Sojka M, Siepak M, Zioła A, Frankowski M, Murat-Błazejewska S, Siepak J
Subdepartament of Hydrology and Water Resources, August Cieszkowski Agricultural University, Poznań, Poland.
Environ Monit Assess. 2008 Dec;147(1-3):159-70. doi: 10.1007/s10661-007-0107-3. Epub 2007 Dec 27.
The paper presents the results of determinations of physico-chemical parameters of the Mała Wełna waters, a river situated in Wielkopolska voivodeship (Western Poland). Samples for the physico-chemical analysis were taken in eight gauging cross-sections once a month between May and November 2006. To assess the physico-chemical composition of surface water, use was made of multivariate statistical methods of data analysis, viz. cluster analysis (CA), factor analysis (FA), principal components analysis (PCA), and discriminant analysis (DA). They made it possible to observe similarities and differences in the physico-chemical composition of water in the gauging cross-sections, to identify water quality indicators suitable for characterising its temporal and spatial variability, to uncover hidden factors accounting for the structure of the data, and to assess the impact of man-made sources of water pollution.
本文介绍了位于大波兰省(波兰西部)的马瓦韦尔纳河水体理化参数的测定结果。2006年5月至11月期间,每月在八个测量断面采集一次用于理化分析的水样。为评估地表水的理化组成,采用了多元统计数据分析方法,即聚类分析(CA)、因子分析(FA)、主成分分析(PCA)和判别分析(DA)。这些方法使得观察测量断面水体理化组成的异同、识别适合表征其时空变异性的水质指标、揭示数据结构背后的隐藏因素以及评估人为水污染来源的影响成为可能。