Assessment of the spatial-temporal variation of water quality in Jingyan section of Mangxi River basin using multivariate statistical techniques

The appropriate acquisition and processing of water quality data were crucial for water resource management. In this study, multivariate statistical analyses were performed to the assessment of the spatial-temporal variation on water quality in Jingyan section of Mangxi River basin (China). The 3 main assessment indicators of water pollutants, including COD_Mn, NH₃-N and TP were analyzed. Water quality data was collected at 18 sampling sites from different monitoring sections monthly over a two-year period. Based on the similarity of water quality characteristics, 18 sampling sites were divided into 4 groups by cluster analysis (CA). The results showed that the highest levels of pollution were identified in cluster 2, which was consistent with the intensive areas for non-point source emission. In addition, the main reason for the significant difference in the water quality characteristics was the environment of different spatial location. The results illustrate the usefulness of multivariate statistical techniques for analyzing and interpreting complex data sets, identifying pollution sources and understanding variations in water quality.