Model parameter uncertainty-based dynamic prediction method for river emergency pollution accident

Abstract

The invention discloses a model parameter uncertainty-based dynamic prediction method for a river emergency pollution accident. The method comprises the steps of S1, generating uncertainty parameters by utilizing parameter rating, empirical data and literature consulting methods; S2, calculating a pollutant concentration value of each cross section at each moment after an accident point by utilizing values of the uncertainty parameters in the step S1 and initial cross section pollutant concentration; S3, selecting a likelihood function for calculating likelihood values corresponding to different parameter sets in the step S2; S4, estimating an uncertain range of a model prediction result under a certain confidence level by utilizing the likelihood values in the step S3 and extending the uncertain range to the dimensionality of the whole event after the accident happens to obtain an uncertainty interval of the model prediction result; and S5, continuously updating and correcting a simulated prediction result by utilizing actual measurement data, and repeating the steps to obtain a newly updated prediction result. According to the method, the model parameter uncertainty-based water quality prediction for the river emergency pollution accident is realized in combination with an uncertainty method, a dynamic updating theory and a generalized likelihood uncertainty algorithm.

Description

technical field [0001] The invention relates to the field of pollutant simulation, and specifically proposes an early warning method for sudden water pollution accidents based on a universal likelihood uncertainty algorithm and dynamic update. Background technique [0002] Rivers, lakes and reservoirs are important freshwater ecological resources for human beings, and areas along rivers and lakes are usually important areas where human activities are frequent and various organisms live and multiply. However, with the rapid development of the economy, human production and living activities have seriously affected the security of water resources, which has caused many economic and social problems. At present, there is no effective means to completely prevent the adverse impact of human activities on the water environment. In a long time in the future, the water environment problem will still be a prominent problem that we have to face. [0003] Among many water environment pr...

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Problems solved by technology

The objective existence of these uncertainties brings difficulties and challenges to the prediction of pollutant concentration

[0005] Although the deterministic water quality model has a complete theoretical system and can even accurately and meticulously represent the process of pollutant migration and diffusion, due to the complexity of the river environment itself, it is difficult to model the mechanism accurately, and it is difficult to fully obtain the initial conditions and hydrological data. In addition, the calibration of model parameters is very difficult, especially for sudden pollution accidents, which require the model to provide prediction data as soon as possible, making it very difficult to establish an excellent deterministic water quality model in a short period of time

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