• 搜索

    科技期刊

    全部分類

    在線辦公

    全部分類
    11

    基于主成分分析和水質標識指數的地下水評價—張明明,陳 剛,劉耿煒,滕祥帥,華 勇

    摘要:為了解鹽城市地下水水質現狀及其主要污染因子,以鹽城市18眼地下水為研究對象,采用主成分分析和水質標識指數法相結合評價地下水水質狀況。

    基于主成分分析和水質標識指數的地下水評價—張明明,陳 剛,劉耿煒,滕祥帥,華 勇

    摘要:為了解鹽城市地下水水質現狀及其主要污染因子,以鹽城市18眼地下水為研究對象,采用主成分分析和水質標識指數法相結合評價地下水水質狀況。

    分類:2021年第04期(總第163期)

    發布: 2021-11-10 20:54:26

    詳情描述

    張明明,陳 剛,劉耿煒,滕祥帥,華 勇

    (江蘇省水文水資源勘測局鹽城分局, 江蘇 鹽城 224051)

      摘 要:為了解鹽城市地下水水質現狀及其主要污染因子,以鹽城市18眼地下水為研究對象,采用主成分分析和水質標識指數法相結合評價地下水水質狀況。結果表明,使用主成分分析可將23個水質指標綜合為8個主成分進行解釋,解釋率為75.967%。利用主成分分析成果構建新的水質評價指標體系并用水質標識指數進行評價,綜合水質標識指數表明18眼地下水水質較差,17個為Ⅳ類,1個為Ⅴ類。主要污染因子為溶解性總固體、總硬度、濁度、錳、總大腸菌群、菌落總數,在主要污染因子的確立上水質標識指數更為準確快速。2種評價方法總體趨勢基本相同,排名不完全一致。2種模型結合使用比單一模型更加可靠。

      關鍵詞:主成分分析;水質標識指數;地下水;評價;鹽城

      Groundwater quality assessment based on principal component analysis and water quality identification indices

      ZHANG Mingming, CHEN Gang, LIU Gengwei, TENG Xiangshuai, HUA Yong

      (Yancheng Hydrology and Water Resources Investigation Bureau of Jiangsu Province, Yancheng 224051, China)

      Abstract: In order to study the groundwater quality and the main pollution factors of Yancheng, eighteen groundwater sites are assessed by combining Principal Component Analysis(PCA) with water quality identification index method. Results show that, by using principal component analysis, 23 water quality indices can be combined into 8 principal component, of which the interpretation rate is 75.967%. Based on PCA results, a new water quality evaluation index system is established and water quality identification index is used to evaluate the water quality. In light of the comprehensive water quality identification indices, the quality of the eighteen groundwater are seriously polluted, of which seventeen sites belongs to Ⅳ, one site belongs to Ⅴ. The main pollution factors are total dissolved solids, total hardness, turbidity, Mn, total coliforms, total bacteria. The comprehensive water quality identification indices are more accurate and quicker on distinguishing the main pollution factors. The ranking of groundwater quality predicted by PCA is not identical with that by comprehensive water quality identification indices, but the overall trend in two models is same, which indicates that combination of the two models are more reliable than that of the single predictive model.

      Key words: Principal Component Analysis(PCA); water quality identification indices; ground water; assessment; Yancheng

    • 基于主成分分析和水質標識指數的地下水評價.pdf
      下載
      下載量:0
    掃一掃查看手機版
    這是描述信息

    水利部南京水利水文自動化研究所

    電話:(025)52898300 
    地址:南京市雨花臺區鐵心橋街95號
    郵箱:
    nsy@nsy.com.cn

    版權所有:水利部南京水利水文自動化研究所     蘇ICP備05086125號     中企動力  南京

    版權所有:水利部南京水利水文自動化研究所     蘇ICP備05086125號     中企動力  南京

    磁力天堂