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中国南海大亚湾水质的人工神经网络评估

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

作者信息

Wu Mei-Lin, Wang You-Shao, Gu Ji-Dong

机构信息

State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301, China.

Daya Bay Marine Biology Research Station, Chinese Academy of Sciences, Shenzhen, 518121, China.

出版信息

Ecotoxicology. 2015 Oct;24(7-8):1632-42. doi: 10.1007/s10646-015-1453-5. Epub 2015 Apr 7.

DOI:10.1007/s10646-015-1453-5
PMID:25847104
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.

摘要

在本研究中,使用了诸如自组织映射(SOM)之类的人工神经网络来评估气候变化和人类活动对中国南海大亚湾水质的影响。SOM已识别出水质的人为影响和季节特征。SOM将四季分为四组(冬季、春季、夏季和秋季)。东南亚季风,10月至次年4月为东北风,5月至9月为西南风,对大亚湾水质也有重要影响。空间格局主要与人为活动和水动力条件有关。在空间特征方面,通过化学计量学将大亚湾水质分为两组。监测站(S3、S8、S10和S11)位于这些区域(大鹏澳、澳头港)以及大亚湾东北部,这些都是人类活动区域。在大亚湾核电站(S5)附近水体已观测到热污染。其余监测点位于大亚湾的南部、中部和东部,这些区域是与中国南海有水体交换的区域。本研究结果可为大亚湾的时空格局提供信息。未来将针对大亚湾气候因素、人类活动和海湾形态变化对海湾生态功能变化开展更多研究。

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本文引用的文献

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Mar Pollut Bull. 2010 Jun;60(6):852-60. doi: 10.1016/j.marpolbul.2010.01.007. Epub 2010 Feb 13.
2
Phytoplankton community structure and environmental parameters in aquaculture areas of Daya Bay, South China Sea.南海大亚湾养殖区浮游植物群落结构与环境参数。
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Identification of anthropogenic effects and seasonality on water quality in Daya Bay, South China Sea.
中国南海大亚湾水质的人为影响及季节性特征识别
J Environ Manage. 2009 Jul;90(10):3082-90. doi: 10.1016/j.jenvman.2009.04.017. Epub 2009 Jun 10.
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Ecological environment changes in Daya Bay, China, from 1982 to 2004.1982年至2004年中国大亚湾的生态环境变化
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Multivariate classification and modeling in surface water pollution estimation.地表水水质污染评估中的多变量分类与建模
Anal Bioanal Chem. 2008 Mar;390(5):1283-92. doi: 10.1007/s00216-007-1700-6. Epub 2007 Nov 15.
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Chemometrics data analysis of marine water quality and source identification in Southern Hong Kong.香港南部海水水质的化学计量学数据分析及来源识别
Mar Pollut Bull. 2007 Jun;54(6):745-56. doi: 10.1016/j.marpolbul.2007.01.006. Epub 2007 Feb 23.
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Application of multivariate statistical methods to water quality assessment of the watercourses in Northwestern New Territories, Hong Kong.多元统计方法在香港新界西北部水道水质评估中的应用。
Environ Monit Assess. 2007 Sep;132(1-3):1-13. doi: 10.1007/s10661-006-9497-x. Epub 2006 Dec 14.
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Assessing water quality in rivers with fuzzy inference systems: a case study.基于模糊推理系统的河流水质评估:一个案例研究
Environ Int. 2006 Aug;32(6):733-42. doi: 10.1016/j.envint.2006.03.009. Epub 2006 May 6.
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Factor analysis of water quality characteristics including trace metal speciation in the coastal environmental system of Chennai Ennore.钦奈埃努拉沿海环境系统水质特征(包括痕量金属形态)的因子分析
Environ Int. 2006 Feb;32(2):174-9. doi: 10.1016/j.envint.2005.08.008. Epub 2005 Oct 7.
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Variation of phytoplankton biomass and primary production in Daya Bay during spring and summer.大亚湾春夏季浮游植物生物量与初级生产力的变化
Mar Pollut Bull. 2004 Dec;49(11-12):1036-44. doi: 10.1016/j.marpolbul.2004.07.008.