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湖北省地表水水质评价指标及监测方式研究
引用本文:安堃达,程继雄,嵇晓燕,张煦,张晓彤,刘彬.湖北省地表水水质评价指标及监测方式研究[J].中国环境监测,2021,37(2):142-147.
作者姓名:安堃达  程继雄  嵇晓燕  张煦  张晓彤  刘彬
作者单位:湖北省生态环境监测中心站, 湖北 武汉 430072;中国环境监测总站, 国家环境保护环境监测质量控制重点实验室, 北京 100012
摘    要:选取湖北省100个国控断面2019年1—12月手工和自动监测数据,采用因子分析和聚类分析相结合的方法对水质评价指标进行优化筛选,结果表明,高锰酸盐指数、氨氮、总磷、pH、溶解氧等5项指标可以代表湖北省地表水水质的主要影响因子,从而实现水质监测指标的降维。对手工和自动2种监测方式进行比对,证明自动监测pH、溶解氧、高锰酸盐指数、总磷和氨氮5项水质评价指标的数据、评价结果与手工监测具有较强的一致性,用自动监测5项指标进行水质评价是合理、可行的,并能减轻手工监测的工作量。

关 键 词:水质评价指标  监测方式  因子分析  聚类分析
收稿时间:2020/1/16 0:00:00
修稿时间:2020/6/2 0:00:00

Study on the Evaluation Indicators and Monitoring Methods of Surface Water Quality in Hubei Province
AN Kund,CHENG Jixiong,JI Xiaoyan,ZHANG Xu,ZHANG Xiaotong,LIU Bin.Study on the Evaluation Indicators and Monitoring Methods of Surface Water Quality in Hubei Province[J].Environmental Monitoring in China,2021,37(2):142-147.
Authors:AN Kund  CHENG Jixiong  JI Xiaoyan  ZHANG Xu  ZHANG Xiaotong  LIU Bin
Institution:Hubei Eco-Environmental Monitoring Center Station, Wuhan 430072, China;State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China
Abstract:Based on the manual and automatic monitoring data of 100 national water monitoring spot in Hubei Province from January to December 2019, the water quality evaluation indicators were optimized by combining factor analysis and cluster analysis in present study.The result showed that the five indicators (CODMn, NH3-N, TP, pH and DO) could represent the main affecting factors of surface water quality in Hubei Province.Manual and automatic monitoring methods were also compared, it was found that the monitoring data and evaluation results of the five indicators (pH, DO, CODMn, TP and NH3-N) by automatic mode had strongly consistent with manual mode.Therefore, water quality evaluation by the five indicators with automatic monitoring mode was reasonable and feasible, which could reduce the workload of manual monitoring.
Keywords:water quality evaluation indicator  monitoring methods  factor analysis  cluster analysis
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