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Effects of Bias-Corrected Regional Climate Projections and Their Spatial Resolutions on Crop Model Results under Different Climatic and Soil Conditions in Austria

Author

Listed:
  • Sabina Thaler

    (Institute of Meteorology and Climatology, University of Natural Resources and Life Sciences (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
    CzechGlobe—Global Change Research Institute CAS, Belidla 986/4a, 603 00 Brno, Czech Republic)

  • Herbert Formayer

    (Institute of Meteorology and Climatology, University of Natural Resources and Life Sciences (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria)

  • Gerhard Kubu

    (Institute of Meteorology and Climatology, University of Natural Resources and Life Sciences (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria)

  • Miroslav Trnka

    (CzechGlobe—Global Change Research Institute CAS, Belidla 986/4a, 603 00 Brno, Czech Republic
    Institute of Agrosystems and Bioclimatology, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic)

  • Josef Eitzinger

    (Institute of Meteorology and Climatology, University of Natural Resources and Life Sciences (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria)

Abstract

The quality, reliability, and uncertainty of Austrian climate projections (ÖKS15) and their impacts on the results of the crop model DSSAT for three different orographic and climatic agricultural regions in Austria were analyzed. Cultivar-specific grain yields of winter wheat, spring barley, and maize were simulated for different soil classes to address three main objectives. First, the uncertainties of simulated crop yields related to the ÖKS15 projections were analyzed under current climate conditions. The climate projections revealed that the case study regions with higher humidity levels generally had lower yield deviations than the drier regions (yield deviations from −19% to +15%). Regarding the simulated crop types, spring barley was found to be less sensitive to the climate projections than rainfed maize, and the response was greater in regions with a low soil water storage capacity. The second objective was to simulate crop yields for the same cultivars using future climate projections. Winter wheat and spring barley tended to show increased yields by the end of the century due to an assumed CO 2 -fertilization effect in the range of 3–23%, especially under RCP 8.5. However, rainfed and irrigated maize were associated with up to 17% yield reductions in all three study regions due to a shortened growth period caused by warming. The third objective addressed the effects of crop model weather input data with different spatial resolutions (1 vs. 5, 11, and 21 km) on simulated crop yields using the climate projections. Irrigated grain maize and rainfed spring barley had the lowest simulated yield deviations between the spatial scales applied due to their better water supply conditions. The ranges of uncertainty revealed by the different analyses suggest that impact models should be tested with site representative conditions before being applied to develop site-specific adaptation options for Austrian crop production.

Suggested Citation

  • Sabina Thaler & Herbert Formayer & Gerhard Kubu & Miroslav Trnka & Josef Eitzinger, 2021. "Effects of Bias-Corrected Regional Climate Projections and Their Spatial Resolutions on Crop Model Results under Different Climatic and Soil Conditions in Austria," Agriculture, MDPI, vol. 11(11), pages 1-39, October.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:11:p:1029-:d:661120
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    References listed on IDEAS

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    1. Pascalle Smith & Georg Heinrich & Martin Suklitsch & Andreas Gobiet & Markus Stoffel & Jürg Fuhrer, 2014. "Station-scale bias correction and uncertainty analysis for the estimation of irrigation water requirements in the Swiss Rhone catchment under climate change," Climatic Change, Springer, vol. 127(3), pages 521-534, December.
    2. Samuel S. Myers & Antonella Zanobetti & Itai Kloog & Peter Huybers & Andrew D. B. Leakey & Arnold J. Bloom & Eli Carlisle & Lee H. Dietterich & Glenn Fitzgerald & Toshihiro Hasegawa & N. Michele Holbr, 2014. "Increasing CO2 threatens human nutrition," Nature, Nature, vol. 510(7503), pages 139-142, June.
    3. Schönhart, Martin & Mitter, Hermine & Schmid, Erwin & Heinrich, Georg & Gobiet, Andreas, 2014. "Integrated Analysis of Climate Change Impacts and Adaptation Measures in Austrian Agriculture," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 63(03), pages 1-21, September.
    4. Miroslav Trnka & Reimund P. Rötter & Margarita Ruiz-Ramos & Kurt Christian Kersebaum & Jørgen E. Olesen & Zdeněk Žalud & Mikhail A. Semenov, 2014. "Adverse weather conditions for European wheat production will become more frequent with climate change," Nature Climate Change, Nature, vol. 4(7), pages 637-643, July.
    5. Schönhart, Martin & Mitter, Hermine & Schmid, Erwin & Heinrich, Georg & Gobiet, Andreas, 2014. "Integrated Analysis of Climate Change Impacts and Adaptation Measures in Austrian Agriculture," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(3).
    6. Lobell, David B. & Ortiz-Monasterio, J. Ivan & Falcon, Walter P., 2007. "Yield uncertainty at the field scale evaluated with multi-year satellite data," Agricultural Systems, Elsevier, vol. 92(1-3), pages 76-90, January.
    7. A. J. Challinor & J. Watson & D. B. Lobell & S. M. Howden & D. R. Smith & N. Chhetri, 2014. "A meta-analysis of crop yield under climate change and adaptation," Nature Climate Change, Nature, vol. 4(4), pages 287-291, April.
    8. Uddameri, Venkatesh & Ghaseminejad, Ali & Hernandez, E. Annette, 2020. "A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels," Agricultural Water Management, Elsevier, vol. 238(C).
    9. Richard H. Moss & Jae A. Edmonds & Kathy A. Hibbard & Martin R. Manning & Steven K. Rose & Detlef P. van Vuuren & Timothy R. Carter & Seita Emori & Mikiko Kainuma & Tom Kram & Gerald A. Meehl & John F, 2010. "The next generation of scenarios for climate change research and assessment," Nature, Nature, vol. 463(7282), pages 747-756, February.
    10. Franziska Strauss & Erwin Schmid & Elena Moltchanova & Herbert Formayer & Xiuying Wang, 2012. "Modeling climate change and biophysical impacts of crop production in the Austrian Marchfeld Region," Climatic Change, Springer, vol. 111(3), pages 641-664, April.
    11. Daniel Wallach & Linda O. Mearns & Alex C. Ruane & Reimund P. Rötter & Senthold Asseng, 2016. "Lessons from climate modeling on the design and use of ensembles for crop modeling," Climatic Change, Springer, vol. 139(3), pages 551-564, December.
    12. Detlef Vuuren & Jae Edmonds & Mikiko Kainuma & Keywan Riahi & Allison Thomson & Kathy Hibbard & George Hurtt & Tom Kram & Volker Krey & Jean-Francois Lamarque & Toshihiko Masui & Malte Meinshausen & N, 2011. "The representative concentration pathways: an overview," Climatic Change, Springer, vol. 109(1), pages 5-31, November.
    13. Manderscheid, Remy & Dier, Markus & Erbs, Martin & Sickora, Jan & Weigel, Hans-Joachim, 2018. "Nitrogen supply – A determinant in water use efficiency of winter wheat grown under free air CO2 enrichment," Agricultural Water Management, Elsevier, vol. 210(C), pages 70-77.
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