scholarly journals Assessment of Best-Management Practice Effects on Rangeland Stream Water Quality Using Multivariate Statistical Techniques

2009 ◽  
Vol 62 (4) ◽  
pp. 371-386 ◽  
Author(s):  
Christopher A. Ellison ◽  
Quentin D. Skinner ◽  
Larry S. Hicks
Keyword(s):  
Water Quality ◽  
Management Practice ◽  
Stream Water ◽  
Best Management Practice ◽  
Practice Effects ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Stream Water Quality ◽  
Multivariate Statistical ◽  
Best Management

Multivariate Analysis of Paired Watershed Data to Evaluate Agricultural Best Management Practice Effects on Stream Water Phosphorus

2005 ◽  
Vol 34 (3) ◽  
pp. 1087-1101 ◽  
Author(s):  
Patricia L. Bishop ◽  
W. Dean Hively ◽  
Jery R. Stedinger ◽  
Michael R. Rafferty ◽  
Jeffrey L. Lojpersberger ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Management Practice ◽  
Stream Water ◽  
Best Management Practice ◽  
Practice Effects ◽  
Best Management ◽  
Paired Watershed

scholarly journals Evaluation of the Swat River, Northern Pakistan, water quality using multivariate statistical techniques and water quality index (WQI) model

2020 ◽  
Vol 27 (31) ◽  
pp. 38545-38558 ◽  
Author(s):  
Shah Jehan ◽  
Ihsan Ullah ◽  
Sardar Khan ◽  
Said Muhammad ◽  
Seema Anjum Khattak ◽  
...  
Keyword(s):  
Water Quality ◽  
Health Risk ◽  
Physicochemical Parameters ◽  
Quality Index ◽  
Statistical Techniques ◽  
Northern Pakistan ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Poor Water Quality ◽  
Swat River

Abstract This study evaluates the characteristics of water along the Swat River, Northern Pakistan. For this purpose, water samples (n = 30) were collected and analyzed for physicochemical parameters including heavy metals (HM). The mean concentrations of physicochemical parameters and HM were within the drinking water guideline values set by the World Health Organization (WHO 2011) except 34%, 60%, and 56% of copper (Cu), nickel (Ni), and lead (Pb), respectively. Pollution sources were identified by various multivariate statistical techniques including correlation analysis (CA) and principal component analysis (PCA) indicating different origins both naturally and anthropogenically. Results of the water quality index (WQI) ranged from 13.58 to 209 with an average value of 77 suggesting poor water quality for drinking and domestic purposes. The poor water quality was mainly related to high sodium (alkalinity) and salinity hazards showing > 27% and 20% water samples have poor alkalinity and salinity hazards, respectively. Hazard quotient (HQ) and hazard index (HI) were used to determine the health risk of HM in the study area. For water-related health risk, HQingestion, HQdermal, and HI values were > 1, indicating noncarcinogenic health risk (NCR) posed by these HM to the exposed population.

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