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Ebrahimi, E.; Manschadi, A.M.; Neugschwandtner, R.W.; Eitzinger, J.; Thaler, S.; Kaul, H.-P. |
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Title |
Assessing the impact of climate change on crop management in winter wheat – a case study for Eastern Austria |
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Journal Article |
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Year |
2016 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
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Volume |
154 |
Issue |
07 |
Pages |
1153-1170 |
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Abstract |
Climate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice. |
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0021-8596 |
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TradeM |
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MA @ admin @ |
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4723 |
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Eitzinger, J.; Thaler, S.; Schmid, E.; Strauss, F.; Ferrise, R.; Moriondo, M.; Bindi, M.; Palosuo, T.; Rotter, R.; Kersebaum, K.C.; Olesen, J.E.; Patil, R.H.; Saylan, L.; Caldag, B.; Caylak, O. |
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Title |
Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria |
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Journal Article |
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Year |
2013 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
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151 |
Issue |
6 |
Pages |
813-835 |
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Keywords |
simulate yield response; climate-change scenarios; central-europe; nitrogen dynamics; high-temperature; future climate; elevated co2; soil; growth; variability |
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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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0021-8596 |
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CropM |
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MA @ admin @ |
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4601 |
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Gobin, A.; Kersebaum, K.; Eitzinger, J.; Trnka, M.; Hlavinka, P.; Takáč, J.; Kroes, J.; Ventrella, D.; Marta, A.; Deelstra, J.; Lalić, B.; Nejedlik, P.; Orlandini, S.; Peltonen-Sainio, P.; Rajala, A.; Saue, T.; Şaylan, L.; Stričevic, R.; Vučetić, V.; Zoumides, C. |
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Title |
Variability in the Water Footprint of Arable Crop Production across European Regions |
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Journal Article |
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Year |
2017 |
Publication |
Water |
Abbreviated Journal |
Water |
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9 |
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2 |
Pages |
93 |
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Crop growth and yield are affected by water use during the season: the green water footprint (WF) accounts for rain water, the blue WF for irrigation and the grey WF for diluting agri-chemicals. We calibrated crop yield for FAO’s water balance model “Aquacrop” at field level. We collected weather, soil and crop inputs for 45 locations for the period 1992–2012. Calibrated model runs were conducted for wheat, barley, grain maize, oilseed rape, potato and sugar beet. The WF of cereals could be up to 20 times larger than the WF of tuber and root crops; the largest share was attributed to the green WF. The green and blue WF compared favourably with global benchmark values (R² = 0.64–0.80; d = 0.91–0.95). The variability in the WF of arable crops across different regions in Europe is mainly due to variability in crop yield (c̅v̅ = 45%) and to a lesser extent to variability in crop water use (c̅v̅ = 21%). The WF variability between countries (c̅v̅ = 14%) is lower than the variability between seasons (c̅v̅ = 22%) and between crops (c̅v̅ = 46%). Though modelled yields increased up to 50% under sprinkler irrigation, the water footprint still increased between 1% and 25%. Confronted with drainage and runoff, the grey WF tended to overestimate the contribution of nitrogen to the surface and groundwater. The results showed that the water footprint provides a measurable indicator that may support European water governance. |
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2073-4441 |
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CropM, ft_macsur |
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MA @ admin @ |
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4988 |
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Kersebaum, C.; Kollas, C.; Bindi, M.; Nendel, C.; Ferrise, R.; Moriondo, M.; Olesen, J.E.; Sharif, B.; Öztürk, I.; Hoffmann, H.; Launay, M.; Ripoche, D.; Ruget, F.; Bertuzzi, P.; Cortazar, I.G.D.; Beaudoin, N.; Armas-Herrera, C.; Mary, B.; Müller, C.; Waha, K.; Ventrella, D.; Palosuo, T.; Rötter, R.; Trnka, M.; Hlavinka, P.; Wu, L.; Wegehenkel, M.; Mirschel, W.; Conradt, T.; Wechsung, F.; Weigel, H.-J.; Manderscheid, R.; Eitzinger, J. |
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Title |
Modelling complex crop rotations and management across sites in Europe with an ensemble of models |
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Conference Article |
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Year |
2014 |
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CropM |
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ASA-CSSA-SSSA Int. Annual Meeting, Long Beach, CA, 2-5 November 2014, 2014-11-02 to 2014-11-05 |
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MA @ admin @ |
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2526 |
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Kersebaum, K.; Kroes, J.; Gobin, A.; Takáč, J.; Hlavinka, P.; Trnka, M.; Ventrella, D.; Giglio, L.; Ferrise, R.; Moriondo, M.; Dalla Marta, A.; Luo, Q.; Eitzinger, J.; Mirschel, W.; Weigel, H.-J.; Manderscheid, R.; Hoffmann, M.; Nejedlik, P.; Iqbal, M.; Hösch, J. |
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Title |
Assessing uncertainties of water footprints using an ensemble of crop growth models on winter wheat |
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Journal Article |
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Year |
2016 |
Publication |
Water |
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Water |
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8 |
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12 |
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571 |
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Crop productivity and water consumption form the basis to calculate the water footprint (WF) of a specific crop. Under current climate conditions, calculated evapotranspiration is related to observed crop yields to calculate WF. The assessment of WF under future climate conditions requires the simulation of crop yields adding further uncertainty. To assess the uncertainty of model based assessments of WF, an ensemble of crop models was applied to data from five field experiments across Europe. Only limited data were provided for a rough calibration, which corresponds to a typical situation for regional assessments, where data availability is limited. Up to eight models were applied for wheat. The coefficient of variation for the simulated actual evapotranspiration between models was in the range of 13%–19%, which was higher than the inter-annual variability. Simulated yields showed a higher variability between models in the range of 17%–39%. Models responded differently to elevated CO2 in a FACE (Free-Air Carbon Dioxide Enrichment) experiment, especially regarding the reduction of water consumption. The variability of calculated WF between models was in the range of 15%–49%. Yield predictions contributed more to this variance than the estimation of water consumption. Transpiration accounts on average for 51%–68% of the total actual evapotranspiration. |
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2073-4441 |
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CropM, ft_macsur |
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MA @ admin @ |
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4987 |
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