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Use of Multivariate Analytical Methods in Assessment of River Water Quality


Affiliations
1 Department of Civil Engineering, Maharishi Markandeshwar University, Mullana, Ambala-133207, Haryana, India
 

This study is focused on the assessment of water quality of river Satluj in North Indian state of Punjab and evaluation of 34 physico-chemical variables monitored during the period 2015-2016, at 3 different sampling locations. Multivariate analytical techniques, such as Principal Component Analysis (PCA)/ Factor Analysis (FA) were applied to the water quality data set to identify characteristics of water quality in the studied catchment. PCA/FA was applied for source identification to data sets pertaining to 3 spatial groups (upper catchment, middle catchment and lower catchment) responsible for the data structure. These factors are conditionally named soil structure and soil erosion; domestic, municipal and industrial effluents; agricultural activities (fertilizers, livestock waste etc.) and seasonal effect factors. In the current study usefulness of multivariate analysis for evaluation of river Satluj water quality assessment and identification of dominant factors and pollution sources for effective water quality management and determination of spatial and temporal variations in water quality illustrated.

Keywords

Surface Water Quality, Multivariate Statistical Analysis, Satluj River.
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  • Use of Multivariate Analytical Methods in Assessment of River Water Quality

Abstract Views: 115  |  PDF Views: 81

Authors

Siddhartha Sharma
Department of Civil Engineering, Maharishi Markandeshwar University, Mullana, Ambala-133207, Haryana, India

Abstract


This study is focused on the assessment of water quality of river Satluj in North Indian state of Punjab and evaluation of 34 physico-chemical variables monitored during the period 2015-2016, at 3 different sampling locations. Multivariate analytical techniques, such as Principal Component Analysis (PCA)/ Factor Analysis (FA) were applied to the water quality data set to identify characteristics of water quality in the studied catchment. PCA/FA was applied for source identification to data sets pertaining to 3 spatial groups (upper catchment, middle catchment and lower catchment) responsible for the data structure. These factors are conditionally named soil structure and soil erosion; domestic, municipal and industrial effluents; agricultural activities (fertilizers, livestock waste etc.) and seasonal effect factors. In the current study usefulness of multivariate analysis for evaluation of river Satluj water quality assessment and identification of dominant factors and pollution sources for effective water quality management and determination of spatial and temporal variations in water quality illustrated.

Keywords


Surface Water Quality, Multivariate Statistical Analysis, Satluj River.