Assessment of temporal and spatial variations in surface water quality using multivariate statistical techniques: A case study of Nenjiang River basin, China

Assessment of temporal and spatial variations in surface water quality is important to evaluate the health of a watershed and make necessary management decisions to control current and future pollution of receiving water bodies. In this work, surface water quality data for 12 physical and chemical parameters collected from 10 sampling sites in the Nenjiang River basin during the years (2012–2013) were analyzed. The results show that river water quality has significant temporal and spatial variations. Hierarchical cluster analysis (HCA) grouped 12 months into three periods (LF, MF and HF) and classified 10 monitoring sites into three regions (LP, MP and HP) based on the similarity of water quality characteristics. The principle component analysis (PCA)/factor analysis (FA) was used to recognize the factors or origins responsible for temporal and spatial water quality variations. Temporal and spatial PCA/FA revealed that the Nenjiang River water chemistry was strongly affected by rock/water interaction, hydrologic processes and anthropogenic activities. This work demonstrates that the application of HCA and PCA/FA has achieved meaningful classification based on temporal and spatial criteria.