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Olesen, J. E., Sharif, B., Plauborg, F., Yin, X., Bindi, M., Doro, L., et al. (2016). Comparison of wheat models and their sensitivity towards tillage and N fertilization with different calibration approaches.. Berlin (Germany).
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Yin, X. G., Olesen, J. E., Wang, M., Öztürk, I., & Chen, F. (2016). Climate effects on crop yields in the Northeast Farming Region of China during 1961–2010. J. Agric. Sci., 154(07), 1190–1208.
Abstract: Crop production in the Northeast Farming Region of China (NFR) is affected considerably by variation in climatic conditions. Data on crop yield and weather conditions from a number of agro-meteorological stations in NFR were used in a mixed linear model to evaluate the impacts of climatic variables on the yield of maize (Zea mays L.), rice (Oryza sativa L.), soybean (Glycine max L. Merr.) and spring wheat (Triticum aestivum L.) in different crop growth phases. The crop growing season was divided into three growth phases based on the average crop phenological dates from records covering 1981 and 2010 at each station, comprising pre-flowering (from sowing to just prior to flowering), flowering (20 days around flowering) and post-flowering (10 days after flowering to maturity). The climatic variables were mean minimum temperature, thermal time (which is used to indicate changes in the length of growth cycles), average daily solar radiation, accumulated precipitation, aridity index (which is used to assess drought stress) and heat degree-days index (HDD) (which is used to indicate heat stress) were calculated for each growth phase and year. Over the 1961–2010 period, the minimum temperature increased significantly in each crop growth phase, the thermal time increased significantly in the pre-flowering phase of each crop and in the post-flowering phases of maize, rice and soybean, and HDD increased significantly in the pre-flowering phase of soybean and wheat. Average solar radiation decreased significantly in the pre-flowering phase of all four crops and in the flowering phase of soybean and wheat. Precipitation increased during the pre-flowering phase leading to less aridity, whereas reduced precipitation in the flowering and post-flowering phases enhanced aridity. Statistical analyses indicated that higher minimum temperature was beneficial for maize, rice and soybean yields, whereas increased temperature reduced wheat yield. Higher solar radiation in the pre-flowering phase was beneficial for maize yield, in the post-flowering phase for wheat yield, whereas higher solar radiation in the flowering phase reduced rice yield. Increased aridity in the pre-flowering and flowering phases severely reduced maize yield, higher aridity in the flowering and post-flowering phases reduced rice yield, and aridity in all growth phases reduced soybean and wheat yields. Higher HDD in all growth phases reduced maize and soybean yield and HDD in the pre-flowering phase reduced rice yield. Such effects suggest that projected future climate change may have marked effects on crop yield through effects of several climatic variables, calling for adaptation measures such as breeding and changes in crop, soil and agricultural water management.
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Yin, X. G., Jabloun, M., Olesen, J. E., Özturk, I., Wang, M., & Chen, F. (2016). Effects of climatic factors, drought risk and irrigation requirement on maize yield in the Northeast Farming Region of China. J. Agric. Sci., 154(7), 1171–1189.
Abstract: Drought risk is considered to be among the main limiting factors for maize (Zea mays L.) production in the Northeast Farming Region of China (NFR). Maize yield data from 44 stations over the period 1961-2010 were combined with data from weather stations to evaluate the effects of climatic factors, drought risk and irrigation requirement on rain-fed maize yield in specific maize growth phases. The maize growing season was divided into four growth phases comprising seeding, vegetative, flowering and maturity based on observations of phenological data from 1981 to 2010. The dual crop coefficient was used to calculate crop evapotranspiration and soil water balance during the maize growing season. The effects of mean temperature, solar radiation, effective rainfall, water deficit, drought stress days, actual crop evapotranspiration and irrigation requirement in different growth phases were included in the statistical model to predict maize yield. During the period 1961-2010, mean temperature increased significantly in all growth phases in NFR, while solar radiation decreased significantly in southern NFR in the seeding, vegetative and flowering phases. Effective rainfall increased in the seeding and vegetative phases, reducing water deficit over the period, whereas decreasing effective rainfall over time in the flowering and maturity phases enhanced water deficit. An increase in days with drought stress was concentrated in western NFR, with larger volumes of irrigation needed to compensate for increased dryness. The present results indicate that higher mean temperature in the seeding and maturity phases was beneficial for maize yield, whereas excessive rainfall would damage maize yield, in particular in the seeding and flowering phases. Drought stress in any growth stage was found to reduce maize yield and water deficit was slightly better than other indicators of drought stress for explaining yield variability. The effect of drought stress was particularly strong in the seeding and flowering phases, indicating that these periods should be given priority for irrigation. The yield-reducing effects of both drought and intense rainfall illustrate the importance of further development of irrigation and drainage systems for ensuring the stability of maize production in NFR.
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Refsgaard, J. C., Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T. A., Drews, M., et al. (2014). A framework for testing the ability of models to project climate change and its impacts. Clim. Change, 122(1-2), 271–282.
Abstract: Models used for climate change impact projections are typically not tested for simulation beyond current climate conditions. Since we have no data truly reflecting future conditions, a key challenge in this respect is to rigorously test models using proxies of future conditions. This paper presents a validation framework and guiding principles applicable across earth science disciplines for testing the capability of models to project future climate change and its impacts. Model test schemes comprising split-sample tests, differential split-sample tests and proxy site tests are discussed in relation to their application for projections by use of single models, ensemble modelling and space-time-substitution and in relation to use of different data from historical time series, paleo data and controlled experiments. We recommend that differential-split sample tests should be performed with best available proxy data in order to build further confidence in model projections.
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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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