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Anthropogenic influences on the water quality of the Baiyangdian Lake in North China over the last decade

Han, Quan, Tong, Runze, Sun, Wenchao, Zhao, Yue, Yu, Jingshan, Wang, Guoqiang, Shrestha, Sangam, Jin, Yongliang
The Science of the total environment 2020 v.701 pp. 134929
ammonium nitrogen, anionic surfactants, anthropogenic activities, arid lands, cluster analysis, data collection, discriminant analysis, dissolved oxygen, ecological footprint, environmental management, factor analysis, fecal bacteria, fluorides, lakes, monitoring, principal component analysis, total nitrogen, total phosphorus, variance, water allocation, water pollution, water quality, water temperature, China
Baiyangdian Lake, the largest shallow lake in the North China Plain, is essential for maintaining ecosystem functioning in this highly populated region. To explore the influences of human activities on the lake’s water quality, an improved Water Quality Index (WQI) method and multivariate statistical techniques were adopted to assess the temporal and spatial variations of the lake’s water quality and explore the dominant factors of these variations. Datasets for 11 water quality parameters from six monitoring stations were used to evaluate the period spanning from 2006 to 2016. Assessment of the annual WQI showed that the water quality of the lake has generally improved over the past decade. Cluster analysis divided 12 months into the dry and wet periods and the six monitoring stations into those located in the western and eastern parts of the lake. Discriminant analysis demonstrated that with only two parameters (water temperature and fluoride) and six parameters (dissolved oxygen, ammonia nitrogen, total nitrogen, total phosphorus, anionic surfactant, and fecal coliform), 96.0% and 93.8% of the water quality data can be classified into the correct spatial and temporal clusters, respectively. For the principal component analysis and factor analysis, the varifactors detected for the two temporal clusters were similar, and varifactors related to pollution explained more variance in the water quality variation than the ones representing natural factors. For the two spatial clusters, the varifactors were different, indicating they are influenced by different types of anthropogenic activities. Correlation analysis between lake water level and water quality indicated that environmental water allocation to the lake generally improve water quality. These findings provide a more thorough understanding of driving mechanism of water quality and may be helpful for making environmental management decisions in Baiyangdian Lake and other large, shallow lakes in highly populated dryland regions.