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印度曼尼普尔邦因帕尔西部地区的地下水质量,利用数据的多元统计分析。

Groundwater quality in Imphal West district, Manipur, India, with multivariate statistical analysis of data.

机构信息

Department of Ecology and Environmental Science, Assam University, Silchar 788011, India.

出版信息

Environ Sci Pollut Res Int. 2013 Apr;20(4):2421-34. doi: 10.1007/s11356-012-1127-2. Epub 2012 Aug 31.

Abstract

The aim of this paper was to analyze the groundwater quality of Imphal West district, Manipur, India, and assess its suitability for drinking, domestic, and agricultural use. Eighteen physico-chemical variables were analyzed in groundwater from 30 different hand-operated tube wells in urban, suburban, and rural areas in two seasons. The data were subjected to uni-, bi-, and multivariate statistical analysis, the latter comprising cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA). Arsenic concentrations exceed the Indian standard in 23.3% and the WHO limit in 73.3% of the groundwater sources with only 26.7% in the acceptable range. Several variables like iron, chloride, sodium, sulfate, total dissolved solids, and turbidity are also beyond their desirable limits for drinking water in a number of sites. Sodium concentrations and sodium absorption ratio (SAR) are both high to render the water from the majority of the sources unsuitable for agricultural use. Multivariate statistical techniques, especially varimax rotation of PCA data helped to bring to focus the hidden yet important variables and understand their roles in influencing groundwater quality. Widespread arsenic contamination and high sodium concentration of groundwater pose formidable constraints towards its exploitation for drinking and other domestic and agricultural use in the study area, although urban anthropogenic impacts are not yet pronounced.

摘要

本文旨在分析印度曼尼普尔邦因帕尔西部地区的地下水水质,并评估其用于饮用水、家庭和农业用途的适宜性。在两个季节中,从城市、郊区和农村的 30 个手动管井中分析了 18 个物理化学变量。数据进行了单变量、双变量和多变量统计分析,后者包括聚类分析 (CA)、主成分分析 (PCA) 和因子分析 (FA)。砷浓度在 23.3%的地下水中超过了印度标准,在 73.3%的地下水中超过了世界卫生组织的限值,只有 26.7%的地下水中在可接受范围内。在许多地方,一些变量如铁、氯、钠、硫酸盐、总溶解固体和浊度也超过了饮用水的理想限值。许多水源的钠离子浓度和钠离子吸收比 (SAR) 都很高,导致这些水不适合农业使用。多元统计技术,特别是 PCA 数据的方差极大旋转,有助于聚焦隐藏但重要的变量,并了解它们在影响地下水质量方面的作用。尽管城市人为影响尚不明显,但地下水的广泛砷污染和高钠浓度对其在研究区域内的饮用水及其他家庭和农业用途的开发构成了严峻的限制。

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