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论文类型：期刊论文

发表时间：2010-10-01

发表刊物：JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN

收录刊物：SCIE、EI、Scopus

卷号：18

期号：5

页面范围：771-779

ISSN号：1023-2796

关键字：water quality model; parameter estimation; data-driven model; near-optimal prediction

摘要：Marine water quality models are complicated because of their multi-parameter and multi-response characteristics. One major difficulty with water quality models is the accurate estimation of model parameters. In this paper, a new method based on a data-driven model (DDM) is developed to retrieve the value of model parameters. All training data are calculated by numerical water quality models from results of multi-parameter matching design cases so the physical properties are not disturbed. The concept is to find the relationship between model parameters and the pollution concentration values of interior stations. Field data are imported into the relationship for inversing optimal parameters or near-optimal parameters, ultimately an optimal or near-optimal prediction method is applied to validate the long-term stability of inversion results. Case tests were carried out in the Bohai Sea, China. Chemical oxygen demand (COD), dissolved inorganic nitrogen (DIN), chlorophyll (Chl) and their sensitive parameters were considered for validating the present method. The optimal solution determination method is applied for DIN and Chl owing to existence of the same sensitive parameters. Case studies show that the present method can make a more satisfactory estimation for this practical problem.