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.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Alves, C. M., Boaventura, R. R. A. R., & Soares, H. M. V. M. (2009). Evaluation of heavy metals pollution loadings in the sediments of the Ave River Basin (Portugal). Soil & Sediment Contamination, 18(5), 603–618.
Decree-Law (1998). Decree-Law no. 236/98—1st August. Ministry of Environment.
EPA (1976). Methodology for the study of urban storm generated pollution and control. In R. E. Wullschleger, A. E. Zanoni, & C. A. Hansen (Eds.), (pp. 326). Cincinnati: U.S. Environmental Protection Agency.
EPER (2004). Registo Europeu das Emissões de Poluentes, Agência Portuguesa do Ambiente.
Figueiredo, D. R., Ferreira, R. V., Cerqueira, M., de Melo, T. C., Pereira, M. J., Castro, B. B., et al. (2012). Impact of water quality on bacterioplankton assemblage along Cértima River Basin (central western Portugal) assessed by PCR–DGGE and multivariate analysis. Environmental Monitoring and Assessment, 184(1), 471–485.
Jarvie, H. P., Whitton, B. A., & Neal, C. (1998). Nitrogen and phosphorous in east-coast British rivers: speciation, sources and biological significance. Science of the Total Environment, 210(211), 79–109.
Kaiser, H. F. (1958). The varimax criterion for analytic rotation in factor analysis. Psychometrica, 23, 187–200.
Liu, C. W., Lin, K. H., & Kuo, Y. M. (2003). Application of factor analysis in the assessment of groundwater quality in a blackfoot disease area in Taiwan. Science of the Total Environment, 313(1–3), 77–89.
Manly, B. F. J. (1994). Multivariate statistical methods—a primer (2nd ed.). London: Chapman and Hall.
McKenna, J. E. (2003). An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modelling & Software, 18, 205–220.
Mendiguchía, C., Moreno, C., Galindo-Riaño, M. D., & García-Vargas, M. (2004). Using chemometric tools to assess anthropogenic effects in river water: a case study: Guadalquivir River (Spain). Analytica Chimica Acta, 515(1), 143–149.
Picado, A., Mendonca, E., Silva, L., Paixao, S. M., Brito, F., Cunha, M. A., et al. (2008). Ecotoxicological assessment of industrial wastewaters in Trancao River Basin (Portugal). Environmental Toxicology, 23(4), 466–472.
Pires, J. C. M., Martins, F. G., Sousa, S. I. V., Alvim-Ferraz, M. C. M., & Pereira, M. C. (2008a). Selection and validation of parameters in multiple linear and principal component regressions. Environmental Modelling & Software, 23, 50–55.
Pires, J. C. M., Sousa, S. I. V., Pereira, M. C., Alvim-Ferraz, M. C. M., & Martins, F. G. (2008b). Management of air quality monitoring using principal component and cluster analysis—part I: SO2 and PM10. Atmospheric Environment, 42(6), 1249–1260.
Pires, J. C. M., Sousa, S. I. V., Pereira, M. C., Alvim-Ferraz, M. C. M., & Martins, F. G. (2008c). Management of air quality monitoring using principal component and cluster analysis—part II: CO, NO2 and O3. Atmospheric Environment, 42(6), 1261–1274.
Pires, J. C. M., Pereira, M. C., Alvim-Ferraz, M. C. M., & Martins, F. G. (2009). Identification of redundant air quality measurements through the use of principal component analysis. Atmospheric Environment, 43, 3837–3842.
Pires, J. C. M., Alvim-Ferraz, M. C. M., Pereira, M. C., & Martins, F. G. (2012). Comparison of several linear statistical models to predict tropospheric ozone concentrations. Journal of Statistical Computation and Simulation, 82(2), 183–192.
Razmkhah, H., Abrishamchi, A., & Torkian, A. (2010). Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: a case study on Jajrood River (Tehran, Iran). Journal of Environmental Management, 91(4), 852–860.
Santos, J. S., Oliveira, E., Bruns, R. E., & Gennari, R. F. (2004). Evaluation of the salt accumulation process during inundation in water resource of Contas river basin (Bahia—Brazil) applying principal component analysis. Water Research, 38(6), 1579–1585.
Sena, R. F. (2005). Avaliação da Biomassa Obtida pela Optimização da Flotação de Efluentes da Indústria de Carnes para Geração de Energia. Florianópolis: Master thesis, Federal University of Santa Catarina.
Shrestha, S., & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji river basin, Japan. Environmental Modelling & Software, 22(4), 464–475.
Singh, K. P., Malik, A., Mohan, D., & Sinha, S. (2004). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Research, 38(18), 3980–3992.
Singh, K. P., Malik, A., & Sinha, S. (2005). Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical techniques: a case study. Analytica Chimica Acta, 538, 355–374.
Soares, H. M. V. M., Boaventura, R. A. R., Machado, A. A. S. C., & da Silva, J. C. G. E. (1999). Sediments as monitors of heavy metal contamination in the Ave river basin (Portugal): multivariate analysis of data. Environmental Pollution, 105(3), 311–323.
Thomann, R. V., & Mueller, J. A. (1987). Principles of surface water quality modelling and control. New York: Harper & Row.
Vega, M., Pardo, R., Barrado, E., & Debán, L. (1998). Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32(12), 3581–3592.
Vieira, J., Fonseca, A., Vilar, V. J. P., Boaventura, R. A. R., & Botelho, C. M. S. (2012a). Water quality in Lis river. Portugal. Environmental Monitoring and Assessment. doi:10.1007/s10661-011-2485-9.
Vieira, J., Fonseca, A., Vilar, V. J. P., Boaventura, R. A. R., & Botelho, C. M. S. (2012b). Water quality modelling of River Lis, Portugal. Environmental Science and Pollution Research. doi:10.1007/s11356-012-1124-5.
Zeng, X., & Rasmussen, T. C. (2005). Multivariate statistical characterization of water quality in Lake Lanier, Georgia, USA. Journal of Environmental Quality, 34, 1980–1991.
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.
About this article
Cite this article
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
- Lis river
- Water quality
- Physicochemical parameters
- Microbiological parameters
- Principal component analysis
- Cluster analysis