Eitzinger, J., Thaler, S., Schmid, E., Strauss, F., Ferrise, R., Moriondo, M., et al. (2013). Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria. J. Agric. Sci., 151(6), 813–835.
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.
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Asseng, S., Ewert, F., Martre, P., Rötter, R. P., Lobell, D. B., Cammarano, D., et al. (2014). Rising temperatures reduce global wheat production. Nat. Clim. Change, 5(2), 143–147.
Abstract: Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.
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Kersebaum, K., & C,. (2014). Results of uncalibrated model runs available (ROTATIONEFFECTS) (Vol. 3).
Abstract: The study ROTATIONEFFECT aims to compare the output of different models simulating field data sets with multi-year crop rotations including different treatments. Data sets for 5 locations in Europe were distributed to 19 interested modeller groups comprising a total of 201 crop growth seasons. In a first step only minimal information for calibration were provided to the modellers. In total 14 modelling teams sent their “uncalibrated” results as single-year calculations and/or calculations of rotation depending on the capability of the model. 7-10 models were capable to run the rotations as continuous runs. Up to 12 models provided single year simulations of at least one crop. Comparing results of models which provided both single year and continuous runs, show a little lower root mean square error for the continuous rotations runs. Cereal crop yields were generally better simulated than tuber/beet yields. Additionally, the models’ response to various treatments (irrigation/rainfed, nitrogen level, CO2 level, residue management/ tillage, catch crops) were compared to observed differences. First indicators of model performance have been developed and presented at international conferences. No Label
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Haas, E., R. Kiese, Klatt, S., Hoffmann, H., Zhao, G., Ewert, F., et al. (2016). Responses of soil nitrous oxide emissions and nitrate leaching on climate, soil and management input data aggregation: a biogeochemistry model ensemble study.. Berlin (Germany).
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Klatt, S., Haas, E., Hoffmann, H., Zhao, G., Van Bussel, L. G. J., Enders, A., et al. (2014). Responses of soil N2O emissions and nitrate leaching on climate input data aggregation: a biogeochemistry model ensemble study. CropM International Symposium and Workshop.
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