Abstract
The Velhas River sub-basin, which is located in the third-largest river basin in Brazil (São Francisco), is in an advanced state of degradation. In this work, the surface water quality of the Velhas River Basin was studied at 65 monitoring sites; 16 water quality parameters were sampled quarterly for 11 years (2008 to 2013). Cluster analysis (CA) and a nonparametric Kruskal–Wallis test were associated with the analysis of violations to water quality standards to interpret the water quality data set from the Velhas River Basin and assess its spatial variations. The CA grouped the 65 monitoring sites into four groups. The Kruskal–Wallis test identified significant differences (p < 0.05) between the groups formed by CA. The results show that watercourses located in the upper region of the Velhas River Basin are more affected by the release of industrial effluent and domestic sewage, and the lower region is more affected by diffuse pollution and erosion. This association between multivariate statistical techniques and nonparametric tests was effective for the classification and processing of large water quality datasets and the identification of major differences between water pollution sources in the basin. Therefore, these results provide an understanding of the factors affecting water quality in the Velhas River Basin. The results can aid in decision-making by water managers and these methods can be applied to other river basins.
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Achieng’, A. O., Raburu, P. O., Kipkorir, E. C., Ngodhe, S. O., Obiero, K. O., & Ani-Sabwa, J. (2017). Assessment of water quality using multivariate techniques in River Sosiani, Kenya. Environmental Monitoring and Assessment, 189, 1–13. https://doi.org/10.1007/s10661-017-5992-5.
Agência Nacional De Águas – ANA. (2013). Cuidando das águas: soluções para melhorar a qualidade dos recursos hídricos, second ed. ANA, Brasília. Accessed 25 June 2017.
Agência Nacional De Águas – ANA. (2015). Conjuntura dos Recursos Hídricos no Brasil: regiões hidrográficas brasileiras, special ed. Superintendência de Planejamento de Recursos Hídricos, Brasília. Accessed 25 June 2017.
Alkarkhi, A., Ahmad, A., Ismail, N., Easa, A., Omar, K. (2008). Assessment of surface water through multivariate analysis. Journal of Sustainable Development, 1(3), 27–33.
Almeida, K.C.B. (2013). Avaliação da rede de monitoramento de qualidade das águas superficiais da Bacia do Rio das Velhas utilizando o método da entropia. Universidade Federal de Minas Gerais. http://www.smarh.eng.ufmg.br/defesas/1042M.PDF. Accessed 01 January 2017.
APHA, AWWA, WEF. (2012). Standard methods for examination of water and wastewater (22nd ed.). Washington: American Public Health Association 1360p.
Bhat, S. A., Meraj, G., Yaseen, S., & Pandit, A. K. (2014). Statistical assessment of water quality parameters for pollution source identification in Suknag Stream: an inflow stream of Lake Wular (Ramsar Site), Kashmir Himalaya. Journal of Ecosystems, 18, 1–18. https://doi.org/10.1155/2014/898054.
Calazans, G. M., Pinto, C. C., Costa, E. P., Perini, A. F., & Oliveira, S. C. (2018). Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin, Brazil. Environmental Monitoring and Assessment, 190(12), 2–15. https://doi.org/10.1007/s10661-018-7099-z.
Comitê da Bacia Hidrográfica do Rio das Velhas – CBH Velhas. (2014). Análise integrada, articulação e compatibilização dos interesses internos e externos, cenários e prognósticos: relatório 03, revisão 02 – atualização do plano diretor de recursos hídricos da bacia hidrográfica do rio das Velhas.
Comitê da Bacia Hidrografica do Rio das Velhas – CBH Velhas. (2018). A Bacia. Disponível em < http://cbhvelhas.org.br/a-bacia-hidrografica-do-rio-das-velhas/>. Acesso em: 10 dez. 2018.
Conselho Estadual de Meio Ambiente/Conselho Estadual de Recursos Hídricos (COPAM/CERH-MG). (2008). Deliberação Normativa Conjunta COPAM/CERH-MG n°01, de 05 de maio de 2008. Brazil. http://www.siam.mg. gov.br/sla/download.pdf?idNorma=8151. Accessed 15 June 2017.
Costa, E. P., Pinto, C. C., Soares, A. L. C., Melo, L. D. V., & Oliveira, S. C. (2017). Evaluation of violations in water quality standards in the monitoring network of São Francisco River basin, the third largest in Brazil. Environmental Monitoring and Assessment, 189(11), 2–16. https://doi.org/10.1007/s10661-017-6266-y.
Finotti, A. R., Finkler, R., Silva, M. D., & Cemim, G. (2009). Monitoramento de Recursos Hídricos em Áreas Urbanas (1st ed.). Rio Grande do Sul: Educs.
Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. (2009). Análise Multivariada de dados (6th ed.). Porto Alegre: Book.
Instituto Mineiro de Gestão das Águas – IGAM. (2013a). Monitoramento da Qualidade das Águas Superficiais no Estado de Minas Gerais: relatório trimestral (2° trimestre de 2013). Accessed 20 May 2018.
Instituto Mineiro de Gestão das Águas – IGAM. (2013b). Identificação de municípios com condição crítica para a qualidade de água na bacia do rio das Velhas. Belo Horizonte. Accessed 16 June 2017.
Instituto Mineiro de Gestão das Águas – IGAM. (2014). Monitoramento da Qualidade das Águas Superficiais no Estado de Minas Gerais (2º trimestre de 2014). Accessed 20 May 2018.
Johnson, R. A., & Wichern, D. W. (2007). Applied multivariate statistical analysis (sixth ed.). New Jersey: Pearson.
Knupp, E.A.N. (2007). Usos de métodos estatísticos para dados de qualidade de águas: estudo de caso, rio das Velhas. Universidade Federal de Minas Gerais. http://www.repositorio.cdtn.br:8080/bitstream/123456789/908/1/Tese_Eliana_ANonato.pdf. Accessed 21 December 2016.
Lattin, J., Carroll, J. D., & Green, P. E. (2011). Análise de Dados Multivariados (1st ed.). São Paulo: Cengage Learning.
Lee, H., Chan, Z., Graylee, K., Kajenthira, A., Martínez, D., & Roman, A. (2014). Challenge and response in the São Francisco River basin. Water Policy, 16(S1), 153–200. https://doi.org/10.2166/wp.2014.007.
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. The Science of Total Environment, 313, 77–89.
Mendiguchía, C., Moreno, C., Galindo-Riano, M. D., & Garcia-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. https://doi.org/10.1016/j.aca.2004.01.058.
Naghettini, M., & Pinto, E. J. A. (2007). Hidrologia Estatística (1st ed.). Belo Horizonte: CPRM.
Oliveira, S. C., Pinto, C. C., Soares, A. L. C., Costa, E. P. (2018). Avaliação da qualidade de água em 14 anos de monitoramento da porção mineira da bacia do rio São Francisco. II Simpósio da Bacia Hidrográfica do Rio São Francisco - Desafios da Ciência para um novo Velho Chico, Sergipe, Brasil.
Panda, U. C., Sundaray, S. K., Rath, P., Nayak, B. B., & Bhatta, D. (2006). Application of factor and cluster analysis for characterization of river and estuarine water systems – a case study: Mahanadi River (India). Journal of Hydrology, 331(3–4), 434–445. https://doi.org/10.1016/j.jhydrol.2006.05.029.
Park, S. Y., Choi, J. H., Wang, S., & Park, S. S. (2006). Design of a water quality monitoring network in a large river system using the genetic algorithm. Ecological Modelling, 199, 289–297. https://doi.org/10.1016/j.ecolmodel.2006.06.002.
Phung, D., Huang, C., Rutherford, S., Dwirahmadi, F., Chu, C., Wang, X., Nguyen, M., Nguyen, N. H., Do, C. M., Nguyen, T. H., & Dinh, T. A. D. (2015). Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam. Environmental Monitoring and Assessment, 187, 1–13. https://doi.org/10.1007/s10661-015-4474-x.
Pinto, C. C., Almeida, K. B., & Oliveira, S. C. (2018). Avaliação espacial da qualidade das águas da calha do rio das Velhas, estado de Minas Gerais. Tchê Química, 15(30), 75–86.
Reghunath, R., Sreedhara Murthy, T. R., Raghavan, B. R. (2002). The utility of multivariate statistical techniques in hydrogeochemical studies: an example from Karnataka, India. Water Research, 36(10), 2437–2442.
Schwertmana, N. C., Owensa, M. A., & Adnanb, R. (2004). A simple more general boxplot method for identifying outliers. Computational Statistics & Data Analysis, 47(1), 165–174. https://doi.org/10.1016/j.csda.2003.10.012.
Secretaria do Estado do Meio Ambiente e Desenvolvimento Sustentável de Minas Gerais – SEMAD. (2006). Aperfeiçoamento do monitoramento da qualidade das águas da Bacia do Alto Curso do Rio das Velhas. Accessed 10 June 2017.
Sistema Nacional de Informações sobre Saneamento - SNIS. (2017). Diagnóstico dos serviços de água e esgotos - 2015. Brasília: SNSA/MCIDADES, 212p.
Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality. Biometrika, 52, 591–599.
Shrestha, S., & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji River Basin, Japan. Environmental Modeling and Software, 22(4), 464–475. https://doi.org/10.1016/j.envsoft.2006.02.001.
Simeonova, V., Stratis, J. A., Samara, C., Zachariadis, G., Voutsa, D., Anthemidis, A., Sofoniou, M., & Kouimtzis, T. (2003). Assessment of the surface water quality in Northern Greece. Water Research, 37(17), 4119–4124. https://doi.org/10.1016/S0043-1354(03)00398-1.
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, 3980–3992. https://doi.org/10.1016/j.watres.2004.06.011.
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. https://doi.org/10.1016/j.aca.2005.02.006.
Sojka, M., Siepak, M., Ziola, A., Frankowski, M., Murat-Blażejewska, S., & Siepak, J. (2008). Application of multivariate statistical techniques to evaluation of water quality in the MalaWelna River (Western Poland). Environmental Monitoring and Assessment, 147, 159–170. https://doi.org/10.1007/s10661-007-0107-3.
Strobl, R. O., & Robillard, P. D. (2008). Network design for water quality monitoring of surface freshwaters: a review. Journal of Environmental Management, 87(4), 639–648.
Trindade, A.L.C. (2013). Aplicação de técnicas estatísticas para avaliação de dados de monitoramento de qualidade das águas superficiais da porção mineira da Bacia do Rio São Francisco. Universidade Federal de Minas Gerais. http://www.smarh.eng.ufmg.br/defesas/1037M.PDF. Accessed 18 June 2018.
Trindade, A. L. C., Almeida, K. C. B., Barbosa, P. E., & Oliveira, S. M. A. C. (2017). Tendências temporais e espaciais da qualidade das águas superficiais da sub-bacia do rio das Velhas, estado de Minas Gerais. Engenharia Sanitária e Ambiental, 22, 13–24. https://doi.org/10.1590/s1413-41522016131457.
Varol, M., Gökot, B., Bekleyen, A., & Şen, B. (2012). Spatial and temporal variations in surface water quality of the dam reservoirs in the Tigris River Basin, Turkey. Catena, 92, 11–21. https://doi.org/10.1016/j.catena.2011.11.013.
Vega, M., Pardo, R., Barrado, E., & Deban, L. (1998). Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32(12), 3581–3592. https://doi.org/10.1016/S0043-1354(98)00138-9.
Wunderlin, D. A., Pilar, D. M., Valeria, A. M., Fabiana, P. S., Cecilia, H. A., & Bistoni, M. A. (2001). Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. Water Research, 35(12), 2881–2894. https://doi.org/10.1016/S0043-1354(00)00592-3.
Zhang, X., Wang, Q., Liu, Y., Wu, J., & Yu, M. (2011). Application of multivariate statistical techniques in the assessment of water quality in the Southwest New Territories and Kowloon, Hong Kong. Environmental Monitoring and Assessment, 173(1–4), 17–27. https://doi.org/10.1007/s10661-010-1366-y.
Acknowledgements
We would like to thank the Institute of Water Management ofMinas Gerais (Igam) and its technical team for providing the monitoring data and for the constant support and service.
Funding
This study received financial supports from the National Counsel of Technological and Scientific Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES), and the Foundation of Support Research of the State of Minas Gerais (FAPEMIG).
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Pinto, C.C., Calazans, G.M. & Oliveira, S.C. Assessment of spatial variations in the surface water quality of the Velhas River Basin, Brazil, using multivariate statistical analysis and nonparametric statistics. Environ Monit Assess 191, 164 (2019). https://doi.org/10.1007/s10661-019-7281-y
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DOI: https://doi.org/10.1007/s10661-019-7281-y