Authors: Likun Yang Sen Peng Jingmei Sun Xinhua Zhao Xia Li
Publish Date: 2016/01/18
Volume: 23, Issue: 9, Pages: 8398-8409
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 submodel 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 submodel can effectively depict the change in water quality and 2 the nutrients resulting from rainwater runoff laid the foundation for phytoplankton bloom
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