IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v134y2016i1p327-339.html
   My bibliography  Save this article

Predicting potential epidemics of rice diseases in Korea using multi-model ensembles for assessment of climate change impacts with uncertainty information

Author

Listed:
  • Kwang-Hyung Kim
  • Jaepil Cho

Abstract

It is highly anticipated that meteorological changes resulting from global climate change will affect the pattern of rice disease epidemics worldwide. Here, we evaluated the potential impacts of climate change on two representative rice diseases, leaf blast and sheath blight, in Korea. This study involves analyses of disease simulation using an epidemiological model, EPIRICE, which was validated for Korean rice paddy fields. The goal of our study was to assess likely changes in national disease probabilities using individual climate scenarios across different models and multi-model ensemble scenarios constructed by running 11 global climate models. In this way, the results from this study emphasize the uncertainties in climate change scenarios resulting from the variations in initial conditions as well as the structural differences in the global climate models. Observed and simulated epidemics for both diseases were compared using the area under the disease progress curve from EPIRICE model runs. Overall, the simulated incidence of epidemics for both diseases gradually decreased towards 2100 both from individual global climate models and multi-model ensembles. It was noted that while each individual model resulted in different magnitudes of impact, the multi-model ensemble gave the most reliable result that accounts for uncertainty compared to the individual models. In conclusion, we found that in modeling climate impacts on rice diseases, ensembles account for uncertainty better than individual climate models and can lead to better decision making. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • Kwang-Hyung Kim & Jaepil Cho, 2016. "Predicting potential epidemics of rice diseases in Korea using multi-model ensembles for assessment of climate change impacts with uncertainty information," Climatic Change, Springer, vol. 134(1), pages 327-339, January.
  • Handle: RePEc:spr:climat:v:134:y:2016:i:1:p:327-339
    DOI: 10.1007/s10584-015-1503-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10584-015-1503-2
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10584-015-1503-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Teng, P. S. & Savary, S., 1992. "Implementing the systems approach in pest management," Agricultural Systems, Elsevier, vol. 40(1-3), pages 237-264.
    2. James M. Murphy & David M. H. Sexton & David N. Barnett & Gareth S. Jones & Mark J. Webb & Matthew Collins & David A. Stainforth, 2004. "Quantification of modelling uncertainties in a large ensemble of climate change simulations," Nature, Nature, vol. 430(7001), pages 768-772, August.
    3. Luo, Y. & Teng, P. S. & Fabellar, N. G. & TeBeest, D. O., 1997. "A rice-leaf blast combined model for simulation of epidemics and yield loss," Agricultural Systems, Elsevier, vol. 53(1), pages 27-39, January.
    4. Matthews, R. B. & Kropff, M. J. & Horie, T. & Bachelet, D., 1997. "Simulating the impact of climate change on rice production in Asia and evaluating options for adaptation," Agricultural Systems, Elsevier, vol. 54(3), pages 399-425, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kyoung-Tae Lee & Hye-Won Jeon & Sook-Young Park & Jaepil Cho & Kwang-Hyung Kim, 2022. "Comparison of projected rice blast epidemics in the Korean Peninsula between the CMIP5 and CMIP6 scenarios," Climatic Change, Springer, vol. 173(1), pages 1-20, July.
    2. Wang, Hui & Mongiano, Gabriele & Fanchini, Davide & Titone, Patrizia & Tamborini, Luigi & Bregaglio, Simone, 2021. "Varietal susceptibility overcomes climate change effects on the future trends of rice blast disease in Northern Italy," Agricultural Systems, Elsevier, vol. 193(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ren, Jinfu & Liu, Yang & Liu, Jiming, 2023. "Chaotic behavior learning via information tracking," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    2. Gupta, Rishabh & Mishra, Ashok, 2019. "Climate change induced impact and uncertainty of rice yield of agro-ecological zones of India," Agricultural Systems, Elsevier, vol. 173(C), pages 1-11.
    3. Lingcheng Li & Liping Zhang & Jun Xia & Christopher Gippel & Renchao Wang & Sidong Zeng, 2015. "Implications of Modelled Climate and Land Cover Changes on Runoff in the Middle Route of the South to North Water Transfer Project in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2563-2579, June.
    4. Getachew Tegegne & Assefa M. Melesse, 2020. "Multimodel Ensemble Projection of Hydro-climatic Extremes for Climate Change Impact Assessment on Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 3019-3035, July.
    5. Hu, Xinyu & Zhao, Jinfeng & Sun, Shikun & Jia, Chengru & Zhang, Fuyao & Ma, Yizhe & Wang, Kaixuan & Wang, Yubao, 2023. "Evaluation of the temporal reconstruction methods for MODIS-based continuous daily actual evapotranspiration estimation," Agricultural Water Management, Elsevier, vol. 275(C).
    6. Stephens, William & Hess, Tim, 1999. "Systems approaches to water management research," Agricultural Water Management, Elsevier, vol. 40(1), pages 3-13, March.
    7. Gillian Rose & Tom Osborne & Helen Greatrex & Tim Wheeler, 2016. "Impact of progressive global warming on the global-scale yield of maize and soybean," Climatic Change, Springer, vol. 134(3), pages 417-428, February.
    8. A. Lopez & E. Suckling & F. Otto & A. Lorenz & D. Rowlands & M. Allen, 2015. "Towards a typology for constrained climate model forecasts," Climatic Change, Springer, vol. 132(1), pages 15-29, September.
    9. Andrew J. Wiltshire & Gillian Kay & Jemma L. Gornall & Richard A. Betts, 2013. "The Impact of Climate, CO 2 and Population on Regional Food and Water Resources in the 2050s," Sustainability, MDPI, vol. 5(5), pages 1-23, May.
    10. Johannes Emmerling, 2018. "Sharing Of Climate Risks Across World Regions," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-19, August.
    11. Lopes, Francis M. & Conceição, Ricardo & Silva, Hugo G. & Salgado, Rui & Collares-Pereira, Manuel, 2021. "Improved ECMWF forecasts of direct normal irradiance: A tool for better operational strategies in concentrating solar power plants," Renewable Energy, Elsevier, vol. 163(C), pages 755-771.
    12. Jürgen Scheffran, 2008. "Adaptive management of energy transitions in long-term climate change," Computational Management Science, Springer, vol. 5(3), pages 259-286, May.
    13. Rick Baker & Andrew Barker & Alan Johnston & Michael Kohlhaas, 2008. "The Stern Review: an assessment of its methodology," Staff Working Papers 0801, Productivity Commission, Government of Australia.
    14. Lee, Jaehyuk & Nadolnyak, Denis A. & Hartarska, Valentina M., 2012. "Impact of Climate Change on Agricultural Production in Asian Countries: Evidence from Panel Study," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119808, Southern Agricultural Economics Association.
    15. Timothy Osborn & Craig Wallace & Ian Harris & Thomas Melvin, 2016. "Pattern scaling using ClimGen: monthly-resolution future climate scenarios including changes in the variability of precipitation," Climatic Change, Springer, vol. 134(3), pages 353-369, February.
    16. Zhang, Bingquan & Xu, Jialu & Lin, Zhixian & Lin, Tao & Faaij, André P.C., 2021. "Spatially explicit analyses of sustainable agricultural residue potential for bioenergy in China under various soil and land management scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    17. H. Hanlon & G. Hegerl & S. Tett & D. Smith, 2015. "Near-term prediction of impact-relevant extreme temperature indices," Climatic Change, Springer, vol. 132(1), pages 61-76, September.
    18. Kropff, M. J. & Teng, P. S. & Rabbinge, R., 1995. "The challenge of linking pest and crop models," Agricultural Systems, Elsevier, vol. 49(4), pages 413-434.
    19. Y. Ghile & M. Taner & C. Brown & J. Grijsen & Amal Talbi, 2014. "Bottom-up climate risk assessment of infrastructure investment in the Niger River Basin," Climatic Change, Springer, vol. 122(1), pages 97-110, January.
    20. Behnam Ababaei, 2014. "Are Weather Generators Robust Tools to Study Daily Reference Evapotranspiration and Irrigation Requirement?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 915-932, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:climat:v:134:y:2016:i:1:p:327-339. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.