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Article

Multivariate Analysis of Water Quality Measurements on the Danube River

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Faculty of Civil Engineering Subotica, University of Novi Sad, Kozaracka 2a, 24000 Subotica, Serbia
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Faculty of Technology Novi Sad, University of Novi Sad, Bulevar cara Lazara 1, 21000 Novi Sad, Serbia
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Faculty of Agriculture, University of Novi Sad, Trg Dositeja Obradovića 8, 21000 Novi Sad, Serbia
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Faculty of Health, Jaume I University, Avinguda de Vicent Sos Baynat, s/n, 12071 Castelló de la Plana, Spain
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Department of Engineering Management in Biotechnology, Faculty of Economics and Engineering Management in Novi Sad, University Business Academy in Novi Sad, Cvećarska 2, 21000 Novi Sad, Serbia
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Author to whom correspondence should be addressed.
Academic Editor: Thomas M. Missimer
Water 2021, 13(24), 3634; https://doi.org/10.3390/w13243634
Received: 16 November 2021 / Revised: 15 December 2021 / Accepted: 16 December 2021 / Published: 17 December 2021
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. View Full-Text
Keywords: multivariate analysis; principal component analysis; alluvial rivers; Danube River; water quality multivariate analysis; principal component analysis; alluvial rivers; Danube River; water quality
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MDPI and ACS Style

Horvat, Z.; Horvat, M.; Pastor, K.; Bursić, V.; Puvača, N. Multivariate Analysis of Water Quality Measurements on the Danube River. Water 2021, 13, 3634. https://doi.org/10.3390/w13243634

AMA Style

Horvat Z, Horvat M, Pastor K, Bursić V, Puvača N. Multivariate Analysis of Water Quality Measurements on the Danube River. Water. 2021; 13(24):3634. https://doi.org/10.3390/w13243634

Chicago/Turabian Style

Horvat, Zoltan, Mirjana Horvat, Kristian Pastor, Vojislava Bursić, and Nikola Puvača. 2021. "Multivariate Analysis of Water Quality Measurements on the Danube River" Water 13, no. 24: 3634. https://doi.org/10.3390/w13243634

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