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Assessment of Tigris River Water Quality Using Multivariate Statistical Techniques

机译:利用多元统计技术评估德格兰河水质量

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摘要

The present study uses the multivariate statistical techniques by applying the Factor Analysis (Principle component method) to explain the observed water quality data of Tigris river within Baghdad city. The water quality was analyzed at eleven different sites, along the river, over a period of one year (2017) using 20 water quality parameters. Five factors were identified by factor analysis which was responsible from the 72.291% of the total variance of the water quality in the Tigris river. The first factor called the pollution factor explained 34.387% of the total variance and the second factor called the surface runoff and erosion factor explained 11.875% of the total variance. While, the third, fourth, and fifth factors explained 10.213%, 8.861% and 6.956% of the total variance and called pH, Silica and nutrient factors, respectively. Multivariate statistical techniques can be effective methods to aid water resources managers understand complex nature of water quality issues and determine the priorities to sustain water quality.
机译:本研究采用多元统计技术来应用因子分析(原理分量方法)来解释巴格达市内蒂格雷斯河的观察到的水质数据。在一年(2017年)的一年内(2017年)使用20个水质参数,在11种不同的地点分析了水质。因子分析确定了五种因素,该因素是底格里斯河水质量总方差的72.291%。称为污染因子的第一因素解释了总方差的34.387%,第二个因素称为表面径流和侵蚀因素的总方差的11.875%。虽然,第三个,第四个和第五个因素分别解释了总差异的10.213%,8.861%和6.956%,分别称为pH,二氧化硅和营养因子。多元统计技术可以是有效的方法,以帮助水资源管理人员了解水质问题的复杂性质,并确定维持水质的优先事项。

著录项

  • 作者

    Muntasir Shareef;

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  • 年度 2019
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  • 原文格式 PDF
  • 正文语种 eng
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