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Modeling CH4 and N2O emission patterns and mitigation potential from paddy fields in Shanghai, China with the DNDC model

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  • Zhao, Zheng
  • Cao, Linkui
  • Deng, Jia
  • Sha, Zhimin
  • Chu, Changbin
  • Zhou, Deping
  • Wu, Shuhang
  • Lv, Weiguang

Abstract

The flooded paddy field ecosystem is an important source of CH4 and N2O emissions from agricultural lands. Denitrification-Decomposition (DNDC), a process-based model, was used in this study to evaluate the effects of different field management practices on CH4 and N2O emissions from flooded paddy fields in Shanghai, China. The results indicated that the predicted seasonal patterns of CH4 (R2 = 0.76, ME = 0.71) and N2O (R2 = 0.71, ME = 0.67) emissions were in line with the observations from our experimental paddy field under traditional management practices. The total CH4 and N2O fluxes from paddy fields in the Shanghai region in the 2013 rice season reached 32,300 and 175 tons, respectively, and varied widely across 101 simulated rice-cultivating towns. A sensitivity analysis indicated that CH4 emissions were positively correlated with the organic fertilizer rate, the straw returned fraction, the tillage depth and the soil organic carbon (SOC) content and negatively correlated with the soil clay fraction. N2O emissions had a positive relationship with precipitation, the urea rate, the tillage depth and the SOC content and a negative relationship with the soil pH and the clay fraction. Based on the sensitivity analysis, four field management variables, including the fertilization rate, the irrigation method, the straw returned fraction and the tillage depth, were selected to construct several management scenarios for the DNDC scenario simulation tests. The simulated results indicated that reducing the rate of fertilization by 20% combined with moistening irrigation (keeping the paddy soil saturated with water but not covered with a layer of water) was the best practice for long-term sustainable management of paddy fields. This best management practice could reduce integrated emissions of CH4 and N2O (CO2-equivalent) by 33%, while maintaining optimal rice yields. However, straw returning and deep plowing increased CH4 emissions from paddy fields in Shanghai.

Suggested Citation

  • Zhao, Zheng & Cao, Linkui & Deng, Jia & Sha, Zhimin & Chu, Changbin & Zhou, Deping & Wu, Shuhang & Lv, Weiguang, 2020. "Modeling CH4 and N2O emission patterns and mitigation potential from paddy fields in Shanghai, China with the DNDC model," Agricultural Systems, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:agisys:v:178:y:2020:i:c:s0308521x18313660
    DOI: 10.1016/j.agsy.2019.102743
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    1. Gilhespy, Sarah L. & Anthony, Steven & Cardenas, Laura & Chadwick, David & del Prado, Agustin & Li, Changsheng & Misselbrook, Thomas & Rees, Robert M. & Salas, William & Sanz-Cobena, Alberto & Smith, , 2014. "First 20 years of DNDC (DeNitrification DeComposition): Model evolution," Ecological Modelling, Elsevier, vol. 292(C), pages 51-62.
    2. Lamers, Marc & Ingwersen, Joachim & Streck, Thilo, 2007. "Modelling N2O emission from a forest upland soil: A procedure for an automatic calibration of the biogeochemical model Forest-DNDC," Ecological Modelling, Elsevier, vol. 205(1), pages 52-58.
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    1. Liang, Hao & Xu, Junzeng & Hou, Huijing & Qi, Zhiming & Yang, Shihong & Li, Yawei & Hu, Kelin, 2022. "Modeling CH4 and N2O emissions for continuous and noncontinuous flooding rice systems," Agricultural Systems, Elsevier, vol. 203(C).

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