Application of Multivariate Statistical Techniques and Water Quality Index to Assess Surface Water Quality: A Case Study of Zhaojiaxi River, China

The water quality in Zhaojiaxi River basin (China) was investigated in terms of water quality index (WQI) and multivariate statistical techniques including factor analysis (FA) and cluster analysis (CA). The main purpose was to see the current pollution status and identify the main problems faced to environmental managers. The dataset consisted of 12 parameters at four different stations (accounting for a total of 1440 observations) from a one-year survey on a monthly basis. The FA identified nine key variables under three varifactors (VFs), which indicated 64% variance in the water quality dataset. Variables in the first, second and third VFs indicated dissolved organic pollution and the effect of eutrophication in the Zhaojiaxi River. The relationships among 12 sampling months were highlighted by CA and represented in a dendrogram to categorise different contamination levels. On the other hand, the WQI in winter and spring was higher that other times. The WQI value was 86.14 at downstream and higher than other sampling stations indicating that the self-purification function of Zhaojiaxi River was healthy. This study presents that the combination of WQI and multivariate statistical techniques can help to manage river systems integrally and effectively.