Back to Search
Start Over
Ground Water Quality and Multivariate Statistical Methods
- Source :
- Environmental Processes. 2:347-360
- Publication Year :
- 2015
- Publisher :
- Springer Science and Business Media LLC, 2015.
-
Abstract
- In this paper, an attempt was made to study the physico-chemical properties of ground water of the Kozhikode district, Kerala, India, by applying multivariate statistical methods on samples collected from various parts of the study area. Combining principal component analysis and multiple linear regression (MLR), we developed a regression model for predicting total dissolved solids (TDS) in terms of calcium, magnesium, nitrate, sodium, chloride, potassium, bicarbonate and sulfate. This study revealed that statistically, calcium is the most significant component of TDS in the study area. The relevance of the regression model with respect to experimental data was further evaluated by applying structural equation modeling (SEM).
- Subjects :
- Environmental Engineering
Chemistry
Health, Toxicology and Mutagenesis
Statistical model
Regression analysis
Management, Monitoring, Policy and Law
Total dissolved solids
Pollution
Chloride
chemistry.chemical_compound
Nitrate
Linear regression
Statistics
Principal component analysis
medicine
Sulfate
Water Science and Technology
medicine.drug
Subjects
Details
- ISSN :
- 21987505 and 21987491
- Volume :
- 2
- Database :
- OpenAIRE
- Journal :
- Environmental Processes
- Accession number :
- edsair.doi...........bdf99f391f8fccc07687bec21ce4f790