title: Environmetric modeling and interpretation of river water monitoring data.
abstract: This environmetric study deals with modeling and interpretation of river water monitoring data from the basin of the Saale river and its tributaries the Ilm and the Unstrut. For a period of one year of observation between September 1993 and August 1994 a data set from twelve campaigns at twenty-nine sampling sites from the Saale river and six campaigns from the river Ilm at seven sampling sites and from river Unstrut at ten sampling sites was collected. Twenty-seven chemical and physicochemical properties were measured to estimate the water quality. The application of cluster analysis, principal components analysis, and apportioning modeling on absolute principal components scores revealed important information about the ecological status of the region of interest:identification of two separate patterns of pollution (upper and lower stream of the rivers);identification of six latent factors responsible for the data structure with different content for the two identified pollution patterns; anddetermination of the contribution of each latent factor (source of emission) to the formation of the total concentration of the chemical burden of the river water. As a result more objective ecological policy and decision making is possible.
authors.affiliation: Department of Analytical Chemistry, Faculty of Chemistry, University of Sofia St. Kl. Okhridski, 1164 Sofia, J. Bourchier Blvd. 1, Bulgaria.
authors.forename: V
authors.initials: V
authors.lastname: Simeonov
authors.forename: J W
authors.initials: JW
authors.lastname: Einax
authors.forename: I
authors.initials: I
authors.lastname: Stanimirova
authors.forename: J
authors.initials: J
authors.lastname: Kraft
mesh_terms: D002031:Bulgaria; D016000:Cluster Analysis; D003625:Data Collection; D004784:Environmental Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D005618:Fresh Water / Q000032:analysis*; D005843:Geography; D005858:Germany; D014876:Water Pollution / Q000032:analysis / Q000706:statistics & numerical data