Multivariate Analysis of Water Quality Measurements on the Danube River

This study investigates the potential of using principal component analysis and other multivariate analysis techniques to evaluate water quality data gathered from natural watercourses. With this goal in mind, a comprehensive water quality data set was used for the analysis, gathered on a reach of t...

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Bibliographic Details
Published in:Water (Basel) 2021-12, Vol.13 (24), p.3634
Main Authors: Horvat, Zoltan, Horvat, Mirjana, Pastor, Kristian, Bursić, Vojislava, Puvača, Nikola
Format: Article
Language:English
Subjects:
Alluvial rivers
Chlorophyll
Clustering
Cross-sections
Data analysis
Hydraulics
Investigations
Multivariate analysis
Natural watercourses
Position measurement
Principal components analysis
Rivers
Sampling
Sediment transport
Statistical analysis
Unsteady flow
Water analysis
Water circulation
Water column
Water quality
Water quality measurements
Watercourses
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Summary:This study investigates the potential of using principal component analysis and other multivariate analysis techniques to evaluate water quality data gathered from natural watercourses. With this goal in mind, a comprehensive water quality data set was used for the analysis, gathered on a reach of the Danube River in 2011. The considered measurements included physical, chemical, and biological parameters. The data were collected within seven data ranges (cross-sections) of the Danube River. Each cross-section had five verticals, each of which had five sampling points distributed over the water column. The gathered water quality data was then subjected to several multivariate analysis techniques. However, the most attention was attributed to the principal component analysis since it can provide an insight into possible grouping tendencies within verticals, cross-sections, or the entire considered reach. It has been concluded that there is no stratification in any of the analyzed water columns. However, there was an unambiguous clustering of sampling points with respect to their cross-sections. Even though one can attribute these phenomena to the unsteady flow in rivers, additional considerations suggest that the position of a cross-section can have a significant impact on the measured water quality parameters. Furthermore, the presented results indicate that these measurements, combined with several multivariate analysis methods, especially the principal component analysis, may be a promising approach for investigating the water quality tendencies of alluvial rivers.
ISSN:2073-4441
2073-4441
DOI:10.3390/w13243634