A Quantitative Prediction Method of Pollution Degree of Offshore Water Based on Pollution Indicator Bacteria

Abstract

The invention belongs to the technical field of quantitatively predicting the degree of pollution of water bodies, and discloses a method for quantitatively predicting the degree of pollution of offshore water bodies based on pollution indicator bacteria groups, which obtains the physical and chemical index data of the water body in the research area to calculate the comprehensive water quality pollution index OPI, and obtains different The microbial community composition information in the sea water samples, using the random forest algorithm to screen out the pollution indicator bacteria that can indicate the pollution status, and then use the relative abundance and weight of each microorganism in the pollution indicator bacteria combination as the independent variable for quantitative prediction Degree of water pollution. The present invention establishes a quantitative determination model of water quality pollution based on random forest algorithm, directly and quickly identifies the severity of water quality deterioration through fewer pollution indicator bacteria, is applicable to water quality evaluation of water bodies in different environments, and provides reliable water quality monitoring and treatment. basis.

Description

technical field [0001] The invention belongs to the technical field of predicting the degree of pollution of water bodies, and in particular relates to a method for quantitatively predicting the degree of pollution of offshore water bodies based on pollution indicator bacteria groups. Background technique [0002] Currently, the closest prior art: [0003] As a collection area, the nearshore sea area receives a large amount of terrestrial sources. The impact of human activities on the nearshore ecological environment is increasing. With the increasing discharge of coastal cities from industry, agriculture and aquaculture, it is finally collected into the ocean through the river system. This has resulted in a natural pollution gradient from the near shore to the far sea, and the coastal environment is threatened by increasingly serious pollution and nutrient salts, which has brought serious harm to the ecological environment. Frequent outbreaks of toxic red tides in recent y...

AI Technical Summary

Problems solved by technology

[0008] (2) In the prior art, the degree of sea water pollution is not predicted by measuring the microbial community, resulting in inaccurate data for predicting the degree of sea water pollution in the prior art;

[0009] (3) In the existing technology, high-throughput sequencing is not used to accurately reflect the microbial composition information, resulting in inaccurate detection of dominant species, rare species and some unknown species in the sea area, that is, inaccurate prediction of pollution indicator bacteria

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