| Records |
| Author |
Angulo, C.; Rötter, R.; Lock, R.; Enders, A.; Fronzek, S.; Ewert, F. |
Title  |
Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe |
Type |
Journal Article |
| Year |
2013 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
170 |
Issue |
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Pages |
32-46 |
| Keywords |
regional crop modelling; calibration; impact assessment; yield variability; simulation; simulation-models; elevated CO2; integrated assessment; bayesian calibration; atmospheric CO2; growth simulation; use efficiency; spring wheat; winter-wheat; large-area |
| Abstract |
Process-based crop simulation models are increasingly used in regional climate change impact studies, but little is known about the implications of different calibration strategies on simulated yields. This study aims to assess the importance of region-specific calibration of five important field crops (winter wheat, winter barley, potato, sugar beet and maize) across 25 member countries of the European Union (EU25). We examine three calibration strategies and their implications on spatial and temporal yield variability in response to climate change: (i) calculation of phenology parameters only, (ii) consideration of both phenology calibration and a yield correction factor and (iii) calibration of phenology and selected growth processes. The analysis is conducted for 533 climate zones, considering 24 years of observed yield data (1983-2006). The best performing strategy is used to estimate the impacts of climate change, increasing CO2 concentration and technology development on yields for the five crops across EU25, using seven climate change scenarios for the period 2041-2064. Simulations and calibrations are performed with the crop model LINTUL2 combined with a calibration routine implemented in the modelling interface LINTUL-FAST. The results show that yield simulations improve if growth parameters are considered in the calibration for individual regions (strategy 3); e.g. RMSE values for simulated winter wheat yield are 2.36, 1.10 and 0.70 Mg ha(-1) for calibration strategies 1, 2 and 3, respectively. The calibration strategy did not only affect the model simulations under reference climate but also the extent of the simulated climate change impacts. Applying the calibrated model for impact assessment revealed that climatic change alone will reduce crop yields. Consideration of the effects of increasing CO2 concentration and technology development resulted in yield increases for all crops except maize (i.e. the negative effects of climate change were outbalanced by the positive effects of CO2 and technology change), with considerable differences between scenarios and regions. Our simulations also suggest some increase in yield variability due to climate change which, however, is less pronounced than the differences among scenarios which are particularly large when the effects of CO2 concentration and technology development are considered. Our results stress the need for region-specific calibration of crop models used for Europe-wide assessments. Limitations of the considered strategies are discussed. We recommend that future work should focus on obtaining more comprehensive, high quality data with a finer resolution allowing application of improved strategies for model calibration that better account for spatial differences and changes over time in the growth and development parameters used in crop models. (c) 2012 Elsevier B.V. All rights reserved. |
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0168-1923 |
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CropM |
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MA @ admin @ |
Serial |
4597 |
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Salo, T.J.; Palosuo, T.; Kersebaum, K.C.; Nendel, C.; Angulo, C.; Ewert, F.; Bindi, M.; Calanca, P.; Klein, T.; Moriondo, M.; Ferrise, R.; Olesen, J.E.; Patil, R.H.; Ruget, F.; Takáč, J.; Hlavinka, P.; Trnka, M.; Rötter, R.P. |
| Title |
Comparing the performance of 11 crop simulation models in predicting yield response to nitrogen fertilization |
Type |
Journal Article |
| Year |
2016 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
| Volume |
154 |
Issue |
7 |
Pages |
1218-1240 |
| Keywords |
northern growing conditions; climate-change impacts; spring barley; systems simulation; farming systems; soil properties; winter-wheat; dynamics; growth; management |
| Abstract |
Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area index (LAI) and yield observations. The models were then tested against new data for 2009 and their performance was assessed and compared with both the two calibration years and the test year. For the calibration period, root mean square error between measurements and simulated grain dry matter yields ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi-model mean could not correct systematic errors in model simulations. Variation in soil N mineralization and LAI development due to differences in weather not captured by the models most likely was the main reason for their unsatisfactory performance. This suggests the need for model improvement in soil N mineralization as a function of soil temperature and moisture. Furthermore, specific weather event impacts such as low temperatures after emergence in 2009, tending to enhance tillering, and a high precipitation event just before harvest in 2008, causing possible yield penalties, were not captured by any of the models compared in the current study. |
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0021-8596 1469-5146 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4713 |
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Angulo, C.; Rötter, R.; Trnka, M.; Pirttioja, N.; Gaiser, T.; Hlavinka, P.; Ewert, F. |
| Title |
Characteristic ‘fingerprints’ of crop model responses to weather input data at different spatial resolutions |
Type |
Journal Article |
| Year |
2013 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
49 |
Issue |
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Pages |
104-114 |
| Keywords |
crop model; weather data resolution; aggregation; yield distribution; climate-change scenarios; areal unit problem; simulation-model; winter-wheat; system model; impacts; europe; yield; productivity; precipitation |
| Abstract |
Crop growth simulation models are increasingly used for regionally assessing the effects of climate change and variability on crop yields. These models require spatially and temporally detailed, location-specific, environmental (weather and soil) and management data as inputs, which are often difficult to obtain consistently for larger regions. Aggregating the resolution of input data for crop model applications may increase the uncertainty of simulations to an extent that is not well understood. The present study aims to systematically analyse the effect of changes in the spatial resolution of weather input data on yields simulated by four crop models (LINTUL-SLIM, DSSAT-CSM, EPIC and WOFOST) which were utilized to test possible interactions between weather input data resolution and specific modelling approaches representing different degrees of complexity. The models were applied to simulate grain yield of spring barley in Finland for 12 years between 1994 and 2005 considering five spatial resolutions of daily weather data: weather station (point) and grid-based interpolated data at resolutions of 10 km x 10 km; 20 km x 20 km; 50 km x 50 km and 100 km x 100 km. Our results show that the differences between models were larger than the effect of the chosen spatial resolution of weather data for the considered years and region. When displaying model results graphically, each model exhibits a characteristic ‘fingerprint’ of simulated yield frequency distributions. These characteristic distributions in response to the inter-annual weather variability were independent of the spatial resolution of weather input data. Using one model (LINTUL-SLIM), we analysed how the aggregation strategy, i.e. aggregating model input versus model output data, influences the simulated yield frequency distribution. Results show that aggregating weather data has a smaller effect on the yield distribution than aggregating simulated yields which causes a deformation of the model fingerprint. We conclude that changes in the spatial resolution of weather input data introduce less uncertainty to the simulations than the use of different crop models but that more evaluation is required for other regions with a higher spatial heterogeneity in weather conditions, and for other input data related to soil and crop management to substantiate our findings. Our results provide further evidence to support other studies stressing the importance of using not just one, but different crop models in climate assessment studies. (C) 2013 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM, ftnotmacsur |
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MA @ admin @ |
Serial |
4598 |
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Cammarano, D.; Rötter, P.; Ewert, F.; Palosuo, T.; Bindi, M.; Kersebaum, K.C.; Olesen, J.E.; Trnka, M.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Angulo, C.; Gaiser, T.; Nendel, C.; Martre, P.; de Wit, A. |
| Title |
Challenges for Agro-Ecosystem Modelling in Climate Change Risk Assessment for major European Crops and Farming systems |
Type |
Conference Article |
| Year |
2013 |
Publication |
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Issue |
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Pages |
555-564 |
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Impacts World 2013, International Conference on Climate Change Effects, Potsdam, Germany, 2013-05-27 to 2013-05-30 |
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MA @ admin @ |
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2765 |
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Nendel, C.; Ewert, F.; Rötter, R.P.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Asseng, S.; Ruane, A.C.; Banse, M.; Tiffin, R.; Brouwer, F.; Sinabell, F.; Scollan, N.; Meijs, J.; Angulo, C.; Antle, J.M.; Baigorria, G.; Basso, B.; Bindi, M.; Boote, K.J.; Gaiser, T.; Janssen, S.; Kersebaum, K.C.; Nelson, G.; Olesen, J.E.; Palosuo, T.; Porter, C.H.; Porter, J.R.; Rivington, M.; Semenov, M.; Stewart, D.; Thorburn, P.; Trnka, M.; van Ittersum, M.K.; Verhagen, J.; Wallach, D.; Winter, J.M. |
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Addressing challenges and uncertainties for, the use of agro-ecosystem models to, assess climate change impact and food security across scales |
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Conference Article |
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2013 |
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CropM |
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Climate Change and Regional Responses Conference, Dresden, 2013-05-27 to 2013-05-27 |
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MA @ admin @ |
Serial |
2679 |
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