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Evaluation of Monitoring Sites for Protection of Groundwater in an Urban Area
Author(s) -
Sargaonkar Aabha P.,
Gupta Apurba,
Devotta Sukumar
Publication year - 2008
Publication title -
water environment research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 73
eISSN - 1554-7531
pISSN - 1061-4303
DOI - 10.2175/106143008x304695
Subject(s) - groundwater , environmental science , context (archaeology) , pollution , univariate , groundwater pollution , bonferroni correction , contamination , environmental engineering , water quality , hydrology (agriculture) , multivariate statistics , statistics , aquifer , geography , mathematics , engineering , ecology , biology , geotechnical engineering , archaeology
Monitoring for seasonal variation and changes in groundwater is a costly project. Assessing groundwater at selected monitoring sites and for site‐specific indicators may reduce the cost of subsequent monitoring.
In this context, the present study developed a method to assess groundwater using a combination of multivariate and univariate statistical techniques to identify critical sites of contamination. The sample data used describes the groundwater quality in Allahabad, India. The factor analysis brings out the observable parameters for groundwater pollution. Finally, univariate techniques such as analysis of variance (ANOVA) and Bonferroni t‐test identify the critical sites of groundwater pollution.
The first factor indicated high loading (>0.6) of total dissolved solids, Cl, Na, Mg, conductivity, SO 4 , and hardness. This represented overall pollution status of groundwater from human habitation, waste disposal, and agricultural activities in Allahabad. Iron, Mn, and Zn showed loading on distinct factors and indicated local contamination. Univariate techniques ANOVA and Bonferroni t‐test for Zn concentration in handpump samples revealed heavy metal contamination at Hasimpur and Beniganj in India.
Thus, initial monitoring followed by statistical analysis can help identify critical sampling locations and important indicators.