Bayesian Monte Carlo and maximum likelihood approach for uncertainty estimation and risk management: Application to lake oxygen recovery model

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• 作者：Abhishek Chaudhary^a ; ^{abhishek.chaudhary@hest.ethz.ch} ; Mohamed M. Hantush^b
• 关键词：Water quality ; Environmental modeling ; Risk management ; Bayesian ; Uncertainty estimation ; Dissolved oxygen
• 刊名：Water Research
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：108
• 期：Complete
• 页码：301-311
• 全文大小：911 K
• 卷排序：108

文摘

We present a modified Bayesian Monte Carlo maximum likelihood method - BMCML. New approach combines model calibration, uncertainty estimation & risk management. We derive analytical solution for lake DO concentration as a function of wind speed. Model parameter covariations influences risk management solutions. BMCML and MCMC performed equally well in simulating lake-oxygen recovery.