Multivariate Statistical Analysis Applied to Water Quality of a Tropical Coastal Lagoon, Cartagena, Colombian Caribbean

https://doi.org/10.22146/ijc.43035

Ildefonso Baldiris-Navarro(1), Juan Carlos Acosta-Jimenez(2), Angel Dario Gonzalez-Delgado(3*), Alvaro Realpe-Jimenez(4), Juan Gabriel Fajardo-Cuadro(5)

(1) SENA CINAFLUP– Cartagena, Cr. A Mamonal #15, Cartagena de Indias, Colombia
(2) Fundacion Universitaria Tecnológico Comfenalco, Cra. 44 #30a-91, 130015, Cartagena de Indias, Colombia
(3) University of Cartagena, Avenida del Consulado, Cll. 30 # 48-152, 130015, Cartagena de Indias, Colombia
(4) University of Cartagena, Avenida del Consulado, Cll. 30 # 48-152, 130015, Cartagena de Indias, Colombia
(5) Universidad Tecnológica de Bolívar, Cra.21 #25-92 Manga, 130001, Cartagena de Indias, Colombia
(*) Corresponding Author

Abstract


Coastal lagoons are one of the most threatened ecosystems in the world, because of population growth, habitat destruction, pollution, wastewater, overexploitation and invasive species which are the main causes of their degradation. The objective of this paper was to evaluate the water quality behavior in a stressed coastal lagoon in Cartagena, Colombian Caribbean. Environmental data was analyzed using hypothesis testing, confidence intervals, and also Principal components analysis (PCA). The study was focused on water parameters such as dissolved oxygen (DO), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), salinity, pH, total dissolved solids, total coliforms (TC), Fecal coliforms (FC), ammonium (NH4+) and total phosphorus (TP). The analysis was conducted in line with the Colombian national water standard. Results showed that BOD5, COD, phosphorus, and coliforms are out of the limits for these variables in Colombia and are reaching levels that may be a threat to human health. Principal components analysis detected five components that explained 79.4% of the variance of data and showed that anthropogenic and temporal factors might be affecting the variation of the parameters.

Keywords


coastal lagoon; water quality; statistics; multivariable analysis; Colombia

Full Text:

Full Text PDF


References

[1] Newton, A., Brito, A.C., Icely, J.D., Derolez, V., Clara, I., Angus, S., Schernewski, G., Inácio, M., Lillebø, A.I., Sousa, A.I., Béjaoui, B., Solidoro, C., Tosic, M., Cañedo-Argüelles, M., Yamamuro, M., Reizopoulou, S., Tseng, H.C., Canu, D., Roselli, L., Maanan, M., Cristina, S., Ruiz-Fernández, A.C., de Lima, R.F., Kjerfve, B., Rubio-Cisneros, N., Pérez-Ruzafa, A., Marcos, C., Pastres, R., Pranovi, F., Snoussi, M., Turpie, J., Tuchkovenko, Y., Dyack, B., Brookes, J., Povilanskas, R., and Khokhlov, V., 2018, Assessing, quantifying and valuing the ecosystem services of coastal lagoons, J. Nat. Conserv., 44, 50–65.

[2] Alves, J.P.H., Fonseca, L.C., Chielle, R.S.A., and Macedo, L.C.B, 2018, Monitoring water quality of the Sergipe River basin: An evaluation using multivariate data analysis, Rev. Bras. Recur. Hídricos., 23, e27.

[3] Anteneh, Y., Zeleke, G., and Gebremariam, E., 2018, Assessment of surface water quality in Legedadie and Dire catchments, Central Ethiopia, using multivariate statistical analysis, Acta Ecol. Sin., 38 (2), 81–95.

[4] Pérez-Ruzafa, A., Marcos, C., and Pérez-Ruzafa, I.M., 2011, Mediterranean coastal lagoons in an ecosystem and aquatic resources management context, Phys. Chem. Earth, 36 (5-6), 160–166.

[5] Alvarez-Vázquez, A., and Olivella-Beltran, R., 2018, Hydraulic simulation of water bodies between the Cabrero’s lagoon and the gates of Chambacú of the city of Cartagena - Colombia, Thesis, University of Cartagena, Colombia.

[6] Baldiris-Navarro, I., Sanchez-Aponte, J., Gonzalez-Delgado, A., Acosta-Jiménez, J.C., and Jiménez, A.R., 2018, Multivariable statistical evaluation of water quality in Juan Polo coastal lagoon (Colombian Caribbean), Contemp. Eng. Sci., 11 (27), 1339–1348.

[7] Azhar, S.C., Aris, A.Z., Yusoff, M.K., Ramli, M.F., and Juahir, H., 2015, Classification of river water quality using multivariate analysis, Procedia Environ. Sci., 30, 79–84.

[8] Alberto, W.D., del Pilar, D.M., Valeria, A.M., Fabiana, P.S., Cecilia, H.A., and de los Ángeles, B.M., 2001, Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study: Suquı́a River Basin (Córdoba–Argentina), Water Res., 35 (12), 2881–2894.

[9] Mitra, S., Ghosh, S., Satpathy, K.K., Bhattacharya, B.D., Sarkar, S.K., Mishra, P., and Raja, P., 2018, Water quality assessment of the ecologically stressed Hooghly River Estuary, India: A multivariate approach, Mar. Pollut. Bull., 126, 592–599.

[10] Taoufik, G., Khouni, I., and Ghrabi, A., 2017, Assessment of physico-chemical and microbiological surface water quality using multivariate statistical techniques: A case study of the Wadi El-Bey River, Tunisia, Arabian J. Geosci., 10, 181.

[11] Hajigholizadeh, M., and Melesse, A.M., 2017, Assortment and spatiotemporal analysis of surface water quality using cluster and discriminant analyses, Catena, 151, 247–258.

[12] Tosic, M., Restrepo, J.D., Lonin, S., Izquierdo, A., and Martins, F., 2019, Water and sediment quality in Cartagena Bay, Colombia: Seasonal variability and potential impacts of pollution, Estuarine Coastal Shelf Sci., 216, 187–203.

[13] Yoon, J.Y., Bhatta, K., Rastogi, G., Muduli, P.R., Do, Y., Kim, D.K., Pattnaik, A.K., and Joo, G.J., 2016, Application of multivariate analysis to determine spatial and temporal changes in water quality after new channel construction in the Chilika Lagoon, Ecol. Eng., 90, 314–319.

[14] Jung, K.Y., Lee, K.L., Im, T.H., Lee, I.J., Kim, S., Han, K.Y., and Ahn, J.M., 2016, Evaluation of water quality for the Nakdong River watershed using multivariate analysis, Environ. Technol. Innovation, 5, 67–82.

[15] Jiang, Y., Guo, H., Jia, Y., Cao, Y., and Hu, C., 2015, Principal component analysis and hierarchical cluster analyses of arsenic groundwater geochemistry in the Hetao basin, Inner Mongolia, Geochemistry, 75 (2), 197–205.

[16] Ruždjak, A.M., and Ruždjak, D., 2015, Evaluation of river water quality variations using multivariate statistical techniques: Sava River (Croatia): A case study, Environ. Monit. Assess., 187, 215.

[17] DIMAR, 2017, Weather conditions in Cartagena de Indias, Centro de Investigaciones Oceanograficas e Hidrograficas, https://www.cioh.org.co/meteorologia/Climatologia/Climatologia%20Cartagena.pdf, accessed on 10 January 2019.

[18] Baird, R., Eaton, A.D., and Rice, E.W., 2017, Standard Methods for the Examination of Water and Wastewater, 23rd Ed., American Public Health Association, American Water Works Association, Water Environment Federation.

[19] Acosta, J.C., Baldiris, I., and Pacheco, H.P., 2015, Análisis de la variación en la calidad del agua en la bahía de Barbacoas-Cartagena durante el period 2001–2014, Rev. Ingeniería Innovación, 3 (1), 7–17.

[20] Montgomery, D.C., Runger, G.C., and Hubele, N.F., 2010, Engineering Statistics, 5th Ed., John Wiley & Sons, New York.

[21] Navarro, I.B., and Aponte, J.H.S., 2017, Application of multivariate statistical methods to water quality assessment in Arroyo Plata, Colombian Caribbean, Teknos Revista Científica, 17, 11–21.

[22] Woolson, R.F., 2008, “Wilcoxon signed-rank test” in Wiley Encyclopedia of Clinical Trials, Eds. D’Agostino, R.B., Sullivan, L., and Massaro, J., John Wiley & Sons, 1–3.

[23] Razmkhah, H., Abrishamchi, A., and Torkian, A., 2010, Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: A case study on Jajrood River (Tehran, Iran), J. Environ. Manage., 91 (4), 852–860.

[24] Kaveh, A.R., Shahedi, K., Roshan, M.H., and Ghorbani, J., 2015, Assessment of spatio-temporal variations of surface water quality and prioritization of pollution Sources (Case study: Talar Watershed, Mazandaran province), Environ. Resour. Res., 3, 27–45.

[25] Barakat, A., El Baghdadi, M., Rais, J., Aghezzaf, B., and Slassi, M., 2016, Assessment of spatial and seasonal water quality variation of Oum Er Rbia River (Morocco) using multivariate statistical techniques, Int. Soil Water Conserv. Res., 4 (4), 284–292.

[26] Ménesguen, A., and Lacroix, G., 2018, Modelling the marine eutrophication: A review, Sci. Total Environ., 636, 339–354.

[27] Cutrim, M.V.J., Ferreira, F.S., dos Santos, A.K.D., Cavalcanti, L.F., Araújo B.O., de Azevedo-Cutrim, A.C.G., Furtado, J.A., and Oliveira, A.L.L., 2019, Trophic state of an urban coastal lagoon (northern Brazil), seasonal variation of the phytoplankton community and environmental variables, Estuarine Coastal Shelf Sci., 216, 98–109.



DOI: https://doi.org/10.22146/ijc.43035

Article Metrics

Abstract views : 2480 | views : 2141


Copyright (c) 2019 Indonesian Journal of Chemistry

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

 


Indonesian Journal of Chemistry (ISSN 1411-9420 /e-ISSN 2460-1578) - Chemistry Department, Universitas Gadjah Mada, Indonesia.

Web
Analytics View The Statistics of Indones. J. Chem.