Investigation of spatial and seasonal variation of water quality along the mid-Black Sea coast (from Sinop to Ordu) of Turkey, by multivariate statistical techniques

2022 ◽  
pp. 102169
Author(s):  
Sevde Üstün Odabaşi ◽  
Zeynep Ceylan ◽  
İlknur Şentürk ◽  
Feryal Akbal ◽  
Gülfem Bakan ◽  
...  
Keyword(s):  
Water Quality ◽  
Seasonal Variation ◽  
Black Sea ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Spatial And Seasonal Variation ◽  
Black Sea Coast ◽  
Sea Coast

Multivariate Statistical Techniques for the Assessment of Surface Water Quality at the Mid-Black Sea Coast of Turkey

2010 ◽  
Vol 216 (1-4) ◽  
pp. 21-37 ◽  
Author(s):  
Feryal Akbal ◽  
Levent Gürel ◽  
Tolga Bahadır ◽  
İlknur Güler ◽  
Gülfem Bakan ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Black Sea ◽  
Surface Water Quality ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Black Sea Coast ◽  
Sea Coast

Assessment of water quality using different pollution indices and multivariate statistical techniques

2021 ◽  
pp. 165-178
Author(s):  
Vishal Sharma ◽  
Mamta Sharma ◽  
Shevita Pandita ◽  
Vinod Kumar ◽  
Jasmeet Kour ◽  
...  
Keyword(s):  
Water Quality ◽  
Statistical Techniques ◽  
Pollution Indices ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical

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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