Inversion of dispersion coeffcient in water quality model using optimal perturbation algorithm

来源 :Applied Mathematics and Mechanics(English Edition) | 被引量 : 0次 | 上传用户:canghaiyuemenglong
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As a primary parameter in the water quality model for shallow bays, the dispersion coeffcient is traditionally determined with a trial-and-error method, which is time-consuming and requires much experience. In this paper, based on the measured data of chemical oxygen demand (COD), the dispersion coeffcient is calculated using an inversion method. In the process, the regularization method is applied to treat the ill-posedness, and an operator identity perturbation method is used to obtain the solution. Using the model with an inverted dispersion coeffcient, the distributions of COD, inorganic nitrogen (IN), and inorganic phosphorus (IP) in Bohai Bay are predicted and compared with the measured data. The results indicate that the method is feasible and the inverted dispersion coeffcient can be used to predict other pollutant distribution. This method may also be further extended to the inversion of other parameters in the water quality model. As a primary parameter in the water quality model for shallow bays, the dispersion coeffcient is traditionally determined with a trial-and-error method, which is time-consuming and requires much experience. In this paper, based on the measured data of chemical oxygen Demand (COD), the dispersion coeffcient is calculated using an inversion method. In the process, the regularization method is applied to treat the ill-posedness, and an operator identity perturbation method is used to obtain the solution. dispersion coeffcient, the distributions of COD, inorganic nitrogen (IN), and inorganic phosphorus (IP) in Bohai Bay are predicted and compared with the measured data. The results indicate that the method is feasible and the inverted dispersion coeffcient can be used to predict other pollutant distribution. This method may also be further extended to the inversion of other parameters in the water quality model.
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