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作 者:李瑶 徐凌云 史云鹏 Li Yao;Xu Lingyun;Shi Yunpeng(Shanghai Investigation, Design&Research Institute Co., Ltd, Shanghai 200335, China)
机构地区:[1]上海勘测设计研究院有限公司,上海200335
出 处:《环境科学与管理》2020年第8期173-177,共5页Environmental Science and Management
基 金:上海市科学技术委员会社会发展领域项目(No.17DZ1202703)。
摘 要:采用内梅罗指数法和主成分分析法,评价了青草沙水库和陈行水库2017年-2018年取、出水口水质。结果表明,与陈行水库相比,青草沙水库取水口和出水口水质差异较大。青草沙水库2017年水质波动不大,2018年有较大波动;陈行水库2017年-2018年水质波动明显。主成分分析法结果比内梅罗指数法的更乐观。内梅罗指数法在无严重超标水质指标时适用。主成分分析法适用于水质指标多、数据量大的情况。该结果为保护、治理和改善这两大水库水质提供一定的数据支持。Nemerow index method and principal component analysis were used to analyze the water quality of the Qingcaosha reservoir and the Chenhang reservoir from 2017 to 2018.Results showed that the difference of water quality between inlet and outlet of the Qingcaosha reservoir was larger than that of the Chenhang reservoir.In 2017,the water quality of the Qingcaosha reservoir fluctuated slightly.And it fluctuated greatly in 2018.The water quality of the Chenhang reservoir had fluctuated significantly from 2017 to 2018.The results of principal component analysis were more optimistic than that of Nemerow index method.Nemerow index method is applicable when there is no serious water quality index beyond the standard.Principal component analysis is suitable for water quality with many indexes and large amount of data.The results provide data support for the protection,management and improvement of water quality in these two reservoirs.
分 类 号:X824[环境科学与工程—环境工程]
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