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

• Published in: Stochastic environmental research and risk assessment Vol. 32; no. 9; pp. 2683 - 2697
• Main Authors: Xu, Ronghua, Cai, Yanpeng, Yang, Zhifeng, Tan, Qian, Xu, Wen, Rong, Qiangqiang
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-09-2018; Springer Nature B.V
• Subjects: Agricultural economics; Agricultural land; Agricultural management; Aquatic Pollution; Carbon dioxide; Chemistry and Earth Sciences; Computational Intelligence; Computer Science; Computer simulation; Earth and Environmental Science; Earth Sciences; Emission; Emissions; Environment; Land use; Local economy; Math. Appl. in Environmental Science; Modelling; Monte Carlo simulation; Nitrous oxide; Optimization; Original Paper; Parameter uncertainty; Physics; Probability Theory and Stochastic Processes; Regional development; Reservoirs; Simulation; Statistics for Engineering; Waste Water Technology; Water Management; Water Pollution Control; Watershed management; Watersheds; Simulation and optimization; O emission; Miyun reservoir watershed; Agricultural N; Agricultural land use patterns
• ISSN: 1436-3240; 1436-3259
• DOI: 10.1007/s00477-018-1586-1

In this research, an integrated simulation–optimization modeling approach (ISOMA) was developed for supporting agricultural N
2
O emission mitigation at the watershed scale. This approach can successfully combine soil N
2
O 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 N
2
O 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, N
2
O emission from multiple agricultural land-use patterns were predicted. The amounts of N
2
O 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 CO
2
 eq ha
−1
 year
−1
, respectively. Two scenarios (i.e., G
1
and G
2
) were set up according to development priorities of local economy and society. Meanwhile, multiple credibility levels were considered according to the risk of N
2
O 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 N
2
O emission management schemes in the Miyun reservoir watershed. The manager also can obtain deeply insights into the tradeoffs between agricultural benefits and system reliabilities.