title: [Identification of spatio-temporal variation in the seaside water quality along Macau Peninsula].
abstract: Cluster analysis (CA) and discriminant analysis (DA) were coupled to identify the spatial and temporal variation of the seaside water quality for 14 parameters and 22 different sites along Macau Peninsula, so as to identify the temporal and spatial variation for further optimizing the monitoring network and controlling the seaside water quality along Macau Peninsula. The results show that 12 months could be grouped into two periods, June-September and the remaining months, and the entire area was divided into two clusters, one located at western sides of Macau Peninsula, and another one is in southeast and southern sides of the Macau peninsula. Through backward stepwise DA, pH, Cl-, TSS, color and TP, Cl-, color, NH4+, DO, COD were identified as the discriminant variables of spatial and temporal variation, with 84.82% and 76.57% correct assignments, respectively. This study illustrates the application of multivariate statistical techniques is beneficial for understanding the temporal and spatial variation of seaside water quality and further effective water quality management.
authors.affiliation: Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084, China
authors.forename: Man-him
authors.initials: MH
authors.lastname: Ho
authors.forename: Jin-liang
authors.initials: JL
authors.lastname: Huang
mesh_terms: D016000:Cluster Analysis; D004784:Environmental Monitoring / Q000379:methods*; D008256:Macau; D025341:Principal Component Analysis; D012623:Seawater / Q000032:analysis*; D013997:Time Factors; D014873:Water Pollutants / Q000032:analysis*
chemical_list: D014873:Water Pollutants