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Assessment for water quality by artificial neural network in Daya Bay, South China Sea.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Wu, Mei-Lin Wang, You-Shao Gu, Ji-Dong
Spatial Coverage	China
Description	Country affiliation: China Author Affiliation: Wu ML ( State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301, China.); Wang YS ( State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301, China. yswang@scsio.ac.cn.); Gu JD ( Daya Bay Marine Biology Research Station, Chinese Academy of Sciences, Shenzhen, 518121, China. yswang@scsio.ac.cn.)
Abstract	In this study, artificial neural network such as a self-organizing map (SOM) was used to assess for the effects caused by climate change and human activities on the water quality in Daya Bay, South China Sea. SOM has identified the anthropogenic effects and seasonal characters of water quality. SOM grouped the four seasons as four groups (winter, spring, summer and autumn). The Southeast Asian monsoons, northeasterly from October to the next April and southwesterly from May to September have also an important influence on the water quality in Daya Bay. Spatial pattern is mainly related to anthropogenic activities and hydrodynamics conditions. In spatial characteristics, the water quality in Daya Bay was divided into two groups by chemometrics. The monitoring stations (S3, S8, S10 and S11) were in these area (Dapeng Ao, Aotou Harbor) and northeast parts of Daya Bay, which are areas of human activity. The thermal pollution has been observed near water body in Daya Bay Nuclear Power Plant (S5). The rest of the monitoring sites were in the south, central and eastern parts of Daya Bay, which are areas that experience water exchanges from South China Sea. The results of this study may provide information on the spatial and temporal patterns in Daya Bay. Further research will be carry out more research concerning functional changes in the bay ecology with respect to changes in climatic factor, human activities and bay morphology in Daya Bay.
File Format	HTM / HTML
ISSN	09639292
Issue Number	7-8
Volume Number	24
e-ISSN	15733017
Journal	Ecotoxicology
Language	English
Publisher	Springer
Publisher Date	2015-10-01
Publisher Place	United States
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discipline Ecology Discipline Environmental Health Discipline Toxicology Environmental Monitoring Methods Hot Temperature Neural Networks (computer) Seawater Analysis Water Pollution China Hydrodynamics Nuclear Power Plants Seasons Water Quality Journal Article Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Health, Toxicology and Mutagenesis Medicine Toxicology Management, Monitoring, Policy and Law

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