不同建议分布MCMC算法在地下水污染源反演识别中的对比研究

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摘要为了探究正态分布、均匀分布和随机游走三种不同建议分布的MCMC算法对地下水污染源反演识别结果的影响,并遴选出最优的建议分布.本文根据假想案例建立了污染质运移模拟模型及基于Kriging方法的替代模型,并建立了基于正态分布、均匀分布和随机游走三种建议分布的MCMC算法以反演识别地下水污染源的释放历史.结果表明,针对本文算例,以均匀分布为建议分布的MCMC算法具有反演精度高、稳定性好、收敛速度快等优点,最为适合作为本研究案例的建议分布进行地下水污染源反演识别研究.

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	李雪利
	罗建男
	刘勇

关键词 ：地下水污染源识别, 贝叶斯理论, MCMC算法, 建议分布

Abstract：In order to obtain the optimal proposal distribution by exploring the influences of normal distribution, uniform distribution and random walk of the MCMC algorithms on the inversion identification results of groundwater pollution source, this paper established a simulation model of pollutant transport and a surrogate model using Kriging method with a hypothetical case, and the MCMC algorithm based on normal distribution, uniform distribution and random walk was developed to identify the release history of groundwater pollution sources. The results show that the inversion algorithm with uniform distribution as the proposal distribution has the advantages of high inversion accuracy, good stability and fast convergence speed, which proves to be the most suitable proposal distribution for groundwater pollution sources inversion.

Key words： groundwater pollution source identification Bayesian theory MCMC algorithm proposal distribution

收稿日期: 2022-08-10

PACS:

X523

基金资助:国家自然科学基金资助项目(42072279);吉林省教育厅科学研究项目(JJKH20211108KJ)

通讯作者: 罗建男,副教授,luojiannan01@126.com E-mail: luojiannan01@126.com

作者简介: 李雪利(1999-),女,河北唐山人,吉林大学硕士研究生,主要从事地下水数值模拟及污染源反演方面研究.xuelil21@mails.jlu.edu.cn.

引用本文:

李雪利, 罗建男, 刘勇. 不同建议分布MCMC算法在地下水污染源反演识别中的对比研究[J]. 中国环境科学, 2023, 43(4): 1646-1654. LI Xue-li, LUO Jian-nan, LIU Yong. Comparative study of different proposal distribution MCMC algorithms in groundwater pollution source identification. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(4): 1646-1654.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2023/V43/I4/1646

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