Spatial aspect of surface water quality using chemometric analysis.

Chemometric or multivariate techniques were applied to identify the spatialvariation and pollution sources of Jakara River Kano-Nigeria. Thirty water sampleswere collected: twenty three along River Getsi and seven surface water samples alongthe main channel River Jakara. Twenty three water quality p...

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Bibliographic Details
Main Authors: Aris, Ahmad Zaharin, Mustapha, Adamu
Format: Article
Language:English
English
Published: Sepuluh Nopember Institute of Technology, Department of Environmental Engineering 2011
Online Access:http://psasir.upm.edu.my/id/eprint/23573/1/Spatial%20aspect%20of%20surface%20water%20quality%20using%20chemometric%20analysis.pdf
http://psasir.upm.edu.my/id/eprint/23573/
https://www.trisanita.org/
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Summary:Chemometric or multivariate techniques were applied to identify the spatialvariation and pollution sources of Jakara River Kano-Nigeria. Thirty water sampleswere collected: twenty three along River Getsi and seven surface water samples alongthe main channel River Jakara. Twenty three water quality parameters namely: pH,temperature, turbidity, electrical conductivity, dissolve oxygen, biochemical oxygendemand, Fecal Coliform, total solids, nitrates, phosphates, cobalt, iron, nickel,manganese, copper, sodium, potassium, mercury, chromium, cadmium, lead,magnesium, and calcium were analyzed. Hierarchical cluster analysis (CA) groupedthe sampling points into three clusters based on the similarities of river water qualitycharacteristics into industrial, domestic and agricultural water pollution sources.Forward and backward Discriminant analysis (DA) effectively discriminate five andfifteen water quality variables respectively with 100% each correct assigning from theoriginal twenty three variables. PCA/FA were used to investigate the origin of eachwater quality parameters due to various land use activities, seven principalcomponents were obtained with 77.5% total variance, in addition PCA identify threelatent pollution sources convinces to support CA.