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A simulation–optimization modeling approach for watershed-scale agricultural N2O emission mitigation under multi-level uncertainties

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Abstract

In this research, an integrated simulation–optimization modeling approach (ISOMA) was developed for supporting agricultural N2O emission mitigation at the watershed scale. This approach can successfully combine soil N2O emission simulation and the consequential mitigation management within a general modeling framework. Also, uncertainties associated with the key soil parameter can be effectively reflected and addressed through adoption of Monte Carlo analysis for the simulation results. The Monte Carlo simulated results were then used to generate fuzzy membership functions that can be consequentially used for emission mitigation management, reflecting the combined uncertainties for N2O emission simulation and mitigation management. The developed ISOMA was then applied to a reservoir watershed in Miyun county of Beijing municipality. In the studying watershed, the simulation model was calibrated and verified. Then, N2O emission from multiple agricultural land-use patterns were predicted. The amounts of N2O emission of four land use patterns (i.e., cash tree, orchard, cropland, and natural forest) were (536.9, 590.8, 653.1), (237.7, 254.4, 275.9), (79.5, 100.7, 105.1), (33.0, 47.3, 61.1) kg CO2 eq ha−1 year−1, respectively. Two scenarios (i.e., G1 and G2) were set up according to development priorities of local economy and society. Meanwhile, multiple credibility levels were considered according to the risk of N2O emission. The land use patterns could be adjusted according to solutions of ISOMA. The developed methods could help regional manager choose various production patterns with cost-effective agriculture N2O emission management schemes in the Miyun reservoir watershed. The manager also can obtain deeply insights into the tradeoffs between agricultural benefits and system reliabilities.

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Abbreviations

Nmin :

Mineral nitrogen

SOC:

Soil organic carbon

GHG:

Greenhouse gases

G1 N2O:

Mitigation scenario

G2 N2O:

Increment scenario

DNDC:

Denitrification and decomposition

BAU:

Business as usual

MC:

Monte Carlo

ISOMA:

Integrated simulation–optimization modeling approach

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Acknowledgements

This work was supported by the by the National Key Research Program of China (2016YFC0502209), the National Natural Science Foundation of China (Nos. 51522901), and the Fundamental Funds for Central Universities. We would also like to express our gratitude to the anonymous reviewers and the editors for providing us the helpful comments and suggestive advices in improving our manuscript.

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Authors and Affiliations

  1. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China

    Ronghua Xu, Yanpeng Cai, Zhifeng Yang, Wen Xu & Qiangqiang Rong

  2. Beijing Engineering Research Center for Watershed Environmental Restoration and Integrated Ecological Regulation, School of Environment, Beijing Normal University, Beijing, 100875, China

    Yanpeng Cai & Zhifeng Yang

  3. Institute for Energy Environment, and Sustainable Communities, University of Regina, Research Drive, Regina, SK, S4S 7H9, Canada

    Yanpeng Cai & Qian Tan

  4. College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100083, China

    Qian Tan

Authors
  1. Ronghua Xu
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  2. Yanpeng Cai
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  3. Zhifeng Yang
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  4. Qian Tan
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  5. Wen Xu
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  6. Qiangqiang Rong
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Correspondence to Yanpeng Cai.

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Xu, R., Cai, Y., Yang, Z. et al. A simulation–optimization modeling approach for watershed-scale agricultural N2O emission mitigation under multi-level uncertainties. Stoch Environ Res Risk Assess 32, 2683–2697 (2018). https://doi.org/10.1007/s00477-018-1586-1

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