Evaluation of Site-specific Potential for Rice Production in Korea under the Changing Climate

지구온난화에 따른 우리나라 벼농사지대의 생산성 재평가

  • Chung, U-Ran (Department of Plant Science, Seoul National University) ;
  • Cho, Kyung-Sook (Climate Prediction Division, Korea Meteorological Administration) ;
  • Lee, Byun-Woo (Department of Plant Science, Seoul National University)
  • 정유란 (서울대학교 식물생산과학부) ;
  • 조경숙 (기상청 기후예측과) ;
  • 이변우 (서울대학교 식물생산과학부)
  • Published : 2006.12.30

Abstract

Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.

본 연구에서는 실측 일기상자료 대신 예측 기후평년 값을 적용하여 기후변화와 그에 상응한 벼 작황의 지리적 분포양상을 복원함으로써 지구온난화에 따른 우리나라 벼농사지대의 생산성을 재평가하였다. 기상청 56개 지점 종관자료(일 최고/최저 기온의 월별 평균값)를 1971-2000년 30년 단위로 수집하여 270m 해상도의 수치기후도를 작성하고, 벼논픽셀에 해당되는 기후자료를 추출하였다. 동일한 시군에 속하는 벼논픽셀의 기후자료를 평균함으로써 시군단위의 '벼논맞춤형 기후자료'를 준비하였다. 같은 방법으로 기상연구소에서 제작한 2011-2100년 기간의 3개 평년(2011-2040, 2041-2070, 2071-2100) 기후시나리오에 근거하여 해당 평년의 기후자료를 추정하였다. 농촌진흥청의 정밀토양도로부터 해당 픽셀의 토성과 토심정보를 검색하고 이를 토대로 유효수분 조견표에 의해 토양자료를 준비하였다. 자포니카형 벼의 특성을 갖도록 개조한 벼 생육모형(CERES-Japonica)에 이들 자료를 입력하고 조생종(오대벼), 중생종 (화성벼), 만생종 (동진벼)의 생육을 모의하였다. 시군 공간평균을 기준으로 3품종 모두 가까운 미래(2011-2040년)에는 출수기가 일주일 정도 빨라지고, 먼 미래(2071-2100년)에는 최대 20일 까지 단축될 수 있다. 생리적 성숙기는 3품종 모두 가까운 미래(2011-2040년)에는 15일 정도 단축되고, 먼 미래(2071-2100년)에는 최대 한달까지도 빨라질 수 있어 출수기에 비해 단축정도가 심하다. 평야지 수량의 경우 조생종인 오대벼는 10a당 6-25%, 중생종 화성벼는 3-26%, 만생종 동진벼는 3-25%까지 감소하였다. 하지만 산간지역에서는 발육속도가 빨라지고 수량이 증가하거나 큰 변화가 없는 곳도 많아 온난화조건에서도 지역별 정밀기후 추정과 이에 근거한 최적품종의 선택, 이앙기 및 수확기 등 생육기간의 조절이 온난화 대응기술로서 유효할 것으로 기대된다.

Keywords

References

  1. Bum, Y., K. J. Lee, and B. W. Lee, 2006: Comparison of traits related to dry matter production and grain yield among rice cultivars released in different years. Korean Journal of Agricultural and Forest Meteorology 8(3), 183-189
  2. Chipanshi, A. C., R. Chanda, and O. Totolo, 2003: Vulnerability assessment of the maize and sorghum crops to climate changes in Botswana. Climatic Change 61(3), 339-360 https://doi.org/10.1023/B:CLIM.0000004551.55871.eb
  3. Choi, J. Y., U. Chung, and J. I. Yun, 2003: Urban-effect correction to improve accuracy of spatially interpolated temperature estimates in Korea. Journal of Applied Meteorology 42(12), 1711-1719 https://doi.org/10.1175/1520-0450(2003)042<1711:UCTIAO>2.0.CO;2
  4. Cui, R. X., M. H. Kim, J. H. Kim, H. S. Nam, and B. W. Lee, 2002: Determination of critical nitrogen concentration and dilution Curve for rice growth. Korean Journal of Crop Science 47(2), 127-131
  5. Chung, U., J. Y. Choi, and J. I. Yun, 2004: Urbanization effect on the observed change in mean monthly temperatures between 1951-1980 and 1971-2000 in Korea. Climatic Change 66, 127-136 https://doi.org/10.1023/B:CLIM.0000043136.58100.ce
  6. Dodson, R., and D. Marks, 1997: Daily temperature interpolated at high spatial resolution over a large mountainous region. Climate Research 8(1), 1-20 https://doi.org/10.3354/cr008001
  7. Gallo, K. P., J. O. Adegoke, T. W. Owen, and C. D. Elvidge, 2002: Satellite-based detection of global urban heat-island temperature influence. Journal of Geophysical Research (D: Atmosphere) 107, ACLJ6-1-ACLJ6-6
  8. Gallo, K. P., and T. W. Owen, 1999: Satellite-based adjustments for the urban heat island temperature bias. Journal of Applied Meteorology 38(6), 806-813 https://doi.org/10.1175/1520-0450(1999)038<0806:SBAFTU>2.0.CO;2
  9. Hansen, J., W. Lawrence, D. Easterling, T. Peterson, T. Karl, R. Ruedy, M. Sato, and M. Imhoff, 2001: A closer look at United States and global surface temperature change. Journal of Geophysical Research(D: Atmospheres) 106(20),23947-23963 https://doi.org/10.1029/2001JD000354
  10. Kim, Y. H., H. D. Kim, S. W. Han, J. Y. Choi, J. M. Koo, U. Chung, J. Y. Kim, and Jin I. Yun, 2002: Using spatial data and crop growth modeling to predict performance of South Korean rice varieties grown in western coastal plains in North Korea. Korean Journal of Agricultural and Forest Meteorology 4(4), 224-236.
  11. Koo, J. M., S. Y. Hong, and J. I. Yun, 2001: A simple method for classifying land cover of rice paddy at a 1 km grid spacing using NOAA-AVHRR data. Korean Journal of Agricultural and Forest Meteorology 3(4), 215-219.
  12. Lee, C. K., B. W. Lee, Y. H. Yoon, and J. C. Shin, 2001a: Temperature response and prediction model of leaf appearance rate in rice. Korean Journal of Crop Science 46(3), 202-208
  13. Lee, C. K., B. W. Lee, J. C. Shin, and Y. H. Yoon, 2001b: Heading date and final leaf number as affected by sowing date and prediction of heading date based on leaf appearance model in rice. Korean Journal of Crop Science 46(3), 195-201
  14. Lee, D. Y., M. H. Kim, K. J. Lee, and B. W. Lee, 2006:Changes in Radiation Use Efficiency of rice canopies under different nitrogen nutrition status. Korean Journal of Agricultural and Forest Meteorology 8(3), 190-198
  15. Lemaire, G, F. Gastal, and F. Salette, 1989: Analysis of the effect of N nutrition on dry matter yield of a sward by reference to potential yield and optimum N content. In: Proceedings of the 16th International Grassland Congress. (Nice, France), 179-180
  16. Nalder, I. A., and R. W. Wein, 1998: Spatial interpolation of climatic normals: test of a new method in the Canadian boreal forest. Agricultural and Forest Meteorology 92(4), 211-225 https://doi.org/10.1016/S0168-1923(98)00102-6
  17. Olsyzk, D. M., H. G S. Centeno, L. H. Ziska, J. S. Kern, and R. B. Matthews, 1999: Global climate change, rice productivity and methane emissions: comparison of simulated and experimental results. Agricultural and Forest Meteorology 97(2),87-101 https://doi.org/10.1016/S0168-1923(99)00065-9
  18. Peterson, T. C., A. Huang, D. A. Mckittrick, K. P. Gallo, J. Lawrimore, and T. W. Owen, 1999: Global rural temperature trends. Geophysical Research Letters 26(3), 329-332 https://doi.org/10.1029/1998GL900322
  19. Pickering, N. B., J. W. Hansen, J. W. Jones, H. Chan, and D. Godwin, 1994: WeatherMan: a utility for managing and generating daily weather data. Agronomy Journal 86, 332-337 https://doi.org/10.2134/agronj1994.00021962008600020023x
  20. Ritchie, J. T., D. C. Godwin, and U. Singh, 1990: Soil and weather inputs for IBSNAT crop models. In: Proceedings of IBSNAT Symposium: Decision Support System for Agrotechnology Transfer. University of Hawaii, Honolulu, USA
  21. Southworth, J., R. A. Pfeifer, M. Habeck, J. C. Randolpf, O. C. Doering, J. J. Johnston, and D. G Rao, 2002: Changes in soybean yields in the midwestern United States as a result of future changes in climate, climate variability, and $CO_2$ fertilization. Climatic Change 53(4), 447-475 https://doi.org/10.1023/A:1015266425630
  22. Shim, K. M., Y. S. Lee, Y. K. Shin, K. Y. Kim, and J. T. Lee, 2005: Changes in simulated rice yields under GCM $2_XCO_2$ climate change scenarios. Proceedings ofthe 8th Conference on Agricultural and Forest Meteorology (Sangju University, Korea, 29-30 September 2005), 88-92
  23. Trnka, M., M. Dubrovsky, and Z. Zalud, 2004: Climate change impacts and adaptation strategies in spring barley production in the Czech Republic. Climatic Change 64, 227-255. https://doi.org/10.1023/B:CLIM.0000024675.39030.96
  24. Thomson, A. M., R. A. Brown, S. J. Ghan, R. C.lzaurralde, N. J. Rosenberg, and L. R. Leung, 2002: Elevation dependence of winter wheat production in eastern Washington State with climate change: a methodological study. Climatic Change 54, 141-164 https://doi.org/10.1023/A:1015743411557
  25. Ulrich, A. 1952: Physiological bases for assessing the nutritional requirements of plants. Annual Review of Plant Physiology 3,207-228 https://doi.org/10.1146/annurev.pp.03.060152.001231
  26. Yun, J. I., 1990: Analysis of the climatic impact on Korean rice production under the carbon dioxide scenario. Journal of Korean Meteorological Society 26(4), 263-274
  27. Yun, J. I., 2000: Estimation of climatological precipitation of North Korea by using a spatial interpolation scheme. Korean Journal ofAgricultural and Forest Meteorology 2(1), 16-23
  28. Yun, J. I., and K. H. Lee, 2000: Agroclimatology of North Korea for paddy rice cultivation: Preliminary results from a simulation experiment. Korean Journal of Agricultural and Forest Meteorology 2(2), 47-61
  29. Yun, J. I., 2003: Predicting regional rice production in South Korea using spatial data and crop-growth modeling. Agricultural Systems 77(1), 23-38 https://doi.org/10.1016/S0308-521X(02)00084-7
  30. Yun, J. I., 2004: Visualization of local climates based on geospatial climatology. Korean Journal of Agricultural and Forest Meteorology 6(4), 272-289.
  31. Yun, S. H., and J. T. Lee, 2001: Climate change impacts on optimum ripening periods of rice plant and its countermeasure in rice cultivation. Korean Journal of Agricultural and Forest Meteorology 3(1), 55-70
  32. 기상연구소 기후연구설, 2005: 한반도 기후 100년 변화와 미래 전망. 제 3차 기후변화학술대회 및 제 2차 기후변화 정책 포럼 CD-ROM (2005년 9월 7-8일, 서울)
  33. 권원태, 2004: 기후변화와의 과학적 현황과 전망 . 환경부 . 기상청 . 한국기상학회 공동주관 제 2 차 기후변화 학술대회 초록집 1-4. (2004 년 II 월 18-19 일, 대구 ).