基于典型相关系数和随机森林的水质预警方法

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Abstract This study proposed a high-precision early-warning method for detecting sudden water pollution incidents. Firstly, a database of sudden water pollution incidents containing 22common pollutants was established through simulation experiments. Secondly, the canonical correlation coefficients were used to accurately reveal the synergetic feedback law among various water quality parameters after pollution incidents. Finally, a water quality early-warning model, called "canonical correlation coefficients-random forest", was developed based on the multi-parameter synergetic feedback law identified above. Results show that the early-warning model's average true positive rates for known and unknown pollutants are 96.78% and 98.33%, respectively, while the average false positive rate under baseline status of water quality monitoring is 0.16%. The proposed early-warning model can provide practical technical support for reducing the loss of sudden water pollution incidents and ensuring the drinking water supply's safety.

Key words： sudden pollution water quality warning multi-parameter synergetic feedback canonical correlation coefficient random forest

Received: 01 February 2021

PACS:

X832

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	LI Ruo-nan
	WANG Qi
	LIU Shu-ming

Cite this article:

LI Ruo-nan,WANG Qi,LIU Shu-ming. Water quality warning method based on canonical correlation coefficient and random forest[J]. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(9): 4457-4464.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2021/V41/I9/4457

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