Paddy and Water Environment

, Volume 14, Issue 1, pp 123–129 | Cite as

Methane mitigation for flooded rice paddy systems in South Korea using a process-based model

Article

Abstract

Rice (Oryza sativa L.) is one of the most important food crops in the world. However, rice paddy fields are considered as one of the major sources of anthropogenic CH4 emissions. The objectives of this study were to estimate CH4 fluxes from a rice paddy field during rice growing seasons in South Korea and to assess the impacts of water managements on reduction of CH4 emissions using a process-based model. Three CH4 flux monitoring chamber systems installed at a rice paddy field in Gimje (South Korea) were used to measure CH4 fluxes. These measured datasets were used to evaluate the performance of the Denitrification–Decomposition (DNDC) model to simulate CH4 fluxes. A mid-late maturing rice cultivar (Shindongjinbyeo) was transplanted with a planting density with 0.15 m × 0.30 m (hill × row) on June 21, 2012 and June 21, 2013 after barely had been harvested at the study site. The DNDC model underestimated CH4 fluxes from a rice paddy field at the beginning of the rice growing seasons (overall 0.7 of R2 for the year 2013), while the DNDC model well-estimated CH4 emissions during the rice growing seasons. The DNDC model was used to assess the impacts of continuous flooding and midseason drainage on CH4 emissions. This study suggests that the DNDC model can be used to assess efficacious mitigation strategies to reduce the greenhouse gases.

Keywords

CH4 emission Closed chamber method Mitigation Water managements 

References

  1. Ali MA, Lee CH, Lee YB, Kim PJ (2009) Silicate fertilization in no-tillage rice farming for mitigation of methane emission and increasing rice productivity. Agric Ecosyst Environ 132:16–22CrossRefGoogle Scholar
  2. Babu YJ, Li C, Frolking S, Nayak DR, Datta A, Adhya TK (2005) Modelling of methane emissions from rice-based production systems in India with the denitrification and decomposition model: Field validation and sensitivity analysis. Curr Sci 89(11):1–9Google Scholar
  3. Beven JK (2001) Rainfall-runoff modelling—the primer. Wiley, Chichester 319Google Scholar
  4. Bodelier PL, Roslev P, Henckel T, Frenzel P (2000) Stimulation by ammoniumbased fertilizers of methane oxidation in soil around roots. Nature 403:421–424PubMedCrossRefGoogle Scholar
  5. Cai Z, Sawamoto S, Li C, Kang G, Boonjawat J, Mosier A, Wassmann R (2003) Field validation of the DNDC model for greenhouse gas emissions in East Asian cropping systems. Glob Biogeochem Cycles 17(4):1107. doi:10.1029/2003GB002046 CrossRefGoogle Scholar
  6. Cho Jaeil, Oki Taikan (2012) Application of temperature, water stress, CO2 in rice growth models. Rice 5(1):1–8CrossRefGoogle Scholar
  7. Cicerone RL, Oremland RS (1988) Biogeochemical aspects of atmospheric methane. Glob Biogeochem Cycles 2:299–327CrossRefGoogle Scholar
  8. Datta A, Yeluripati JB, Nayak DR, Mahata KR, Santra SC, Adhya TK (2013) Seasonal variation of methane flux from coastal saline rice field with the application of different organic manures. Atmos Environ 66:114–122CrossRefGoogle Scholar
  9. Denman KL, Brasseur G, Chidthaisong A, Ciais P, Cox PM, Dickinson RE, Hauglustaine D, Heinze C, Holland E, Jacob D, Lohmann U, Ramachadran S, da Silva Dias PC, Wofsy SC, Zhang X (2007) Coupling between changes in the climate system and biogeochemistry. Climate change 2007: the physical science basis. In: Soloma S, Ain D, Manning M, Chen Z, Marquis M, Averyt KB, Tignon M, Miller HL (eds) Contribution of working Group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 499–587Google Scholar
  10. Dong H, Yao Z, Zheng X, Mei B, Xie B, Wang R, Deng J, Cui F, Zhu J (2011) Effect of ammonium-based, non-sulfate fertilizers on CH4 emissions from a paddy field with a typical Chinese water management regime. Atmos Environ 45:1095–1101CrossRefGoogle Scholar
  11. Fumoto T, Kobayashi K, Li C, Yagi K, Hasegawa T (2008) Revising a process-based biogeochemistry model (DNDC) to simulate methane emission from rice paddy fields under various residue management and fertilizer regimes. Glob Change Biol 14:382–402CrossRefGoogle Scholar
  12. Giltrap DL, Li C, Saggar S (2010) DNDC: a process-based model of greenhouse gas fluxes form agricultural soils. Agr Ecosyst Environ 136:292–300CrossRefGoogle Scholar
  13. Gutierrez Jessie, Kima SY, Kim PJ (2013) Effect of rice cultivar on CH4 emissions and productivity in Korean paddy soil. Field Crop Res 146:16–24CrossRefGoogle Scholar
  14. Haas E, Klatt S, Fröhlich A, Kraft P, Werner C, Kiese R, Grote R, Breuer L, Butterbach-Bahl K (2012) LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale. Landsc Ecol 28:1–22Google Scholar
  15. Institute for the Study of Earth, Oceans and Space (2012) User’s guide for the DNDC model (Version 9.5). University of New Hampshire, DurhamGoogle Scholar
  16. IPCC (2006) IPCC guidelines for national greenhouse gas inventories, prepared by the national greenhouse gas inventories programme. In: Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K (eds) IGES, Hayama, JapanGoogle Scholar
  17. IPCC (2007) Summary for policymakers. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working group 1 to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UKGoogle Scholar
  18. Jain N, Dubey r, Dubey DS, Singh J, Khanna M, Pathak H, Bhatia A (2014) Mitigation of greenhouse gas emission with system of rice intensification in the Indo-Gangetic Plains. Paddy Water Environ 12:355–363CrossRefGoogle Scholar
  19. Jeong H, Roh K, Kim G, So K, Shim K, Lee DB (2010) Evaluation of CH4 emission in Korea paddy soil from 1991 to 2008. Korean J Soil Sci Fert 2010(1):214 (in Korean)Google Scholar
  20. Kim G-Y, Park S-I, Song B-H, Shin Y-K (2002) Emission characteristics of methane and nitrous oxide by management of water and nutrient in a rice paddy soil. Korean J Environ Agric 21(2):136–143 (in Korean with English abstract)CrossRefGoogle Scholar
  21. Kim SY, Gutierrez J, Kim PJ (2012a) Considering winter cover crop selection as green manure to control methane emission during rice cultivation in paddy soil. Agric Ecosyst Environ 161:130–136CrossRefGoogle Scholar
  22. Kim SY, Lee CH, Gutierrez J, Kim PJ (2012b) Contribution of winter cover crop amendments on global warming potential on rice paddy soil during cultivation. Plant Soil 366(1–2):273–286Google Scholar
  23. Li CS, Frolking S, Frolking TA (1992) A model of nitrous oxide evolution from soil driven by rainfall events: I. model structure and sensitivity. J Geophys Res 97:9759–9776CrossRefGoogle Scholar
  24. Li C, Aber J, Stange F, Butterbach-Bahl K, Papen H (2000) A process oriented model of N2O and NO emissions from forest soils: 1, Model development. J Geophys Res 105:4369–4384CrossRefGoogle Scholar
  25. Li C, Qiu J, Frolking S, Xiao X, Salas W, Moore B III, Boles S, Huang Y, Sass R (2002) Reduced methane emissions from large-scale changes in water management in China’s rice paddies during 1980–2000. Geophys Res Lett 29(20). doi:10.1029/2002GL015370
  26. Li C, Zhang Z, Guo L, Cai M, Cao C (2013) Emissions of CH4 and CO2 from double rice cropping systems under varying tillage and seeding methods. Atmos Environ 80:438–444Google Scholar
  27. Linguist B, van Groenigen KJ, Adviento-Borbe MA, Pittelkow C, van Kessel C (2012) An agronomic assessment of greenhouse gas emissions from major cereal crops. Global Change Biol 18:194–209CrossRefGoogle Scholar
  28. Lugato E, Zuliani M, Alberti G, Vedove GD, Gioli B, Miglietta F, Peressotti A (2010) Application of DNDC biogeochemistry model to estimate greenhouse gas emissions from Italian agricultural areas at high spatial resolution. Agric Ecosyst Environ 139:546–556CrossRefGoogle Scholar
  29. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part I—a discussion of principles. J Hydrol 10:282–290CrossRefGoogle Scholar
  30. Prather M, Ehhalt D (lead authors) (2001) Atmospheric chemistry and greenhouse gases. In: Houghton JT et al. (eds) Climate Change 2001: the scientific basis contribution of working group I to the third assessment report of the intergovernmental panel on climate change, Cambridge Univ. Press, New York, pp 239–287Google Scholar
  31. Ramaswamy V, Boucher O, Haigh J, Hauglustaine D, Haywood J, Myhre G, Nakajima T, Shi GY, Solomon S (2001) Radiative forcing of climate change. In: Houghton JT et al. Climate change 2001: the scientific basis contribution of working group I to the third assessment report of the intergovernmental panel on climate change, Cambridge Univ. Press, New York, pp 239–287Google Scholar
  32. Shin Y, Lee Y, Koh M, Eom K (2003) Diel Change of methane emission through rice plant under different water management and organic amendment. Korean J Soil Sci Fert 36(1):32–40Google Scholar
  33. Taylor JA, Brasseur GP, Zimmerman PR, Cicerone RJ (1991) A study of the sources and sinks of methane and methyl chloroform using a global three-dimensional Lagrangian tropospheric tracer transport model. J Geophys Chem 96:3013–3044CrossRefGoogle Scholar
  34. Wang C, Li S, Lai DYF, Wang W, Ma Y (2014) The effect of floating vegetation on CH4 and N2O emissions from subtropical paddy fields in China. Paddy Water Environ. doi:10.1007/s10333-014-0459-6 Google Scholar
  35. Yagi K, Minami K (1991) Emission and production of methane in the paddy fields of Japan. Jpn Agric Res Q 25:165–171Google Scholar
  36. Yun Jin I (2003) Predicting regional rice production in South Korea using spatial data and crop-growth modeling. Agr Syst 77:23–38CrossRefGoogle Scholar
  37. Zhang L, Yu D, Shi X, Weindorf DC, Zhao L, Ding W, Wang H, Pan J, Li C (2009a) Simulatioin of global warming potential (GWP) from rice fields in the Tai-Lake region, China by coupling 1:50,000 soil database with DNDC model. Atmos Environ 43:2237–2746Google Scholar
  38. Zhang L, Yu D, Shi X, Weindorf D, Zhao L, Ding W, Wang H, Pan J, Li C (2009b) Quantifying methane emissions from rice fields in the Taihu lake region, China by coupling a detailed soil database with biogeochemical model. Biogeosciences 6:739–749CrossRefGoogle Scholar

Copyright information

© The International Society of Paddy and Water Environment Engineering and Springer Japan 2015

Authors and Affiliations

  1. 1.APEC Climate Center, Climate Research DepartmentClimate Change Research TeamBusanRepublic of Korea
  2. 2.Department of Agricultural Environment, Climate Change and Agroecology Division, National Academy of Agricultural ScienceRural Development AdministrationSuwonKorea

Personalised recommendations