title: A case study of an enhanced eutrophication model with stoichiometric zooplankton growth sub-model calibrated by Bayesian method.
abstract: Urban lakes in China have suffered from severe eutrophication over the past several years, particularly those with relatively small areas and closed watersheds. Many efforts have been made to improve the understanding of eutrophication physiology with advanced mathematical models. However, several eutrophication models ignore zooplankton behavior and treat zooplankton as particles, which lead to the systematic errors. In this study, an eutrophication model was enhanced with a stoichiometric zooplankton growth sub-model that simulated the zooplankton predation process and the interplay among nitrogen, phosphorus, and oxygen cycles. A case study in which the Bayesian method was used to calibrate the enhanced eutrophication model parameters and to calculate the model simulation results was carried out in an urban lake in Tianjin, China. Finally, a water quality assessment was also conducted for eutrophication management. Our result suggests that (1) integration of the Bayesian method and the enhanced eutrophication model with a zooplankton feeding behavior sub-model can effectively depict the change in water quality and (2) the nutrients resulting from rainwater runoff laid the foundation for phytoplankton bloom.
authors.affiliation: School of Environmental Science and Engineering, Tianjin University, Tianjin, 300072, China.
authors.forename: Likun
authors.initials: L
authors.lastname: Yang
authors.affiliation: School of Environmental Science and Engineering, Tianjin University, Tianjin, 300072, China.|State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China.
authors.forename: Sen
authors.initials: S
authors.lastname: Peng
authors.affiliation: School of Environmental Science and Engineering, Tianjin University, Tianjin, 300072, China. jmsun@tju.edu.cn.|State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China. jmsun@tju.edu.cn.
authors.forename: Jingmei
authors.initials: J
authors.lastname: Sun
authors.affiliation: School of Environmental Science and Engineering, Tianjin University, Tianjin, 300072, China.|State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China.
authors.forename: Xinhua
authors.initials: X
authors.lastname: Zhao
authors.affiliation: School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin, 300384, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Li
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D002138:Calibration; D002681:China; D004784:Environmental Monitoring / Q000379:methods*; D005068:Eutrophication; D060106:Lakes / Q000737:chemistry*; D015233:Models, Statistical; D009584:Nitrogen / Q000032:analysis; D010758:Phosphorus / Q000032:analysis; D010839:Phytoplankton / Q000254:growth & development; D060753:Water Quality; D015048:Zooplankton / Q000254:growth & development*
chemical_list: D010758:Phosphorus; D009584:Nitrogen
keywords: Bayesian method; Eutrophication model; MCMC; Stoichiometry; Urban lake; Zooplankton