Evaluation of drinking quality of groundwater through multivariate techniques in urban area

Groundwater is a major source of drinking water in urban areas. Because of the growing threat of debasing water quality due to urbanization and development, monitoring water quality is a prerequisite to ensure its suitability for use in drinking. But analysis of a large number of properties and para...

Full description

Saved in:
Bibliographic Details
Published in:Environmental monitoring and assessment 2010-07, Vol.166 (1-4), p.149-157
Main Authors: Das, Madhumita, Kumar, A, Mohapatra, M, Muduli, S. D
Format: Article
Language:English
Subjects:
Applied sciences
Atmospheric Protection/Air Quality Control/Air Pollution
Cities
Cluster Analysis
Datasets
Discriminant analysis
Drinking
Drinking quality
Drinking water
Drinking water and swimming-pool water. Desalination
Earth and Environmental Science
Ecology
Ecotoxicology
Environment
Environmental Management
Environmental monitoring
Environmental Monitoring - methods
Exact sciences and technology
Fresh Water - chemistry
Groundwater
Groundwaters
Indicators
Monitoring/Environmental Analysis
Multivariate Analysis
Multivariate techniques
Natural water pollution
Nitrates
Pollution
Principal components analysis
Statistical methods
Surface water
Urban area
Urban areas
Urbanization
Variables
Water analysis
Water monitoring
Water Pollutants - analysis
Water Pollution - statistics & numerical data
Water quality
Water quality indicators
Water sampling
Water Supply - analysis
Water treatment and pollution
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Groundwater is a major source of drinking water in urban areas. Because of the growing threat of debasing water quality due to urbanization and development, monitoring water quality is a prerequisite to ensure its suitability for use in drinking. But analysis of a large number of properties and parameter to parameter basis evaluation of water quality is not feasible in a regular interval. Multivariate techniques could streamline the data without much loss of information to a reasonably manageable data set. In this study, using principal component analysis, 11 relevant properties of 58 water samples were grouped into three statistical factors. Discriminant analysis identified “pH influence” as the most distinguished factor and pH, Fe, and NO [graphic removed] as the most discriminating variables and could be treated as water quality indicators. These were utilized to classify the sampling sites into homogeneous clusters that reflect location-wise importance of specific indicator/s for use to monitor drinking water quality in the whole study area.
ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-009-0991-9