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Pohanková, E., Hlavinka, P., Kersebaum, K. C., Dubrovský, M., Fischer, M., Balek, J., et al. (2015). Pilot study: Field crop rotations modeling under present and future conditions in the Czech Republic using HERMES model (Vol. 5).
Abstract: The aim of this study is to compare the water and organic material balance, yields and other aspects estimated within crop rotations by the Hermes crop model for present and future climatic conditions in the Czech Republic. Moreover, this is a pilot study for the complex and continuous crop rotations modeling (using both single crop models and ensembles) in connection with transient climate change scenarios. For this purpose, three locations representing important agricultural regions of the Czech Republic (with different climatic conditions) were selected. The crop rotation (including spring barley, silage maize, winter wheat, winter rape, and winter wheat in the listed order) was simulated from 1981-2080. The period 1981-2010 was covered by measured meteorological data, and the period 2011-2080 was represented by a transient synthetic weather series from the weather generator M&Rfi. The generated data was based on five circulation models representing an ensemble of 18 CMIP3 global circulation models to preserve to a large degree the uncertainty of the original ensemble. Two types of crop management were compared, and the influences of soil quality, increasing atmospheric CO2 and magnitude of adaptation measure (in the form of sowing date changes) were also considered. According to the results, if a “dry” scenario (such as GFCM21) would occur, then all the C3 crops produced in drier regions would be devastated in a significant number of seasons; for example, by the 2070s, up to 19.5%, 21.5% and 47.0% of seasons with winter rape, spring barley and winter wheat, respectively, would have a yield level below 50% of the present yield. Negative impacts are likely even on premium-quality soils regardless of the use of a flexible sowing date and accounting for increasing CO2 concentrations. Moreover, in some cases, the use of catch crops can have negative impacts, exacerbating the soil water deficit for the subsequent crops. This study (submitted to Climate Research journal) will be used as a pilot for subsequent activities. In this area, following calculations (the same set of stations and updated climate scenarios) using growth models ensemble (currently includes 12 modeling approaches) started to estimate uncertainty aspects. Consequently, the analysis within wider range of conditions (across continents) and farming methods will be conducted. No Label
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Yin, X. G., Kersebaum, K. C., Kollas, C., Manevski, K., Baby, S., Beaudoin, N., et al. (2017). Performance of process-based models for simulation of grain N in crop rotations across Europe. Agric. Syst., 154, 63–77.
Abstract: The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. Generally, the results showed that the accuracy of the simulations in predicting grain N increased under detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordewn vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena saliva L.), winter rye (Secale cereale L.), pea (Piswn sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism.
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Trnka, M., Hlavinka, P., Wimmerová, M., Pohanková, E., Rötter, R., Olesen, J. E., et al. (2017). Paper on model responses to selected adverse weather conditions (Vol. 10).
Abstract: Based on the Trnka et al. (2015) study that indicated that heat and drought will be the most important stress factors for most of the European what area the further effort focused on these two extremes. The crop model HERMES has been tested for its ability to replicate correctly drought stress, heat stress and combination of both stresses. While data on the drought stress were available for both field and growth chambers, heat stress and its combination with heat stress was available only for the growth chambers. The modified version of the HERMES crop model was developed by Dr. Kersebaum and is being currently prepared for the journal paper publication.
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Rötter, R. P., Höhn, J., Trnka, M., Fronzek, S., Carter, T. R., & Kahiluoto, H. (2013). Modelling shifts in agroclimate and crop cultivar response under climate change. Ecol. Evol., 3(12), 4197–4214.
Abstract: THIS PAPER AIMS: (i) to identify at national scale areas where crop yield formation is currently most prone to climate-induced stresses, (ii) to evaluate how the severity of these stresses is likely to develop in time and space, and (iii) to appraise and quantify the performance of two strategies for adapting crop cultivation to a wide range of (uncertain) climate change projections. To this end we made use of extensive climate, crop, and soil data, and of two modelling tools: N-AgriCLIM and the WOFOST crop simulation model. N-AgriCLIM was developed for the automatic generation of indicators describing basic agroclimatic conditions and was applied over the whole of Finland. WOFOST was used to simulate detailed crop responses at four representative locations. N-AgriCLIM calculations have been performed nationally for 3829 grid boxes at a 10 × 10 km resolution and for 32 climate scenarios. Ranges of projected shifts in indicator values for heat, drought and other crop-relevant stresses across the scenarios vary widely – so do the spatial patterns of change. Overall, under reference climate the most risk-prone areas for spring cereals are found in south-west Finland, shifting to south-east Finland towards the end of this century. Conditions for grass are likely to improve. WOFOST simulation results suggest that CO2 fertilization and adjusted sowing combined can lead to small yield increases of current barley cultivars under most climate scenarios on favourable soils, but not under extreme climate scenarios and poor soils. This information can be valuable for appraising alternative adaptation strategies. It facilitates the identification of regions in which climatic changes might be rapid or otherwise notable for crop production, requiring a more detailed evaluation of adaptation measures. The results also suggest that utilizing the diversity of cultivar responses seems beneficial given the high uncertainty in climate change projections.
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Hlavinka, P., Trnka, M., Kersebaum, K. C., Cermák, P., Pohanková, E., Orság, M., et al. (2014). Modelling of yields and soil nitrogen dynamics for crop rotations by HERMES under different climate and soil conditions in the Czech Republic. J. Agric. Sci., 152(02), 188–204.
Abstract: The crop growth model HERMES was used to model crop rotation cycles at 12 experimental sites in the Czech Republic. A wide range of crops (spring and winter barley, winter wheat, maize, potatoes, sugar beet, winter rape, oats, alfalfa and grass), cultivated between 1981 and 2009 under various soil and climatic conditions, were included. The model was able to estimate the yields of field crop rotations at a reasonable level, with an index of agreement (IA) ranging from 0.82 to 0.96 for the calibration database (the median coefficient of determination (R-2) was 0.71), while IA for verification varied from 0.62 to 0.93 (median R-2 was 0.78). Grass yields were also estimated at a reasonable level of accuracy. The estimates were less accurate for the above-ground biomass at harvest (the medians for IA were 0.76 and 0.72 for calibration and verification, respectively, and analogous medians of R-2 were 0.50 and 0.49). The soil mineral nitrogen (N) content under the field crops was simulated with good precision, with the IA ranging from 0.49 to 0.74 for calibration and from 0.43 to 0.68 for verification. Generally, the soil mineral N was underestimated, and more accurate results were achieved at locations with intensive fertilization. Simulated yields, soil N, water and organic carbon (C) contents were compared with long-term field measurements at Ne. mc. ice, located within the fertile Moravian lowland. At this station, all of the observed parameters were reproduced with a reasonable level of accuracy. In the case of the organic C content, HERMES reproduced a decrease ranging from c. 85 to 77 tonnes (t)/ha (for the 0-0.3 m soil layer) between the years 1980 and 2007. In spite of its relatively simple approach and restricted input data, HERMES was proven to be robust across various conditions, which is a precondition for its future use for both theoretical and practical purposes.
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