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Kersebaum, K. C., Kollas, C., Bindi, M., Palosuo, T., Wu, L., Sharif, B., et al. (2014). Model inter-comparison on crop rotation effects – an intermediate report. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed.
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Lizaso, J. I., Ruiz-Ramos, M., Rodriguez, L., Gabaldon-Leal, C., Oliveira, J. A., Lorite, I. J., et al. (2017). Modeling the response of maize phenology, kernel set, and yield components to heat stress and heat shock with CSM-IXIM. Field Crops Research, 214, 239–252.
Abstract: The available evidence suggests that the current increasing trend in global surface temperatures will continue during this century, which will be accompanied by a greater frequency of extreme events. The IPCC has projected that higher temperatures may outscore the known optimal and maximum temperatures for maize. The purpose of this study was to improve the ability of the maize model CSM-IXIM to simulate crop development, growth, and yield under hot conditions, especially with regards to the impact of above-optimal temperatures around anthesis. Field and greenhouse experiments that were performed over three years (2014-2016) using the same short-season hybrid, PR37N01 (FAO 300), provided the data for this work. Maize was sown at a target population density of 5 plants M-2 on two sowing dates in 2014 and 2015 and on one in 2016 at three locations in Spain (northern, central, and southern Spain) with a well-defined thermal gradient. The same hybrid was also sown in two greenhouse chambers with daytime target temperatures of approximately 25 and above 35 degrees C. During the nighttime, the temperature in both chambers was allowed to equilibrate with the outside temperature. The greenhouse treatments consisted of moving 18 plants at selected phenological stages (V4, V9, anthesis, lag phase, early grain filling) from the cool chamber to the hot chamber over a week and then returning the plants back to the cool chamber. An additional control treatment remained in the cool chamber all season, and in 2015 and 2016, one treatment remained permanently in the hot chamber. Two maize models in the Decision Support System for Agrotechnology Transfer (DSSAT) V4.6 were compared, namely CERES and IXIM. The HUM version included additional components that were previously developed to improve the crop N simulation and to incorporate the anthesis-silking interval (ASI). A new thermal time calculation, a heat stress index, the impact of pollen-sterilizing temperatures, and the explicit simulation of male and female flowering as affected by the daily heat conditions were added to IXIM. The phenology simulation in field experiments by IXIM improved substantially. The RMSE for silking and maturity in CERES were 7.9 and 13.7 days, decreasing in DCIM to 2.8 and 7.3 days, respectively. Similarly, the estimated kernel numbers, kernel weight, grain yield and final biomass were always closer to the measurements in HUM than in CERES. The worst simulations were for kernel weight, and for that reason, the differences in grain yield between the models were small (the RMSE in CERES was 1219 kg ha(-1) vs. 1082 kg ha(-1) in IXIM). The greenhouse results also supported the improved estimations of crop development by IXIM (RMSE of 2.6 days) relative to CERES (7.4 days). The impact of the heat treatments on grain yield was consistently overestimated by CERES, while HUM captured the general trend. The new HUM model improved the CERES simulations when elevated temperatures were included in the evaluation data. Additional model testing with measurements from a wider latitudinal range and relevant heat conditions are required.
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Leolini, L., Moriondo, M., De Cortazar-Atauri, I., Ruiz-Ramos, M., Nendel, C., Roggero, P. P., et al. (2017). Modelling different cropping systems (Vol. 10).
Abstract: Grapevine is a worldwide valuable crop characterized by a high economic importance for the production of high quality wines. However, the impact of climate change on the narrow climate niches in which grapevine is currently cultivated constitute a great risk for future suitability of grapevine. In this context, grape simulation models are considered promising tools for their contribution to investigate plant behavior in different environments. In this study, six models developed for simulating grapevine growth and development were tested by focusing on their performances in simulating main grapevine processes under two calibration levels: minimum and full calibration. This would help to evaluate major limitations/strength points of these models, especially in the view of their application to climate change impact and adaptation assessments. Preliminary results from two models (GrapeModel and STICS) showed contrasting abilities in reproducing the observed data depending on the site, the year and the target variable considered. These results suggest that a limited dataset for model calibration would lead to poor simulation outputs. However, a more complete interpretation and detailed analysis of the results will be provided when considering the other models simulations.
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Hlavinka, P., Olesen, J. E., Kersebaum, K. - C., Trnka, M., Pohankova, E., Stella, T., et al. (2017). Modelling long term effects of cropping and managements systems on soil organic matter, C/N dynamics and crop growth (Vol. 10).
Abstract: While simulation of cropping systems over a few years might reflect well the short term effects of management and cultivation, long term effects on soil properties and their consequences for crop growth and matter fluxes are not captured. Especially the effect on soil carbon sequestration/depletion is addressed by this task. Simulations of an ensemble of crop models are performed as transient runs over a period of 120 year using observed weather from three stations in Czech Republic (1961-2010) and transient long time climate change scenarios (2011-2080) from five GCM of the CMIP5 ensemble to assess the effect of different cropping and management systems on carbon sequestration, matter fluxes and crop production in an integrative way. Two cropping systems are regarded comprising two times winter wheat, silage maize, spring barley and oilseed rape. Crop rotations differ regarding their organic input from crop residues, nitrogen fertilization and implementation of catch crops. Models are applied for two soil types with different water holding capacity. Cultivation and nutrient management is adapted using management rules related to weather and soil conditions. Data of phenology and crop yield from the region of the regarded crops were provided to calibrate the models for crops of the rotations. Twelve models were calibrated in this first step. For the transient long term runs results of four models were submitted so far. Outputs are crop yields, nitrogen uptake, soil water and mineral nitrogen contents, as well as water and nitrogen fluxes to the atmosphere and groundwater. Changes in the carbon stocks and the consequences for nitrogen mineralisation, N fertilization and emissions also considered.
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Gabaldón-Leal, C., Webber, H., Otegui, M. E., Slafer, G. A., Ordonez, R. A., Gaiser, T., et al. (2016). Modelling the impact of heat stress on maize yield formation. Field Crops Research, 198, 226–237.
Abstract: The frequency and intensity of extreme high temperature events are expected to increase with climate change. Higher temperatures near anthesis have a large negative effect on maize (Zea mays, L.) grain yield. While crop growth models are commonly used to assess climate change impacts on maize and other crops, it is only recently that they have accounted for such heat stress effects, despite limited field data availability for model evaluation. There is also increasing awareness but limited testing of the importance of canopy temperature as compared to air temperature for heat stress impact simulations. In this study, four independent irrigated field trials with controlled heating imposed using polyethylene shelters were used to develop and evaluate a heat stress response function in the crop modeling framework SIMPLACE, in which the Lintul5 crop model was combined with a canopy temperature model. A dataset from Argentina with the temperate hybrid Nidera AX 842 MG (RM 119) was used to develop a yield reduction function based on accumulated hourly stress thermal time above a critical temperature of 34 degrees C. A second dataset from Spain with a FAO 700 cultivar was used to evaluate the model with daily weather inputs in two sets of simulations. The first was used to calibrate SIMPLACE for conditions with no heat stress, and the second was used to evaluate SIMPLACE under conditions of heat stress using the reduction factor obtained with the Argentine dataset. Both sets of simulations were conducted twice; with the heat stress function alternatively driven with air and simulated canopy temperature. Grain yield simulated under heat stress conditions improved when canopy temperature was used instead of air temperature (RMSE equal to 175 and 309 g m(-2), respectively). For the irrigated and high radiative conditions, raising the critical threshold temperature for heat stress to 39 degrees C improved yield simulation using air temperature (RMSE: 221 gm(-2)) without the need to simulate canopy temperature (RMSE: 175 gm(-2)). However, this approach of adjusting thresholds is only likely to work in environments where climatic variables and the level of soil water deficit are constant, such as irrigated conditions and are not appropriate for rainfed production conditions. (C) 2016 Elsevier B.V. All rights reserved.
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