Naslov
Spatial characterization of Surface water quality in Kosovo

Autori
Virgjina Lipoveci, Mirjana Čurlin, Marjana Simonič

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Book of abstract Water for all / Habuda Stanić, Mirna - Osijek : Prehrambeno tehnološki fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2019, 122-122

ISBN
978-953-7005-59-7

Skup
8. međunarodni znanstveno-stručni skup: Voda za sve = 8th International Scientific and Professional Conference: Water for all

Mjesto i datum
Osijek, Hrvatska, 21.01.2019. - 22.01.2019

Vrsta sudjelovanja
Poster

Vrsta recenzije
Recenziran

Ključne riječi
spatial characterization, surface water quality, chemometrics, data analysis

Sažetak
In this paper statistical and chemometric data analysis (Factor Analysis and Cluster Analysis) for spatial classification of water quality indicators was performed. The used data for analysis were obtained by measuring the 34 parameters that indicate the quality of the surface water of Ibri river basin in Kosovo, during the year 2017. All parameters were experimentally determined according to standard methods for water analysis in Kosovo Environmental Protection Agency. Ibri river basin has 18 monitoring stations, three of which belongs to the Iber River (Location 1), while the other monitoring stations are positioned at different stations at the rivers: Sitnica (Location 2), Llapi (Location 3), Prishtevka (Location 4), Gracanka (Location 5), Drenica (Location 6) and the river Shtime (Location 7). By applying the chemometric data analysis (FA/PCA) classification for all water quality parameters was identified. Cluster analysis for spatial classifications showed that different locations may be generally grouped into main clusters (groups). The first group consisted of location 1, 3, 7, while second groups consist of location 2 and 6. Location 4 and Location 5 with large distances are separatelly placed and conected with other groups. Routine monitoring programs of the water quality generate complex multidimensional data set. Since, the data obtained had multivariate nature and several of the variables were correlated, multivariate statistical data analysis methods can be used for the interpretation of the data. Multivariate statistical technique for evaluation and interpretation of large complex data set presents a necessity and usefulness for planning program of effective water and human health protection.

Izvorni jezik
Engleski

Znanstvena područja
Kemijsko inženjerstvo, Biotehnologija

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