Multivariate Analysis of Water Quality Measurements on the Danube River
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Other documents of the author: Horvat, Zoltan; Horvat, Mirjana; Pastor, Kristian; Bursic, Vojislava; Puvača, Nikola
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Title
Multivariate Analysis of Water Quality Measurements on the Danube RiverDate
2021-12-17Publisher
MDPIBibliographic citation
Horvat, Z.; Horvat, M.; Pastor, K.; Bursi´c, V.; Puvaˇca, N. Multivariate Analysis of Water Quality Measurements on the Danube River. Water 2021, 13, 3634. https://doi.org/10.3390/w13243634Type
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Abstract
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 ... [+]
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. [-]
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Water 2021, 13(24)Funder Name
Ministry of Education, Science and Technological Development, Republic of Serbia
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451-03-9/2021-14/200093 | 451-03-9/2021-14/200134
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Except where otherwise noted, this item's license is described as © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).