Water quality simulation method based on GLUE multi-target water quality model calibration

Abstract

The invention relates to a water quality simulation method based on GLUE multi-target water quality model calibration. The method includes the following steps: 1) conducting parameter sensitivity analysis on a water quality model according to an overall sensitivity analysis method and conducting screening to obtain multi-target sensitive parameters according to the obtained sensitivity indexes; 2) generating a water quality random parameter group according to the prior sample distribution condition of the screened multi-target sensitive parameters; 3) simulating water quality indexes in the random parameter group, conducting screening through a likelihood function to obtain sensitive parameter intersection of various water quality indexes in an iteration mode, and finally enabling the parameters to be converged in a smaller section to achieve high accuracy water quality simulation. By means of the method, the optimum parameter combination is determined through simultaneous calibration of various output indexes, the water quality indexes can be simulated accurately and effectively, and the method provides accurate quantitative theoretical support for follow-up water environment water quality management, prediction, assessment and the like.

Description

technical field [0001] The invention relates to a water quality simulation method based on automatic calibration of parameters of a water quality model, which is mainly used for calibration and calibration of current mainstream multi-index water quality models. Background technique [0002] At present, with the in-depth understanding of the water environment, the structure of the water environment model has become increasingly complex. Common water quality models, such as WASP, QUAL, QUASAR, MIKE (ECOLAB), BASINS (RCHRES), etc., are complex model systems that can simultaneously simulate multiple water quality indicators. Although these model frameworks are gradually complete and can more comprehensively reflect human understanding of changes in the water environment, but at the same time the model variables and parameters continue to increase, leading to the determination (Pandon, Ren Li. 2012. Application in Irrigation Management of Majia River Basin Ⅰ. Parameter Calibrati...

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Problems solved by technology

[0005] In order to overcome the parameter error caused by the phenomenon of "different parameters with the same effect" in the existing method of simply using a single likelihood function to rate and time the water quality model, the present invention provides a method to simultaneously rate and determine multiple output indicators The optimal parameter combination, and then realize the method of water quality simulation, that is, by comprehensively considering multiple simulation indicators, to further screen the parameter combination that satisfies the conditions

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