title: The spatial-temporal variations of water quality in controlling points of the main rivers flowing into the Miyun Reservoir from 1991 to 2011.
abstract: Cluster analysis (CA), discriminant analysis (DA), and principal component analysis/factor analysis (PCA/FA) were used to analyze the interannual, seasonal, and spatial variations of water quality from 1991 to 2011 in controlling points (Xinzhuang Bridge, Daguan Bridge) of the main rivers (Chaohe River, Baihe River) flowing into the Miyun Reservoir. The results demonstrated that total nitrogen (TN) and total phosphorus (TP) exceeded China National Standard II for surface water separately 5.08 times and 1 time. CA showed that the water quality could be divided into three interannual (IA) groups: IAI (1991-1995, 1998), IAII (1996-1997, 1999-2000, 2002-2006), and IAIII (2001, 2007-2011) and two seasonal clusters: dry season 1 (December), dry season 2 (January-February), and non-dry season (March-November). At interannual scale, the higher concentration of SO4 (2-) from industrial activities, atmospheric sedimentation, and fertilizer use in IAIII accelerated dissolution of carbonate, which increased Ca(2+), Mg(2+), total hardness (T-Hard), and total alkalinity (T-Alk). The decreasing trend of CODMn contributed to the establishment of sewage treatment plants and water and soil conservation in the Miyun upstream. The changing trend of NO3 (-)-N indicated increasing non-point pollution load of IAII and effective non-point pollution controlling of IAIII. Only one parameter T in the seasonal scale verified improved non-point pollution controlling. The major pollution in two controlling points was NO3 (-)-N, T-Hard, TN, and other ion pollution (SO4 (2-), F(-), Ca(2+), Mg(2+), T-Hard, T-Alk). Higher concentration of NO3 (-)-N in Xinzhuang and CODMn in Daguan indicated different controlling measures, especially controlling agriculture intensification in Chaohe River to decrease N pollution and decreasing water and soil loss and cage culture in Baihe River to weaken organic pollution. Controlling SO4 (2-) from industrial activity, atmospheric sedimentation and fertilizer use in watershed can effectively control Ca(2+), Mg(2+), T-Hard, and T-Alk.
authors.affiliation: College of Resources Environment and Tourism, Capital Normal University, Beijing, 100048, China.
authors.forename: Dongqing
authors.initials: D
authors.lastname: Li
authors.affiliation: College of Hydroelectricity and Digitalization Engineering, Huazhong University of Science & Technology, Wuhan, 430074, China.
authors.forename: Ji
authors.initials: J
authors.lastname: Liang
authors.affiliation: College of Resources Environment and Tourism, Capital Normal University, Beijing, 100048, China.
authors.forename: Yanming
authors.initials: Y
authors.lastname: Di
authors.affiliation: College of Resources Environment and Tourism, Capital Normal University, Beijing, 100048, China.
authors.forename: Huili
authors.initials: H
authors.lastname: Gong
authors.affiliation: College of Resources Environment and Tourism, Capital Normal University, Beijing, 100048, China. xiaoyucnu@126.com.
authors.forename: Xiaoyu
authors.initials: X
authors.lastname: Guo
mesh_terms: D000383:Agriculture; D002681:China; D016000:Cluster Analysis; D004784:Environmental Monitoring; D005308:Fertilizers / Q000032:analysis; D009584:Nitrogen / Q000032:analysis; D010758:Phosphorus / Q000032:analysis; D025341:Principal Component Analysis; D045483:Rivers / Q000737:chemistry*; D012621:Seasons; D014873:Water Pollutants / Q000032:analysis; D014876:Water Pollution / Q000706:statistics & numerical data*; D060753:Water Quality
chemical_list: D005308:Fertilizers; D014873:Water Pollutants; D010758:Phosphorus; D009584:Nitrogen
keywords: Multivariate statistical methods; Spatial-temporal variations; The Miyun watershed