand on climatic conditions but secondly on management and grazing pressure. Using a global vegetation model considering different management and grazing options, effects of livestock density on primary productivity can be assessed. It is expected that low animal densities enhance productivity whereas increasing grazing pressure may deteriorate grass plants. Thus, the optimal animal density depend on the specific primary production of the pasture and optimal grazing intensity. Using these optimal grass yields, the impacts of livestock production on resource use is assessed by applying the global land use model MAgPIE. This model integrates a detailed representation of the livestock sector and integrates socio-economic regional information with spatially explicit biophysical data. With scenario analysis we analyze the impact of livestock production on future deforestation and land use. Our results indicate that the reduction of animal derived calory demand has a huge potential to spare land for nature and reduce deforestation. On the supply side, feeding efficiency gains can help to decrease demand for land and overall biomass requirements. |
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Series Editor |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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no |
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Call Number |
MA @ admin @ |
Serial |
5078 |
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Author |
Hoffmann, H.; Zhao, G.; Van Bussel, L.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Doro, L.; Nendel, C.; Kiese, R.; Raynal, H.; Eckersten, H.; Haas, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Roggero, P.P.; Rötter, R.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Wang, E.; Zhao, Z.; Ewert, F. |
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Title |
Effects of climate input data aggregation on modelling regional crop yields |
Type |
Conference Article |
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Year |
2014 |
Publication |
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Abbreviated Journal |
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Crop models can be sensitive to climate input data aggregation and this response may differ among models. This should be considered when applying field-scale models for assessment of climate change impacts on larger spatial scales or when coupling models across scales. In order to evaluate these effects systematically, an ensemble of ten crop models was run with climate input data on different spatial aggregations ranging from 1, 10, 25, 50 and 100 km horizontal resolution for the state of North Rhine-Westphalia, Germany. Models were minimally calibrated to typical sowing and harvest dates, and crop yields observed in the region, subsequently simulating potential, water-limited and nitrogen-limited production of winter wheat and silage maize for 1982-2011. Outputs were analysed for 19 variables (yield, evapotranspiration, soil organic carbon, etc.). In this study the sensitivity of the individual models and the model ensemble in response to input data aggregation is assessed for crop yield. Results show that the mean yield of the region calculated from climate time series of 1 km horizontal resolution changes only little when using climate input data of higher aggregation levels for most models. However, yield frequency distributions change with aggregation, resembling observed data better with increasing resolution. With few exceptions, these results apply to the two crops and three production situations (potential, water-, nitrogen-limited) and across models including the model ensemble, regardless of differences among models in simulated yield levels and spatial yield patterns. Results of this study improve the confidence of using crop models at varying scales. |
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Corporate Author |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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Approved |
no |
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Call Number |
MA @ admin @ |
Serial |
5077 |
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Permanent link to this record |