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Multivariate Statistical Approach to Identify Influencing Factors of Groundwater Quality in Jinji Water Source of Wuzhong City

Cao Yang1,2,Teng Yanguo1,2,Liu Yunzhu3   

  1. 1.College of Water Sciences, Beijing Normal University, Beijing100875, China;
    2.Engineering Research Center of Groundwater Pollution Control and Remediation, Ministry of Education, Beijing100875, China;
    3.Water Resources and Hydropower Planning and Design General Institute, Ministry of Water Resources, Beijing100120, China
  • Received:2012-06-27 Online:2013-01-26 Published:2013-01-26

Abstract:

32 water samples in Jinji water source of Wuzhong City are collected and 11 parameters for each sample are analyzed. Based on the analysis of flow field and hydrochemistry of groundwater, both of factor analysis method and hierarchical cluster analysis method are used to evaluate the comprehensive influence factors of groundwater quality. The results of these two methods are relatively consistent, both of which show that the groundwater quality here are mainly controlled by three kinds of impacts. The first kind of impact is from lixiviation mainly controlled by Cl-, SO2-4, Mg2+, NO-3, and Ca2+, which appears stronger in east than west. The relative contribution of this impact is 48.4%. The second kind of impact is from evaporation-concentration mainly controlled by HCO-3, Na+, EC, TDS, and T-Hard, which appears stronger in east than in west. The relative contribution of this impact is 39.66%. The third kind of impact is from human activities mainly associated with NH4-N. The last impact has the same spatial distribution as the factories and pollution discharge areas. The relative contribution of this impact is 11.94%. The distributions of three factors show that evaporation-concentration mainly occurs along the Yellow River. The combined effect of lixiviation and evaporation-concentration occur in north of the Han Drainage. Ammonia-nitrogen pollution is obvious along the Nangan Drainage.

Key words: groundwater, water quality, influence factors, multivariate statistical analysis, Wuzhong City

CLC Number: 

  • P641
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