Water bloom prediction and factor analysis method based on multivariate periodic stationary time series analysis and gray theory

Abstract

The invention discloses a method for forecasting water bloom and analyzing factors on the basis of multivariate cyclostationary time sequence analysis and a grey theory, and belongs to the technical field of environmental engineering. The method includes acquiring and preprocessing monitoring data; screening characteristic factors; modeling a time sequence of the characteristic factors; and forecasting the time sequence of the characteristic factors and analyzing the characteristic factors. A multivariate cyclostationary property of the multivariate time sequence is inspected, a process for screening the characteristic factors of the water bloom is provided, necessary conditions for reasonably modeling the multivariate time sequence of the characteristic factors of the water bloom are provided, and a basis is also provided for analyzing the characteristic factors of the water bloom. In addition, a procedure for forming the water bloom due to the multiple characteristic factors is comprehensively described, and accordingly the accuracy and the reliability of a water bloom forecasting result are improved. Besides, closeness degrees of relations among the various influencing factors and the water bloom can be obtained according to errors among the water bloom forecasting result given by the method and measured data.

Description

technical field [0001] The invention relates to a water bloom prediction and factor analysis method, which belongs to the technical field of environmental engineering. Background technique [0002] Water bloom refers to a phenomenon that in eutrophic water bodies, when there are suitable environmental conditions such as light, water temperature, climate and hydrology that are conducive to the growth and accumulation of algae, algae will explode and accumulate and reach a certain concentration. Large-scale algal blooms are very harmful. It will not only destroy the structure and function of the water ecosystem and endanger human health, but also reduce the efficiency of water resource utilization, threaten the sustainable development and utilization of water resources, and cause huge economic losses. Generally speaking, there is still a lack of technologies and means that can effectively control algae blooms in a short period of time. Therefore, before the water bloom is eff...

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Problems solved by technology

[0014] The purpose of the present invention is to solve the inaccurate prediction results of existing water blooms, the difficulty of modeling the interaction between multiple characteristic factors in the formation of water blooms, and the determination of the degree of correlation between different characteristic factors and water blooms. Adopting technical means based on multivariate periodic stationary time-series analysis and gray theory, through the time-series modeling and analysis of characteristic factors in the formation process of water blooms, the prediction effect and factor analysis results of water blooms that are more in line with the actual situation can be obtained

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