A holistic review on the assessment of groundwater quality using multivariate statistical techniques

被引:13
|
作者
Patel, Praharsh S. [1 ]
Pandya, Dishant M. [1 ]
Shah, Manan [2 ]
机构
[1] Pandit Deendayal Energy Univ, Sch Technol, Dept Math, Gandhinagar 382426, Gujarat, India
[2] Pandit Deendayal Energy Univ, Sch Energy Technol, Dept Chem Engn, Gandhinagar 382426, Gujarat, India
关键词
Groundwater; Water quality; Multivariate statistical techniques; HEAVY-METAL CONTAMINATION; GOMTI RIVER INDIA; WATER-QUALITY; TEMPORAL VARIATIONS; SPATIAL-DISTRIBUTION; GIS; INDEX; DRINKING; SURFACE; BASIN;
D O I
10.1007/s11356-023-27605-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Water is an essential element in nature. It is used in drinking, irrigation, and industry mainly. Human health is directly linked to groundwater quality and is affected by poor groundwater quality caused by excessive fertilizer application and unhygienic circumstances. Because of increased pollution, investigating the water quality became a point of research for many researchers. There are numerous approaches to assessing water quality, and statistical methods are essential among them. This review paper discusses Multivariate Statistical Techniques, including Cluster Analysis, Principal Component Analysis, Factor Analysis, Geographical Information System, and Analysis of Variance, to name a few. We have presented the significance of each method concisely and how it is being used. In addition, an extensive table is prepared to demonstrate the individual technique along with the computational tool, the type of water bodies, and their respective regions. The advantages and disadvantages of the statistical techniques are also discussed therein. It is found that Principal Component Analysis and Factor Analysis are widely explored techniques.
引用
收藏
页码:85046 / 85070
页数:25
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