AbstractThe Pearl River Delta (PRD) region is one of the most industrialized areas in China, and the river water is increasingly deteriorated due to anthropogenic pollution from the rapid economic development. Principal component analysis (PCA) and cluster analysis (CA) were used to identify characteristics of water quality and to assess water quality spatial pattern in this region. The results of PCA for three regions showed that the first four components of PCA analysis showed 85.52% and 89.25% of the total variance in the data sets of North River region and West River region, respectively, the first three components showed 84.63% of variance for data set of East River region. Results of CA based on the station score of PCA were that stat...
Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), pr...
AbstractThis study investigates the spatial water quality pattern of 13 stations located along the m...
Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis ...
AbstractThe Pearl River Delta (PRD) region is one of the most industrialized areas in China, and the...
In the Duliujian River, 12 water environmental parameters corresponding to 45 sampling sites were an...
The analysis and interpretation the spatiotemporal patterns of river water quality are a critical el...
Thepresent study evaluated the spatial variations of surface water quality in a tropical river using...
Rapid urban development has led to a critical negative impact on water bodies flowing in and around...
AbstractThe classification of river water quality is a useful way of reporting the water quality sta...
AbstractWater quality can be considered a key contributor to both health and disease for humans. Thi...
Principal component analysis (PCA) and multiple linear regressions were applied on the surface water...
Surface water quality is one of the critical environmental concerns of the globe and water quality m...
This study aims to assess the sampling sites and frequencies of sampling of the existing surface wat...
This study estimated spatial and seasonal variation of water quality to understand characteristics o...
This study evaluates the spatial variation of river water quality and identifies major sources of wa...
Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), pr...
AbstractThis study investigates the spatial water quality pattern of 13 stations located along the m...
Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis ...
AbstractThe Pearl River Delta (PRD) region is one of the most industrialized areas in China, and the...
In the Duliujian River, 12 water environmental parameters corresponding to 45 sampling sites were an...
The analysis and interpretation the spatiotemporal patterns of river water quality are a critical el...
Thepresent study evaluated the spatial variations of surface water quality in a tropical river using...
Rapid urban development has led to a critical negative impact on water bodies flowing in and around...
AbstractThe classification of river water quality is a useful way of reporting the water quality sta...
AbstractWater quality can be considered a key contributor to both health and disease for humans. Thi...
Principal component analysis (PCA) and multiple linear regressions were applied on the surface water...
Surface water quality is one of the critical environmental concerns of the globe and water quality m...
This study aims to assess the sampling sites and frequencies of sampling of the existing surface wat...
This study estimated spatial and seasonal variation of water quality to understand characteristics o...
This study evaluates the spatial variation of river water quality and identifies major sources of wa...
Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), pr...
AbstractThis study investigates the spatial water quality pattern of 13 stations located along the m...
Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis ...