Multivariate analysis of the Hong Kong Victoria Harbour water quality data

Two multivariate techniques (principal components analysis and cluster analysis) are used to analyse Hong Kong Victoria Harbour water quality data. Results show that the sampling stations can be divided into four main groups, which is consistent with the tripartite structure obtained from an environmental approach. Moreover, it is found that the groups produced can be interpreted based on two main features of the data: nutrient level and the algae-faecal pollution.