The aim of this article is to evaluate the quality of the Danube River in its course through Serbia as well as to demonstrate the possibilities for using three statistical methods: Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA) in the surface water quality management. Given that the Danube is an important trans-boundary river, thorough water quality monitoring by sampling at different distances during shorter and longer periods of time is not only ecological, but also a political issue. Monitoring was carried out at monthly intervals from January to December 2011, at 17 sampling sites. The obtained data set was treated by multivariate techniques in order, firstly, to identify the similarities and differences between sampling periods and locations, secondly, to recognize variables that affect the temporal and spatial water quality changes and thirdly, to present the anthropogenic impact on water quality parameters.
In the study suitability of water quality index approach and environmetric methods in fi ngerprinting heavy metal pollution as well as comparison of spatial variability of multiple contaminants in surface water were assessed in the case of The Gediz River Basin, Turkey. Water quality variables were categorized into two classes using factor and cluster analysis. Furthermore, soil contamination index was adapted to water pollution index and used to fi nd out the relative relationship between the reference standards and the current situation of heavy metal contamination in water. Results revealed that surface water heavy metal content was mainly governed by metal processing, textile and tannery industries in the region. On the other hand, metal processing industry discharges mainly degraded quality of water in Kemalpasa and Menemen. Furthermore, Kemalpasa region has been heavily affected from tannery and textile industries effl uents. Moreover, pollution parameters have not been infl uenced by changes in physical factors (discharge and temperature). This study indicated the effectiveness of water quality index approach and statistical tools in fi ngerprinting of pollution and comparative assessment of water quality. Both methods can assist decision makers to determine priorities in management practices.
The paper discusses possible applications of the percolation theory in analysis of the microstructure images of polycrystalline materials. Until now, practical use of this theory in metallographic studies has been an almost unprecedented practice. Observation of structures so intricate with the help of this tool is far from the current field of its application. Due to the complexity of the problem itself, modern computer programmes related with the image processing and analysis have been used. To enable practical implementation of the task previously established, an original software has been created. Based on cluster analysis, it is used for the determination of percolation phenomena in the examined materials. For comparative testing, two two-phase materials composed of phases of the same type (ADI matrix and duplex stainless steel) were chosen. Both materials have an austenitic - ferritic structure. The result of metallographic image analysis using a proprietary PERKOLACJA.EXE computer programme was the determination of the content of individual phases within the examined area and of the number of clusters formed by these phases. The outcome of the study is statistical information, which explains and helps in better understanding of the planar images and real spatial arrangement of the examined material structure. The results obtained are expected to assist future determination of the effect that the internal structure of two-phase materials may have on a relationship between the spatial structure and mechanical properties.