APPLICATION OF MULITIVARIATE STATISTICAL METHODS FOR ANALYSIS OF PHYSICAL AND CHEMICAL FACTORS IN RESERVOIR WITH SEPARATED PRE-DAM ZONE ON THE BASIS OF THE EXAMPLE OF JEZIORO KOWALSKIE.

In the paper the application of multivariate statistical methods (cluster analysis, principal component analysis, factor analysis, discriminant analysis) for analysis of spatial and temporal variation of physical and chemical parameters along a reservoir was tested. The reservoir studied is a special two-stage reservoir. The choice of representative parameters of water quality and their variability is also presented. The basis for the assessment was the set of data including 15 parameters of water quality sampled once per month. The samples were taken at five measurement control points (MCP) located along Jezioro Kowalskie reservoir. The samples were taken in the period from September 2011 to November 2012. The inundation area of Jezioro Kowalskie reservoir is 2.03 km² (volume 6.58 million m³). The reservoir is located in watershed of the Glowna river. The depth of the aquifer varies between 1.5 m and 6.5 m (near the dam). The analyses performed have shown that multivariate statistical methods enabled effective assessment of water quality. On the other hand, the applied methods may be used for optimization of the measurement network. The use of these statistical methods was found to permit reduction in the number of measurement control points (MCP) and optimize the frequency of sampling. The cluster analysis and the principal component analysis enabled distinction of two groups of measurement control points MCP. The water samples in each group contained similar amount of wastes. The concentrations of chemical indicators in the samples have similar spatial distribution. The concentrations of ammonia, nitrites, phosphates, iron, calcium, chlorides and magnesium presented significant tendency to decrease along the reservoir and they were classified in separate group because of this feature. Additionally, the discriminant analysis enabled the choice of representative parameters most suitable for assessment of temporal and spatial variation of water quality in the reservoir. The factor analysis was used to link the dependencies between the analyzed parameters and processes occurring along the reservoir. [ABSTRACT FROM AUTHOR]