Ecology and Resilient Infrastructure

Korean Society of Ecology and Infrastructure Engineering (응용생태공학회)
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Analysis of Greenhouse Gas Emission Models and Evaluation of Their Application on Agricultural Lands in Korea

토양 온실가스 배출 예측 모델 분석 및 국내 농경지 적용성 평가

  • Hwang, Wonjae (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Park, Minseok (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Kim, Yong-Seong (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Cho, Kijong (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Lee, Woo-Kyun (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Hyun, Seunghun (Division of Environmental Science and Ecological Engineering, Korea University)
  • 황원재 (고려대학교 환경생태공학부) ;
  • 박민석 (고려대학교 환경생태공학부) ;
  • 김용성 (고려대학교 환경생태공학부) ;
  • 조기종 (고려대학교 환경생태공학부) ;
  • 이우균 (고려대학교 환경생태공학부) ;
  • 현승훈 (고려대학교 환경생태공학부)
  • Received : 2015.05.12
  • Accepted : 2015.06.23
  • Published : 2015.06.30
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Abstract

Greenhouse gas (GHG) emission from agricultural lands is recognized as one of important factors of global warming. The objective of this short communication was to evaluate the applicability of different soil GHG emission prediction models on agricultural systems in Korea. Four models, namely, DNDC, DAYCENT, EXPERT-N and COUP, were selected and the basic structure (e.g., components and sub-model), input variables, and output variables were compared. In particular, the availability and compilation of essential input variables were assessed. Major input variables needed for operating these predictive models were found to be available through database systems established by national organizations such as the Korea Meteorological Administration, the Korean Soil Information System, and the Rural Development Administration. However, in order to apply these models in Korea, it was necessary to calibrate and validate each of the models for the domestic landscape settings and climate conditions. In addition, field data of long-term monitoring of GHG emission from agricultural lands are limited and therefore should be measured.

농경지 토양에서 배출되는 온실가스는 기후변화와 지구온난화에 영향을 미치는 중요한 요인 중 하나이다. 본 연구에서는 해외에서 개발되어 이용되고 있는 DNDC, DAYCENT, EXPER-N, COUP 모델의 기본적인 구조와 입력, 출력 인자를 분석함으로써 국내 적용 가능성을 평가하였으며, 현재 국내의 여건에서 각 모델의 구동에 요구되는 필수 입력 인자의 형태와 확보 가능성에 대해 조사하였다. 모델 구동의 필수 인자는 기상청, 한국토양정보시스템, 농촌진흥청 등의 국내 관계 기관의 자료를 통해 확보할 수 있다. 하지만 실제 국내 적용을 위해서는 국내 지형과 기후 조건을 반영하고 모델의 보정과 검증을 통해 모델을 교정할 필요가 있다. 또한, 다양한 조건의 농경지를 대상으로 한 장기적인 현장 온실가스 발생 모니터링 자료 구축이 필요하다.

Keywords

References

  1. Anand, S.V. 2013. Global environmental issues. doi: 10.4172/scientificreports.632.
  2. Conant, R.T., Ryan, M.G., Agren, G.I., Birge, H.E., Davidson, E.A., Eliasson, P.E., Evans, S.E., Frey, S.D., Giardina, C.P., Hopkins, F.M., Hyvonen, R., Kirschbaum, M.U., Lavallee, J.M., Leifeld, J., Parton, W.J., Steinweg, J.M., Wallenstein, M.D., Wetterstedt, J.A.M. and Bradford, M.A. 2011. Temperature and soil organic matter decom-position rates- synthesis of current knowledge and a way forward. Global Change Biology 17: 3392-3404. https://doi.org/10.1111/j.1365-2486.2011.02496.x
  3. Deng, J., Zhou, Z., Zheng, X. and Li, C. 2013. Modeling impacts of fertilization alternatives on nitrous oxide and nitric oxide emissions from conventional vegetable fields in southeastern China. Atmospheric Environment 81: 642-650. https://doi.org/10.1016/j.atmosenv.2013.09.046
  4. Eckersten, H., Jansson, P.E. and Johnsson, H. 1998. SOILN Model User's Manual, Version 9.2. Communications. 98: 6. Division of Hydrotechnics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
  5. Engel, T. and Priesack, E. 1993. Expert-N, a building block system of nitrogen models as resource for advice, research, water management and policy. In, Eijsackers, H.J.P. and Hamers, T. (eds.), Integrated Soil and Sediment Research: a Basis for Proper Protection. Kluwer Academic Publishers, Dordrecht, the Netherlands. pp. 503-507.
  6. Giltrap, D.L., Li, C. and Saggar, S. 2010. DNDC: A processbased model of greenhouse gas fluxes from agricultural soils. Agriculture, Ecosystems and Environment 136: 292-300. https://doi.org/10.1016/j.agee.2009.06.014
  7. Hutson, J.L. and Wagenet, R.J. 1992. LEACHM: Leaching Estimation and Chemistry Model: a Process-Based Model of Water and Solute Movement, Transformations, Plant Uptake and Chemical Reactions in the Unsaturated Zone. Version 3.0. Research Series No. 93-3. Department of Soil, Crop, and Atmospheric Sciences, Cornell University, Ithaca, New York, USA.
  8. IPCC. 2013. Working Group I Contribution to the IPCC Fifth Assessment Report Climate Change 2013: The Physical Science Basis. http://www.climatechange2013.org/report/. Accessed 29 April 2015.
  9. Jansson, P.E. and Moon, D.S. 2001. A coupled model of water, heat and mass transfer using object-orientation to improve flexibility and functionality. Environmental Modelling and Software 16: 37-46. https://doi.org/10.1016/S1364-8152(00)00062-1
  10. Johnsson, H., Bergstrom, L., Jansson, P.E. and Paustian, K. 1987. Simulated nitrogen dynamics and losses in a layered agricultural soil. Agriculture, Ecosystems and Environment 18: 333-356. https://doi.org/10.1016/0167-8809(87)90099-5
  11. Kim, D.S. and Na, U.S. 2011. Soil emission measurements of $N_2O$, $CH_4$ and $CO_2$ from intensively managed upland cabbage field. Journal of Korean Society for Atmospheric Environment 27: 313-325. (in Korean) https://doi.org/10.5572/KOSAE.2011.27.3.313
  12. KMA. 2015. http://www.kma.go.kr. Korea Meteorological Administration, Korea. Accessed 29 April 2015. (in Korean)
  13. KREI. 2015. http://www.krei.re.kr. Korea Rural Economic Institute, Korea. Accessed 29 April 2015. (in Korean)
  14. KSIS. 2015. http://soil.rda.go.kr/soil/index.jsp. Korean Soil Information System, Korea. Accessed 29 April 2015. (in Korean)
  15. Li, C., Frolking, S. and Frolking, T.A. 1992. A model of nitrous oxide evolution from soil driven by rainfall events: I. model structure and sensitivity. Journal of Geophysical Research 97: 9759-9776. https://doi.org/10.1029/92JD00509
  16. Parton, W.J., Hartman, M., Ojima, D.S. and Schimel, D.W. 1998. DAYCENT and its land surface submodel: description and testing. Global and Planetary Change 19: 35-48. https://doi.org/10.1016/S0921-8181(98)00040-X
  17. Parton, W.J., Schimel, D.S., Ojima, D.S. and Cole, C.V. 1994. A general model for soil organic matter dynamics: sensitivity to litter chemistry, texture and management. In, Bryant, R.B. and Arnold, R.W. (eds.), Quantitative Modeling of Soil Forming Processes. Soil Science Society of America. Madison, WI, USA. pp. 147-167.
  18. RDA. 2015. http://rda.go.kr/. Rural Development Administration, Korea. Accessed 29 April 2015. (in Korean)
  19. Shin, M.H, Jang, J.R., Won, C.H., Kum, D.H., Jung, Y.H., Lee, S.I., Lim, K.J. and Choi, J.D. 2014. Simulation of GHG emission from paddy field using DNDC model. Journal of the Korean Society of Agricultural Engineers 56: 47-57. (in Korean)
  20. Wua, S.H., Jansson, P.E. and Kolari, P. 2011. Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem. Ecological Modelling 222: 3103-3119. https://doi.org/10.1016/j.ecolmodel.2011.05.023

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