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Author |
Höglind, M., Persson T. |
Title |
Yields and harvest security in Nordic forage production in the future – examples from simulation studies using the LINGRA model |
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Conference Article |
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2013 |
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CropM |
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NJF Seminar 455 Nordic Forage Model Applications- predicting forage yield and quality in a variable and changing climate, Forssa, Finland, NJF Report Vol. 9 No. 1 2013, p 4-5., 2013-01-30 to 2013-01-31 |
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MA @ admin @ |
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2484 |
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Höglind, M. |
Title |
Europeisk landbruk i et klima i endring (MACSUR) |
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Conference Article |
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2014 |
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CropM |
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Bioforsk-konferansen 2014, Hamar Norway, 2014-02-05 to 2014-02-06 |
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MA @ admin @ |
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2485 |
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Author |
Höglind, M.; Persson, T.; van Oijen, M. |
Title |
Identifying target traits for forage grass breeding under a changing climate in Norway using the BASGRA model |
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Conference Article |
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2013 |
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CropM |
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Proceedings of the 22nd International Grasslands Congress, Sydney, Australia, 2013-09-15 to 2013-09-19 |
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MA @ admin @ |
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2483 |
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Zhao, G.; Hoffmann, H.; van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.L.; Constantin, J.; Raynal, H.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.G.; Nendel, C.; Kiese, R.; Eckersten, H.; Haas, E.; Vanuytrecht, E.; Wang, E.; Kuhnert, M.; Trombi, G.; Moriondo, M.; Bindi, M.; Lewan, E.; Bach, M.; Kersebaum, K.C.; Rotter, R.; Roggero, P.P.; Wallach, D.; Cammarano, D.; Asseng, S.; Krauss, G.; Siebert, S.; Gaiser, T.; Ewert, F. |
Title |
Effect of weather data aggregation on regional crop simulation for different crops, production conditions, and response variables |
Type |
Journal Article |
Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
Volume |
65 |
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141-157 |
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crop model; model comparison; spatial resolution; data aggregation; spatial heterogeneity; scaling; climate-change scenarios; sub-saharan africa; winter-wheat; spatial-resolution; yield response; input data; systems simulation; large-scale; soil data; part i |
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We assessed the weather data aggregation effect (DAE) on the simulation of cropping systems for different crops, response variables, and production conditions. Using 13 process-based crop models and the ensemble mean, we simulated 30 yr continuous cropping systems for 2 crops (winter wheat and silage maize) under 3 production conditions for the state of North Rhine-Westphalia, Germany. The DAE was evaluated for 5 weather data resolutions (i.e. 1, 10, 25, 50, and 100 km) for 3 response variables including yield, growing season evapotranspiration, and water use efficiency. Five metrics, viz. the spatial bias (Delta), average absolute deviation (AAD), relative AAD, root mean squared error (RMSE), and relative RMSE, were used to evaluate the DAE on both the input weather data and simulated results. For weather data, we found that data aggregation narrowed the spatial variability but widened the., especially across mountainous areas. The DAE on loss of spatial heterogeneity and hotspots was stronger than on the average changes over the region. The DAE increased when coarsening the spatial resolution of the input weather data. The DAE varied considerably across different models, but changed only slightly for different production conditions and crops. We conclude that if spatially detailed information is essential for local management decision, higher resolution is desirable to adequately capture the spatial variability for heterogeneous regions. The required resolution depends on the choice of the model as well as the environmental condition of the study area. |
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English |
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0936-577x |
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CropM, ft_macsur |
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MA @ admin @ |
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4754 |
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Hlavinka, P.; Kersebaum, K.C.; Dubrovský, M.; Pohanková, E.; Balek, J.; Žalud, Z.; Trnka, M. |
Title |
Water balance and yield estimates for field crop rotations present versus future conditions based on transient scenarios |
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Conference Article |
Year |
2014 |
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CropM |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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MA @ admin @ |
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2478 |
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