Multivariate Statistics Applied to the Identification of Compositional Control Parameters for Groundwater
DOI:
https://doi.org/10.11137/1982-3908_2024_47_49797Keywords:
Factorial analysis, Principal component analysis, Hierarchical clusterAbstract
The objective of the present study was to identify the most influent parameters in the composition of groundwater in the municipality of Icapuí, Ceará - Brazil, seeking correlations with the composition of the percolating aquifer formations that can be associated with the sources of these components. For this purpose, multivariate statistical techniques were applied by means of a Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). The PCA allowed a reduction of physicochemical parameters and determined the two components responsible for approximately 86% of total variance in the data for both sampling periods (rainy and dry). The first component is represented by variables that indicate natural rock weathering processes, and the second comprises seasonality and pollution indicators. Samples were also correlated through HCA according to compositional similarities, which were associated with possible natural or human sources.
References
Ado, M., Adeyeye, O., Xiao, C. & Liang, X. 2019, ‘Hydrogeochemistry of Groundwater from Kazaure Area, NW Nigeria using Multivariate Statistics’, E3S Web of Conferences, vol. 98, no. 07001, pp. 6, DOI:10.1051/e3sconf/20199807001.
Bertossi, A.P.A., Menezes, J.P.C., Cecílio, R.A., Garcia, G.O. & Neves, M.A. 2013, ‘Seleção e agrupamento de indicadores da qualidade de águas utilizando Estatística Multivariada’, Semina: Ciências Agrárias, Londrina, vol. 34, no. 5, pp. 2025-36.
Besser, H., Redhaouniab, B., Bedouia, S., Ayadia, Y., Khelifib, F. & Hamedb, Y. 2019, ‘Geochemical, isotopic and statistical monitoring of groundwater quality: Assessment of the potential environmental impacts of the highly polluted CI water in Southwestern Tunisia’, Journal of African Earth Sciences, vol. 153, pp. 144–55, DOI:10.1016/j.jafrearsci.2019.03.001.
Buttafuoco, G., Guagliardi, I., Tarvainen, I. & Jarva, J. 2017, ‘A multivariate approach to study the geochemistry of urban topsoil in the city of Tampere, Finland’, Journal of Geochemical Exploration, vol. 181, pp. 191-204, DOI:10.1016/j.gexplo.2017.07.017.
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, vol. 190, no. 12, e726, DOI:10.1007/s10661-018-7099-z.
Celligoi, A. 1999, ‘Considerações sobre análises químicas de águas subterrâneas’, Geografia (Londrina), vol. 8, no. 1, pp. 91-7, DOI:10.5433/2447-1747.1999v8n1p91.
Dabgerwal, D.K. & Tripathi, S.K. 2016, ‘Assessment of surface water quality using hierarchical cluster analysis’, International Journal of Environment, vol. 5, no. 1., pp. 32-44, DOI:10.3126/ije.v5i1.14563.
Everest, T. & Özcan, H. 2019, ‘Applying multivariate statistics for identification of groundwater resources and qualities in NW Turkey’, Environmental Monitoring and Assessment, vol. 191, no. 47, DOI:10.1007/s10661-018-7165-6.
Ferreira, D.F. 1996, Análise multivariada, Lavras, Minas Gerais.
Fundação Cearense de Meteorologia e Recursos Hídricos – FUNCEME 2021, viewed 17 August 2021, .
Gomes, L.S., Furtado, A.C.R. & Souza, M.C. 2018, ‘A Sílica e suas Particularidades’, Revista Virtual de Química, vol. 10, no. 4, pp. 1018-38, DOI:10.21577/1984-6835.20180072
Gomes, M.C.R. & Cavalcante, I.N. 2017, ‘Aplicação da análise estatística multivariada no estudo da qualidade da água subterrânea’, Revista Águas Subterrâneas, vol. 31, no. 1, pp. 134-49, DOI:10.14295/ras.v31i1.28617.
Gomes, M.C.R., Anjos, J.A.S.A. & Daltro, R.R. 2020, ‘Multivariate statistical analysis applied to the evaluation of groundwater quality in the central-southern portion of the state of Bahia – Brazil’, Revista Ambiente & Água, vol. 15, no. 1, e2408, DOI:10.4136/ambi-agua.2408.
Hair Jr, J.F., Anderson, R.E., Tathan, R.L. & Black, W.C. 1998, Multivariate data analysis, Prentice Hall, New Jersey, 928 p.
Heibati, M., Stedmon, C.A., Stenroth, K., Rauch, S., Toljander, J., Säve-Söderbergh, M. & Murphy, K.R. 2017, ‘Assessment of drinking water quality at the tap using fluorescence spectroscopy’, Water Research, vol. 125, pp. 1-10, DOI:10.1016/j.watres.2017.08.020.
Hounslow, A.W. 1995, Water quality data: analysis and interpretation, Lewis Publishers New York, Boca Raton.
Instituto Brasileiro de Geografia e Estatística – IBGE 2021, viewed 18 June 2021, <http://www.ibge.gov.br>.
Keita, S. & Zhonghua, T. 2017, ‘The assessment of processes controlling the spatial distribution of hydrogeochemical groundwater types in Mali using multivariate statistics’, Journal of African Earth Sciences, vol. 134, pp. 573-89, DOI:10.1016/j.jafrearsci.2017.07.023.
Liu, P., Hoth, N., Drebenstedt, C., Sun, Y. & Xu, Z. 2017, ‘Hydro-geochemical paths of multi-layer groundwater system in coal mining regions - Using multivariate statistics and geochemical modeling approaches’, Science of the Total Environment, vol. 601-602, pp. 1-14, DOI:10.1016/j.scitotenv.2017.05.146.
Maia, S.R.R. 2018, ‘Estudo hidroquímico-ambiental do aquífero costeiro do município de Icapuí – CE’, PhD thesis, Universidade Federal do Ceará.
Mente, A. 2008, ‘A Água Subterrânea no Brasil’, in F.A.C. Feitosa, J. Manoel Filho, E.C. Feitosa, J.G.A. Demetrio, JGA (org.), Hidrogeologia: Conceitos e Aplicações, 3rd. ed. revisada e ampliada, CPRM /LABHID, Rio de Janeiro, pp. 31-48.
Molinari, A., Guadagnini, L., Marcaccio, M. & Guadagnini, A. 2019, ‘Geostatistical multimodel approach for the assessment of the spatial distribution of natural background concentrations in large-scale groundwater bodies’, Water Research, vol. 149, pp. 522-32, DOI:10.1016/j.watres.2018.09.049.
Morais, F., Melo, J.G., Medeiros, J.I., Srivastava, N.K., Diniz Filho, J.B., Lopes, V.L., Oliveira, J.A. & Vasconcelos, M.B. 2005, Comportamento das bacias sedimentares da região semi-árida do Nordeste brasileiro. Avaliação do aquífero Açu na borda sul da bacia Potiguar – Trecho: Upanema-Afonso Bezerra, CPRM/FINEP, Recife.
Reimann, C. & Caritat, P. 1998, Chemical Elements in the Environment: Factsheets for the Geochemist and Environmental Scientist, Springer-Verlag, Berlin, Heidelberg.
Sadler, R., Maetam, B., Edokpolo, B., Connell, D., Yu, J., Stewart, D., Park, M.J., Gray, D. & Laksono, B. 2016, ‘Health risk assessment for exposure to nitrate in drinking water from village wells in Semarang, Indonesia’, Environmental Pollution, vol. 216, pp. 738-45, DOI:10.1016/j.envpol.2016.06.041.
Sousa, D.C. 2002, ‘Litoestratigrafia e deformação Cenozóica na região de Icapuí, Ceará, e implicações para a estruturação de campos de petróleo na borda ocidental da Bacia Potiguar (NE do Brasil) ‘, PhD thesis, Universidade Federal do Rio Grande do Norte.
Tiri, A., Lahbari, N. & Boudoukha, A. 2017, ‘Assessment of the quality of water by hierarchical cluster and variance analyses of the Koudiat Medouar Watershed, East Algeria’, Applied Water Science, vol. 7, pp. 4197-206, DOI:10.1007/s13201-014-0261-z.
Vasconcelos, S.M.S., Teixeira, Z.A. & Alves Neto, J. 2010, ‘Caracterização do aquífero Jandaíra, porção situada no estado do Ceará, Brasil’, Revista de Geologia, vol. 23, no. 1, pp. 50-60.
Villar, P.C. 2016, ‘As águas subterrâneas e o direito à água em um contexto de crise’, Revista Ambiente & Sociedade, vol. 19, pp. 83-102.
World Health Organization - WHO 2011, Guidelines for drinking-water Quality, Genebra.
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