Abstract
In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009–2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data.
Highlights
Water quality is assuming great importance with rising pressure on industry, agriculture, and population [1]
self-organising map (SOM) involved 98 output neurons displayed in 14 rows and 7 columns is chosen in this study
Water pollution control and management require the interpretation of a large amount of water quality data, and the data are complex, multidimensional, and nonlinearly related
Summary
Water quality is assuming great importance with rising pressure on industry, agriculture, and population [1]. Surface water is a substantial source for domestic usage, industrial heating, and agricultural irrigation. Since surface water is accessible to human beings, it is the most vulnerable water body to contaminants. The major pollutant sources of surface water include discharges from domestic, industrial and agricultural activities. Runoff transports pollutants in urban areas and agricultural lands to surface water resources, such as rivers and lakes [2]. Due to the complexity and uncertainty involved in surface water interaction mechanism into groundwater, pollutants in surface water appear significant for groundwater quality. The assessment of surface water quality is of great concern in water environmental management
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