Identification of the Spatiotemporal Variability and Pollution Sources for Potential Pollutants of the Malian River Water in Northwest China Using the PCA-APCS-MLR Receptor Model

Identifying potential pollution sources of river water is a basis for effectively improving water pollution and sustainable water quality management. This study presents the analyses of the spatiotemporal variations of 12 water quality parameters from 6 water quality monitoring sections of the Malian River in northwest China. One-way analysis of variance (ANOVA) and cluster analysis (CA) were used to evaluate the changes in the spatiotemporal water quality over the monitoring period spanning from January 2017 to December 2021. The potential pollution sources and their contributions to river water pollution were qualitatively assessed via principal component analysis (PCA), factor analysis (FA), and the absolute principal component score-multiple linear regression (APCS-MLR) analysis. Despite the overall improvement of the water quality from 2017 to 2021, the upstream water quality is generally inferior to the downstream water quality, and is worse in the dry season compared to that in the other seasons. According to the APCS-MLR results, urban domestic-urban runoff and rural sewage contributed 24.08% and 20.10% to the river water pollution, respectively. Agricultural non-point sources, and livestock and poultry breeding, contributed 18.65% and 16.23%, to the river pollution, respectively. This study provides in-depth insights for identifying regional water pollution sources and serves as a reference for water environmental treatment in other similar watersheds in the Chinese Loess Plateau.