Zhao Zhang a,*, Fulu Tao b, Juan Du a, Peijun Shi a,*, Deyong Yu a, Yaobin Meng a, Yu Sun c

a State Key Laboratory of Earth Surface Processes and Resource Ecology, Academy of Disaster Reduction and Emergency Management, Beijing Normal University,

Beijing 100875, China

b Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

c The Center of Disaster Relief and Donation, Bureau of Civil Administration in Hebei Province, Shijiazhuang, 050051, China1

 

Surface water quality and its natural and anthropogenic controls in the Xiangjiang River were investigated using multivariate statistical approaches and a comprehensive observation dataset collected from 2004 to 2008. Cluster analysis (CA) grouped the 15 different sampling stations into five clusters with similar hydrochemistry characteristics and pollution levels. Four principal components (PCs), nutrients, heavy metals, natural components, and organic components, were extracted from the entire dataset. Comparison of the different regional characteristics of these four PCs revealed a decreasing trend for heavy metals and an increasing trend for organic factor on an annual scale, and the seasonal trend was only observed for natural factor. We also conducted analysis of variance (ANOVA) in combination with principal component analysis (PCA) to quantify the relative contribution of spatial and temporal variations to each of the four PCs. The results revealed that 62% of the contributions from the spatial sites were responsible for variations in heavy metals, while 83% of the contributions from the sampling time were responsible for natural variations observed. However, no significant spatial or temporal contributions were found to be responsible for the nutrient and organic variations. Finally, some suggestions regarding water management were put forward based on the current status and future trends of surface water quality in the Xiangjiang River.

 

Study area and surface water quality monitoring sites in Xiangjiang River.

Keywords: Cluster analysis ; Principal component analysis ; Nutrient pollutants ; Heavy metal ; Organic pollutants ; Xiangjiang river