Abstract
This study presents the application of multivariate statistical tools for the evaluation of spatial variations and the interpretation of water quality data obtained in a monitoring program of Lis river basin surface water, Portugal. Twenty-seven physicochemical and microbiological parameters were determined in six water sampling campaigns at 16 monitoring sites during the period from September 2003 to November 2006. Correlation analysis, principal component analysis, and cluster analysis were performed to evaluate the main water pollution sources and to characterize the spatial distribution of water pollution profiles in river basin. The results achieved with the statistical methodologies led to distinguish natural and anthropogenic pollution sources. Additionally, monitoring sites with similar water pollution profile were identified, indicating that some monitoring locations can be changed to improve the spatial characterization of water quality in the river basin. CBO, CQO, P, and N were identified as significant variables affecting spatial variations, namely in the Lis river middle reach. Besides the identification of main pollution sources, the applied statistical tools were able to identify spatial patterns of water pollution in Lis river basin, which further helps in the reassessment of the number and location of monitoring sites.
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Acknowledgments
Financial support for this work was provided by project PEst-C/EQB/LA0020/2011, financed by FEDER through COMPETE—Programa Operacional Factores de Competitividade, and by FCT—Fundação para a Ciência e a Tecnologia. Judite S. Vieira acknowledges financial support PRODEP program (2003/2006). José C.M. Pires acknowledges his post-doctoral fellowship (SFRH/BPD/66721/2009) supported by the Portuguese Foundation for Science and Technology (FCT), POPH-QREN, and FSE. V. Vilar acknowledges Ciência 2008 Program.
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Vieira, J.S., Pires, J.C.M., Martins, F.G. et al. Surface Water Quality Assessment of Lis River Using Multivariate Statistical Methods. Water Air Soil Pollut 223, 5549–5561 (2012). https://doi.org/10.1007/s11270-012-1267-5
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DOI: https://doi.org/10.1007/s11270-012-1267-5