scholarly journals Application of multivariate statistical analysis in the assessment of surface water quality in Seyfe Lake, Turkey

2014 ◽  
Vol 20 (2) ◽  
pp. 152-163
Author(s):  
KIYMAZ Sultan; KARADAVUT
Keyword(s):  
Water Quality ◽  
Statistical Analysis ◽  
Surface Water ◽  
Multivariate Statistical Analysis ◽  
Surface Water Quality ◽  
Multivariate Statistical

Multivariate statistical analysis for estimating surface water quality in reservoirs

2018 ◽  
Vol 8 (1) ◽  
pp. 52 ◽  
Author(s):  
Matias Bonansea ◽  
Raquel Bazán ◽  
Susana Ferrero ◽  
Claudia Rodríguez ◽  
Claudia Ledesma ◽  
...  
Keyword(s):  
Water Quality ◽  
Statistical Analysis ◽  
Surface Water ◽  
Multivariate Statistical Analysis ◽  
Surface Water Quality ◽  
Multivariate Statistical

scholarly journals Assessment of Surface Water Quality by Using Multivariate Statistical Analysis Techniques: A Case Study of Nhue River, Vietnam

2020 ◽  
Vol 11 (10) ◽  
pp. 488-492
Author(s):  
Nguyen Huu Hue ◽  
◽  
Nguyen Huu Thanh
Keyword(s):  
Water Quality ◽  
Cluster Analysis ◽  
Statistical Analysis ◽  
Surface Water ◽  
Spatial Variability ◽  
Multivariate Statistical Analysis ◽  
Surface Water Quality ◽  
Monitoring Site ◽  
Multivariate Statistical ◽  
Analysis Techniques

The aim of this study is to assess the spatial variability and to determine the main contamination sources in surface water quality of the Nhue River, Viet Nam by using multivariate statistical analysis techniques, including principal component analysis (PCA) and cluster analysis (CA). Eight water quality parameters were measured at 21 sites along the Nhue River and its tributaries during irrigated periods from 2016 to 2019. The spatial variability of water quality in the Nhue River and its tributaries was determined separately from cluster analysis. The result determined two tributaries, including Yen Xa Canal (NT9 monitoring site) and To Lich River (NT3 monitoring site) leading to severe pollution at To Bridge (N4 monitoring site) region in the Nhue River. The PCA determined a reduced number of two principal components that explained 47.75% of the total variation in the data. The first PC indicated that water temperature (WT) and pH are the dominant polluting factors which are attributed to craft villages, domestic sewage and industrial wastewater. Following is nitrate nitrogen NO3¯ in the second PC which is related to fertilizer application in the farms nearby. The results indicated that CA multivariate statistical analysis technique is useful for the assessment of the spatial water quality variability in a river which has a number of tributaries.

Multivariate statistical analysis for estimating surface water quality in reservoirs

2018 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Claudia Ledesma ◽  
Lucio Pinotti ◽  
Raquel Bazan ◽  
Claudia Rodriguez ◽  
Susana Ferrero ◽  
...  
Keyword(s):  
Water Quality ◽  
Statistical Analysis ◽  
Surface Water ◽  
Multivariate Statistical Analysis ◽  
Surface Water Quality ◽  
Multivariate Statistical
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