Records |
Author |
Hoffmann, H.; Zhao, G.; Asseng, S.A.U.-,; Bindi, M.; Cammarano, D.; Constantin, J.; Coucheney, E.; Dechow, R.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kassie, B.; Kersebaum, K.C.; Kiese, R.; Klatt, S.; Kuhnert, M.; Lewan, E.; Moriondo, M.; Nendel, C.; Raynal, H.; Roggero, P.P.; Rötter, R.; Siebert, S.; Sosa, C.; Specka, X.; Tao, F.; Teixeira, E.; Trombi, G.; Yeluripati, J.; Vanuytrecht, E.; Wallach, D.; Wang, E.; Weihermüller, L.; Zhao, Z.; Ewert, F. |
Title |
Analysing data aggregation effects on large-scale yield simulations |
Type |
Conference Article |
Year |
2016 |
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Place of Publication |
Berlin (Germany) |
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Conference |
International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
Notes |
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Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4923 |
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Author |
Rezaei, E.E.; Siebert, S.; Ewert, F. |
Title |
Data aggregation does not reduce signals of heat and drought stress in large area yield simulations |
Type |
Conference Article |
Year |
2016 |
Publication |
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Pages |
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Place of Publication |
Berlin (Germany) |
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poster |
Area |
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Conference |
International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
Notes |
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Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4919 |
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Author |
Siebert, S.; Ewert, F.; Rezaei, E.E.; Kage, H.; Grass, R. |
Title |
Impact of heat stress on crop yield-on the importance of considering canopy temperature |
Type |
Journal Article |
Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
Volume |
9 |
Issue |
4 |
Pages |
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Keywords |
heat stress; crop yield; temperature; soil moisture; modelling; wheat; rye; harvest index; wheat yields; climate-change; winter-wheat; grain number; extreme heat; maize; variability; irrigation; drought |
Abstract |
Increasing crop productivity while simultaneously reducing the environmental footprint of crop production is considered a major challenge for the coming decades. Even short episodes of heat stress can reduce crop yield considerably causing low resource use efficiency. Studies on the impact of heat stress on crop yields over larger regions generally rely on temperatures measured by standard weather stations at 2 m height. Canopy temperatures measured in this study in field plots of rye were up to 7 degrees C higher than air temperature measured at typical weather station height with the differences in temperatures controlled by soil moisture contents. Relationships between heat stress and grain number derived from controlled environment studies were only confirmed under field conditions when canopy temperature was used to calculate stress thermal time. By using hourly mean temperatures measured by 78 weather stations located across Germany for the period 1994-2009 it is estimated, that mean yield declines in wheat due to heat stress during flowering were 0.7% when temperatures are measured at 2 m height, but yield declines increase to 22% for temperatures measured at the ground. These results suggest that canopy temperature should be simulated or estimated to reduce uncertainty in assessing heat stress impacts on crop yield. |
Address |
2016-10-31 |
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English |
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ISSN |
1748-9326 |
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Notes |
CropM, ftnotmacsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4814 |
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Author |
Siebert, S.; Ewert, F. |
Title |
Future crop production threatened by extreme heat |
Type |
Journal Article |
Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
Volume |
9 |
Issue |
4 |
Pages |
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Keywords |
climate-change; simulation-models; wheat yields; day length; temperature; growth; impact; co2; phenology; patterns |
Abstract |
Heat is considered to be a major stress limiting crop growth and yields. While important findings on the impact of heat on crop yield have been made based on experiments in controlled environments, little is known about the effects under field conditions at larger scales. The study of Deryng et al (2014 Global crop yield response to extreme heat stress under multiple climate change futures Environ. Res. Lett. 9 034011), analysing the impact of heat stress on maize, spring wheat and soya bean under climate change, represents an important contribution to this emerging research field. Uncertainties in the occurrence of heat stress under field conditions, plant responses to heat and appropriate adaptation measures still need further investigation. |
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2016-10-31 |
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English |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-9326 |
ISBN |
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Medium |
Article |
Area |
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Conference |
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Notes |
CropM, ftnotmacsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4813 |
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Author |
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 |
Issue |
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Pages |
141-157 |
Keywords |
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 |
Abstract |
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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Edition |
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ISSN |
0936-577x |
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Notes |
CropM, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4754 |
Permanent link to this record |