Assessment of temporal and spatial variations in water quality using multivariate statistical methods: a case study of the Xin'anjiang River, China

作者: Xue Li , Pengjing Li , Dong Wang , Yuqiu Wang

DOI: 10.1007/S11783-014-0736-Z

关键词: WastewaterWater qualityPollutionSpatial variabilityPrincipal component analysisSampling (statistics)Environmental scienceSpearman's rank correlation coefficientCorrelation coefficientStatistics

摘要: This study evaluated the temporal and spatial variations of water quality data sets for Xin’anjiang River through use multivariate statistical techniques, including cluster analysis (CA), discriminant (DA), correlation analysis, principal component (PCA). The samples, measured by ten parameters, were collected every month three years (2008–2010) from eight sampling stations located along river. hierarchical CA classified 12 months into periods (First, Second Third Period) sites groups (Groups 1, 2 3) based on seasonal differences various pollution levels caused physicochemical properties anthropogenic activities. DA identified significant parameters (temperature, pH E.coli) to distinguish with close 76% correct assignment. also discovered five electricity conductivity, total nitrogen, chemical oxygen demand phosphorus) variation 80.56% non-parametric coefficient (Spearman R) explained relationship between basin characteristics, GIS made results visual direct. PCA four PCs Groups 1 2, Group 3. These captured 68.94%, 67.48% 70.35% variance 3, respectively. Although natural affects River, main sources included agricultural activities, industrial waste, domestic wastewater.

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