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Author van Bussel, L.G.J.; Ewert, F.; Zhao, G.; Hoffmann, H.; Enders, A.; Wallach, D.; Asseng, S.; Baigorria, G.A.; Basso, B.; Biernath, C.; Cammarano, D.; Chryssanthacopoulos, J.; Constantin, J.; Elliott, J.; Glotter, M.; Heinlein, F.; Kersebaum, K.-C.; Klein, C.; Nendel, C.; Priesack, E.; Raynal, H.; Romero, C.C.; Rötter, R.P.; Specka, X.; Tao, F.
Title Spatial sampling of weather data for regional crop yield simulations Type Journal Article
Year 2016 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 220 Issue Pages 101-115
Keywords (up) Regional crop simulations; Winter wheat; Upscaling; Stratified sampling; Yield estimates; climate-change scenarios; water availability; growth simulation; potential impact; food-production; winter-wheat; model; resolution; systems; soil
Abstract Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50,100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4673
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Author Eitzinger, J.; Thaler, S.; Schmid, E.; Strauss, F.; Ferrise, R.; Moriondo, M.; Bindi, M.; Palosuo, T.; Rotter, R.; Kersebaum, K.C.; Olesen, J.E.; Patil, R.H.; Saylan, L.; Caldag, B.; Caylak, O.
Title Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria Type Journal Article
Year 2013 Publication Journal of Agricultural Science Abbreviated Journal J. Agric. Sci.
Volume 151 Issue 6 Pages 813-835
Keywords (up) simulate yield response; climate-change scenarios; central-europe; nitrogen dynamics; high-temperature; future climate; elevated co2; soil; growth; variability
Abstract The objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0021-8596 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4601
Permanent link to this record