| Records |
| 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. |
| Title |
Effects of climate input data aggregation on modelling regional crop yields |
Type  |
Conference Article |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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Issue |
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| Abstract |
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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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5077 |
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| Author |
Kersebaum, K.C.; Kollas, C.; Bindi, M.; Palosuo, T.; Wu, L.; Sharif, B.; Öztürk, I.; Trnka, M.; Hlavinka, P.; Nendel, C.; Müller, C.; Waha, K.; Armas-Herrera, C.; Olesen, J.E.; Eitzinger, J.; Roggero, P.P.; Conradt, T.; Martre, P.; Ferrise, R.; Moriondo, M.; Ruiz-Ramos, M.; Ventrella, D.; Rötter, R.P.; Wegehenkel, M.; Eckersten, H.; Lorite Torres, I.J.; Hernandez, C.G.; Launay, M.; De Wit, A.; Hoffmann, H.; Weigel, H.-J.; Manderscheid, R.; Beaudoin, N.; Constantin, J.; Garcia de Cortazar-Atauri, I.; Mary, B.; Ripoche, D.; Ruget, F. |
| Title |
Model inter-comparison on crop rotation effects – an intermediate report |
Type |
Conference Article |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed. |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Edition |
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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 |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5104 |
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| Author |
Zhao, G.; Hoffmann, H.; Van Bussel, L.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.; Nendel, C.; 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.; Kiese, R.; Wang, E.; Ewert, F. |
| Title |
Weather data aggregation’s effects on simulation of cropping systems: a model, production system and crop comparison |
Type |
Conference Article |
| Year |
2014 |
Publication |
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Issue |
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Pages |
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| Abstract |
Interactions of climate, soil and management practices in cropping systems can be simulated at different scales to provide information for decision making. Low resolution simulation need less effort, but important details could be lost through data aggregation effects (DAEs). This paper aims to provide a general method to assess the DAEs on weather data and the simulation of cropping systems, and further investigate how the DAEs vary with changing crop models, crops, variables and production systems. A 30-year continuous cropping system was simulated for winter wheat and silage maize and potential, water-limited and water-nitrogen-limited production situations. Climate data of 1 km resolution and aggregations to resolutions of 10 to 100 km was used as input for the simulations. The data aggregation narrowed the variation of weather data and DAEs increased with increasingly coarser spatial resolution, causing the loss of hot spots in simulated results. Spatial patterns were similar across different resolutions. Consistent with DAEs on weather data, the DAEs on simulated yield (0 to 1.2 t ha-1 for winter wheat and 0 to 1.7 t ha-1 for silage maize), evapotranspiration (3 to 45 mm yr-1 for winter wheat and 4 to 40 mm yr-1 for silage maize), and water use efficiency (0.02 to 0.25 kg m-3 for winter wheat and 0.04 to 0.4 kg m-3 for silage maize), increased with coarser spatial resolution. Thus, if spatial information is needed for local management decisions, higher resolution is needed to adequately capture the spatial heterogeneity or hot spots in the region. |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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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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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5141 |
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| Author |
Ewert, F.; van Bussel, L.G.J.; Zhao, G.; Hoffmann, H.; Gaiser, T.; Specka, X.; Nendel, C.; Kersebaum, K.-C.; Sosa, C.; Lewan, E.; Yeluripati, J.; Kuhnert, M.; Tao, F.; Rötter, R.P.; Constantin, J.; Raynal, H.; Wallach, D.; Teixeira, E.; Grosz, B.; Bach, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Kiese, R.; Haas, E.; Eckersten, H.; Trombi, G.; Bindi, M.; Klein, C.; Biernath, C.; Heinlein, F.; Priesack, E.; Cammarano, D.; Asseng, S.; Elliott, J.; Glotter, M.; Basso, B.; Baigorria, G.A.; Romero, C.C.; Moriondo, M. |
| Title |
Uncertainties in Scaling up Crop Models for Large Area Climate-change Impact Assessments |
Type |
Book Chapter |
| Year |
2015 |
Publication |
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Abbreviated Journal |
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Issue |
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Pages |
261-277 |
| Keywords |
CropM; |
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Imperial College Press |
Place of Publication |
London |
Editor |
Rosenzweig, C.; Hillel, D. |
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Series Title |
Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project (AgMIP) Integrated Crop and Economic Assessments — Joint Publication with American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America (In 2 Parts) |
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ICP Series on Climate Change Impacts, Adaptation, |
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no |
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MA @ admin @ |
Serial |
2427 |
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Boote, K.J.; Porter, C.; Jones, J.W.; Thorburn, P.J.; Kersebaum, K.C.; Hoogenboom, G.; White, J.W.; Hatfield, J.L. |
| Title |
Sentinel site data for crop model improvement—definition and characterization |
Type |
Book Chapter |
| Year |
2016 |
Publication |
Improving Modeling Tools to Assess Climate Change Effects on Crop Response |
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Crop models are increasingly being used to assess the impacts of future climate change on production and food security. High quality, site-specific data on weather, soils, management, and cultivar are needed for those model applications. Also important is that model development, evaluation, improvement, and calibration require additional high quality, site-specific measurements on crop yield, growth, phenology, and ancillary traits. We review the evolution of minimum data set requirements for agroecosystem modeling and then describe the characteristics and ranking of sentinel site data needed for crop model improvement, calibration, and application. We in the Agricultural Model Intercomparison and Improvement Project (AgMIP), propose to rank sentinel site data sets as platinum, gold, silver, and copper, based on the degree of true site-specific measurement of weather, soils, management, crop yield, as well as the quality, comprehensiveness, quantity, accuracy, and value. For example, to be ranked platinum, the weather and soil characterization must be measured on-site, and all management inputs must be known. Dataset ranking will be lower for weather measured off-site or soil traits estimated from soil mapping. Ranking also depends on the intended purposes for data use. If the purpose is to improve a crop model for response to water or N, then additional observations are necessary, such as initial soil water, initial soil inorganic N, and plant N uptake during the growing season to be ranked platinum. Rankings are enhanced by presence of multiple treatments and sites. Examples of platinum-, gold-, and silver-quality data sets for model improvement and calibration uses are illustrated. |
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Editor |
Hatfield, J.L.; Fleisher, D. |
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Series Title |
Advances in Agricultural Systems Modeling |
Abbreviated Series Title |
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| Series Volume |
7 |
Series Issue |
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Edition |
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ISBN |
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Expedition |
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Conference |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4980 |
| Permanent link to this record |
