title: A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region.
abstract: In this study, a Bayesian-based two-stage inexact optimization (BTIO) method is developed for supporting water quality management through coupling Bayesian analysis with interval two-stage stochastic programming (ITSP). The BTIO method is capable of addressing uncertainties caused by insufficient inputs in water quality model as well as uncertainties expressed as probabilistic distributions and interval numbers. The BTIO method is applied to a real case of water quality management for the Xiangxi River basin in the Three Gorges Reservoir region to seek optimal water quality management schemes under various uncertainties. Interval solutions for production patterns under a range of probabilistic water quality constraints have been generated. Results obtained demonstrate compromises between the system benefit and the system failure risk due to inherent uncertainties that exist in various system components. Moreover, information about pollutant emission is accomplished, which would help managers to adjust production patterns of regional industry and local policies considering interactions of water quality requirement, economic benefit, and industry structure.
authors.affiliation: Sino-Canada Resources and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China.
authors.forename: X H
authors.initials: XH
authors.lastname: Hu
authors.affiliation: Sino-Canada Resources and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China. yongping.li@iseis.org.|Environmental Systems Engineering Program, Faculty of Engineering and Applied Science, University of Regina, Regina, Sask, S4S 0A2, Canada. yongping.li@iseis.org.
authors.forename: Y P
authors.initials: YP
authors.lastname: Li
authors.affiliation: Sino-Canada Resources and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China.|Environmental Systems Engineering Program, Faculty of Engineering and Applied Science, University of Regina, Regina, Sask, S4S 0A2, Canada.
authors.forename: G H
authors.initials: GH
authors.lastname: Huang
authors.affiliation: Sino-Canada Resources and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China.
authors.forename: X W
authors.initials: XW
authors.lastname: Zhuang
authors.affiliation: Sino-Canada Resources and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China.
authors.forename: X W
authors.initials: XW
authors.lastname: Ding
mesh_terms: D001499:Bayes Theorem; D002681:China; D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D012306:Risk; D045483:Rivers; D035501:Uncertainty; D014876:Water Pollution / Q000706:statistics & numerical data*; D060753:Water Quality
keywords: Bayesian statistics; Optimization; Simulation; Two-stage stochastic; Uncertainty; Water quality management
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