OPEN ACCESS
One of the main challenges of water management in developing countries is to control the impact of the urban environment on the natural environment. Identifying sources of pollution in an urban watershed is a critical first step towards providing more integrated environmental planning, proper wastewater disposal and public water supplying. Thus, in this study we assessed 5-year water quality data from six urban river basins in Southern Brazil. In addition to the principal component analysis (PCA), three indexes were evaluated individually: Water Quality Index (WQI), Toxicity Index (TI) and CCME WQI framework (CCME WQI). In order to evaluate the effect of land use, the monitoring sites were assessed according to the urbanization criteria. The application of PCA revealed the existence of six components, explaining 73.78% of data variation. The component that explains most of the variation in water quality (30.80%) is associated with domestic wastewater. The second component showed a strong dependence (29.44%) on industrial activities such as electroplating and metalworking in determining the water quality, while the other components are related to certain industrial and agricultural activities. Likewise, the application of WQIs demonstrated similar results to the PCA. WQI and TI showed scenarios of concern regarding public supply. CCME WQI presented a significant disparity between the assessed watersheds and the Brazilian legal framework goals. Studies in this field significantly contribute to the establishment of environmental licensing criteria, by demonstrating patterns and environmental features. In addition to it, one can identify which watersheds demand greater attention with respect to control and recovery of proper environmental conditions. Furthermore, it can provide support for revisions in urban and wa- tershed planning, especially in qualitative aspects eluding conflicts over water use in future scenarios.
Caxias do Sul, multivariate analysis, toxicity index, urban waters, water quality index, water resources management
[1] Vega, M., Pardo, R., Barrado, E. & Deban, L., Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32(12), pp. 3581–3592, 1998. DOI: 10.1016/S0043-1354(98)00138-9.
[2] Almeida, M.A.B. & Schwarzbold, A., Avaliação Sazonal da Qualidade das Águas do Arroio da Cria Montenegro, RS com Aplicação de um Índice de Qualidade de Água (IQA). Revista Brasileira de Recursos Hídricos, 8(1), pp. 81–97, 2003. DOI: 10.21168/rbrh.v8n1.p81-97.
[3] Singh, K.P., Basant, A., Malik, A. & Jain, G., Artificial neural network modeling of the river water quality – A case study. Ecological Modelling, 220(6), pp. 888–895, 2009. DOI: 10.1016/j.ecolmodel.2009.01.004.
[4] Bertossi, A.P.A., Cecílio, R.A., Neves, M.A. & Garcia, G.O., Qualidade da água em microbacias hidrográficas com diferentes coberturas do solo no sul do Espirito Santo. Revista Árvore, 37(1), pp. 107–117, 2013. DOI: 10.1590/S1415-43662010000100008.
[5] Toledo, L.G. & Nicolella, G., Índice de qualidade de água em microbacia sob uso agrícola e urbano. Scientia Agricola, 59(1), pp. 181–186, 2002. DOI: 10.2134/jeq1998.00472425002700020006x.
[6] Fan, X., Cui, B., Zhao, H., Zhang, Z. & Zhang, H., Assessment of river water quality in Pearl River Delta using multivariate statistical techniques. Procedia Environmental Sciences, 2, pp. 1220–1234, 2010. DOI: 10.1016/j.proenv.2010.10.133.
[7] Guedes, H.A.S., Silva, D.D., Elesbon, A.A.A., Ribeiro, C.B. M., Matos, A.T. & Soares, J.H.P., Aplicação da análise estatística multivariada no estudo da qualidade da agua do Rio Pomba, MG. Revista Brasileira de Engenharia Agrícola e Ambiental, 15(5), pp. 558–563, 2012. DOI: 10.2134/jeq2004.0337.
[8] Damasceno, M. da C.S., Ribeiro, H.M.C., Takiyama, L.R. & Paula, M.T. Avaliação sazonal da qualidade das águas superficiais do Rio Amazonas na orla da cidade de Macapá, Amapá, Brasil. Revista Ambiente e Água, 10(3), pp. 598–613, 2015. DOI: 10.4136/ambi-agua.1606.
[9] Instituto Brasileiro de Geografia e Estatística (IBGE), Gross domestic product – Brazil 2014, available at http://www.ibge.gov.br/english/estatistica/economia/pibmunicipios/2014/default.shtm, 2014 (accessed 25 August 2017).
[10] Brasil. CONAMA Resolution 357, available at http://www.mma.gov.br/port/conama/res/res05/res35705.pdf, 2005 (accessed 25 August 2017).
[11] Rio Grande do Sul. CRH Resolution 121, available at http://www.sema.rs.gov.br/upload/arquivos/201708/22162317-resolucao-crh-121-2012-aprova-enquadramentoaguas-superficiais-bacia-taquari-antas-07-01-1.pdf, 2012(accessed 25 August 2017).
[12] Rio Grande do Sul. CRH Resolution 50, available at http://www.sema.rs.gov.br/upload/arquivos/201708/22151357-resolucao-crh-50-2008-aprova-enquadramento-das-baciasdos-rios-cai-pardo-tramandai-e-lago-guaiba.pdf, 2008 (accessed 25 August 2017).
[13] Jolliffe, I.T. Principal Component Analysis, Springer-Verlag: New York, NY, 2002.
[14] Wang, X., Cai, Q., Ye, L. & Qu, X., Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques: A case study of the Xiangxi River basin, China. Quaternary International, 282, pp. 137–144, 2012. DOI: 10.1016/j.quaint.2012.05.015.
[15] Coletti, C., Testezlafl, R., Ribeiro, T.A.P., de Souza, R.T.G. & Pereira, D. de A., Water quality index using multivariate factorial analysis. Revista Brasileira de Engenharia Agrícola e Ambiental, 14(5), pp. 517–522, 2009. DOI: 10.1590/S1415-43662010000500009.
[16] Pinto, U. & Maheshwari, B.L., River health assessment in peri-urban landscapes: An application of multivariate analysis to identify the key variables. Water Research, 45(13), pp. 3915–3924, 2011. DOI: 10.1016/j.watres.2011.04.044.
[17] Companhia de Tecnologia de Saneamento Ambiental (CETESB), Relatório Anual de Qualidade das Águas Interiores no Estado de São Paulo, available at http://aguasinteriores.cetesb.sp.gov.br/wp-content/uploads/sites/32/2013/11/02.pdf, 2009 (accessed 25 August 2017).
[18] Von Sperling, M., Princípios do tratamento biológico de águas residuárias: Introdução à qualidade das águas e ao tratamento de esgotos, DESA-UFMG: Belo Horizonte, Brazil, 1996.
[19] Canadian Council of Ministers of the Environment (CCME), Water Quality Index: Technical Report. In: Canadian Water Quality Guidelines for the Protection of Aquatic Life, available at http://www.ccme.ca/files/Resources/calculators/WQI%20User's%20Manual%20(en).pdf, 2001 (accessed 25 August 2017).
[20] Cude, C.G., Oregon Water Quality Index a tool for evaluating water quality management effectiveness. Journal of the American Water Resources Association, 37(1), pp. 125–137, 2001. DOI: 10.1111/j.1752-1688.1978.tb02261.x.
[21] Terrado, M., Barceló, D., Tauler, R., Borrell, E., Campos, S. & Barceló, D. Surface-water-quality indices for the analysis of data generated by automated sampling networks. Trends in Analytical Chemistry, 29(1), pp. 40–52, 2010. DOI: 10.1016/j.trac.2009.10.001.
[22] Hurley, T., Sadiq, R. & Mazumder, A., Adaptation and evaluation of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for use as an effective tool to characterize drinking source water quality. Water Research, 46(11), pp. 3544–3552, 2012. DOI: 10.1016/j.watres.2012.03.061.
[23] Abukila, A.F., Assessing the drain estuaries water quality in response to pollution abatement. Water Science, 29(1), pp. 1–18, 2015. DOI: 10.1016/j.wsj.2015.02.002.
[24] Amaro, C.A., Proposta de um índice para avaliação de conformidade da qualidade dos corpos hídricos ao enquadramento, available at www.teses.usp.br/teses/disponiveis/3/3147/tde-11082009-121147/pt-br.php, 2009 (accessed 25 August 2017).