Assessment of Water Quality Parameters on Uzuncayır Dam Lake Using Principal Component and Cluster Analysis

Yıl 2016, , 0 - 0, 11.06.2016

Banu Kutlu , Azime Küçükgül Osman Serdar Rahmi Aydın , Durali Danabaş

https://doi.org/10.17693/yunus.83387

Öz

This study was carried out to monitor water quality in Uzunçayır Dam Lake from May 2013 to March 2014 based on monthly sample monitoring from ten stations. Temperature, dissolved oxygen, pH, biological oxygen demand (BOD), electrical conductivity, total dissolved solids, total hardness, total alkalinity, specific conductance, calcium (Ca), magnesium (Mg),  orthophosphate-phosphorus (PO₄-P), ammonium (NH₄),  nitrate (NO₃), nitrite (NO₂), chlorophyll a (Chl-a) parameters were investigated during study. Data obtained were evaluated by using multivariate statistical analysis, cluster analysis, principal component analysis and factor analysis. Uzunçayır Dam Lake is defined as a hard water lake because of the high pH and high electrical conductivity and total solids content as the result of the high content of dissolved anions and cations.

Principal components (PCA) analysis revealed in two different clusters to the similarities among the stations reflected different physico-chemical properties and the level of pollution in Uzunçayır Dam Lake. Three potential factors were determined explaining 100% of the total variation of the data. In component 1, 17.7 % of all variation had Mg, NH₄ and NO₂. According to the component 2 and 3 the results showed that 34.95 % of all variation stem from agricultural drainage and nutrient, from physical parameters of 68.2 %.  In analyses of cluster, one group (10 station) was found to affect directly the activities of domestic and agricultural land.

Based on the Surface Water Quality Management (A and B group), it was concluded that Uzunçayır Dam Lake had high quality and slightly contaminated and the appropriate structure for many activities such as agricultural irrigation, drinking water supply, trout and other fish production. 

Kaynakça

• Adams, S., Titus, R., Pietesen, K., Tredoux, G. and Harris, C. 2001. Hydrochemical characteristic of aquifers near Sutherland in the Western Karoo. South Africa. Journal of Hydrology, 241: 91-103.
• Andrade, E.M., Palácio, H.A.Q., Souza, I.H., Leão, R.A. and Guerreiro, M. J. 2008. Land use Effects in Groundwater Composition of an Alluvial Aquifer (Trussu River, Brazil) by Multivariate Techniques. Environmental Research. 106: 170-177.
• Ayeni, A. O. and. Soneye, A. S. O. 2013. Interpretation of surface water quality using principal components analysis and cluster analysis. Journal of Geography and Regional Planning, Vol. 6(4): 132-141
• Bathusha, M.I. and Saseetharan. M.K. 2006. Statistical study on physico – chemical characteristics of ground water of coimbatore south zone. Indian Journal environmental Protection, 26(6), 508 – 515 .
• Easton, Z.M., Gerard-marchant,P., Walter, M.T., Petrovic A.M., and Steenhuis,T.S. 2007. Identifying dissolved phosphorus source areas and predicting transport from an urban watershed using distributed hydrologic modeling. Water Resources Research, 43: 5-16.
• EİE. 1996. 1992 Su Yılı Akım Değerleri. Ankara: EİE Genel Müdürlüğü Yayınları, No. 95–25.
• Helena, B., Pardo, R., Vega, M., Barrado, E., Ferna´ndez, J.M. and Ferna´ndez, L.2000. Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga river, Spain) by principal component analysis. Water Research, 34: 807-816.
• Ireland Environmental Protection Agency. 2001. Parameters of Water Quality Interpretation and Standards. Environ- mental Protection Agency, Johnstown, p: 133.
• Jarvie, H.P., Whitton, B.A. and Neal, C. 1998. Nitrogen and phosphorus in east coast British rivers: Speciation, sources and biological significance. Sci Total Environ 1998; 210/211: 79–109.
• Kaufman, L. and Rousseeuw, P. J. 1990. Finding groups in data: an introduction to cluster analysis. New York, Wiley.
• Lee, J.Y., Cheon, J.Y., Lee, K.K., Lee, S.Y. and Lee, M.H. 2001. Statistical evaluation of geochemical parameter distribution in a ground water system contaminated with petroleum hydrocarbons. Journal of Environmental Quality, 30: 1548-1563.
• Liu, C.W., Lin, K. H. and Kuo, Y.M. 2003. Application of factor analysis in the assessment of groundwater quality in a Blackfoot disease area in Taiwan. Science. Total Environmental, 313:77-89.
• Niemi, G. J. , Devore, P., Detenbeck,N., Taylor, D., and Lima ,A. 1990. Overview of Case Studies on Recovery of Aquatic Systems from Disturbance. Environmental Management, 14: 571-587.
• Reghunath, R., Murthy, T.R.S.and Raghavan, B.R. 2002. The utility of multivariate statistical techniques in hydrogeochemical studies: an example from Karnataka, India. Water Research, 36: 2437–2442.
• Sickman,J.O., Zanoli, M.J., and Mann, H.L. 2007. Effects of Urbanization on Organic Carbon Loads in the Sacramento River, California. Water Resources Research, 43, 1-15.
• Simeonov, V., Simeonova, P. and Tsitouridou, R. 2004. Chemometric quality assessment of surface waters: two case studies. Chemical Engineer. Ecology 11: 449–469.
• Simeonova, P., Simeonov, V. and Andreev, G. 2003. Water quality study of the Struma River Basin, Bulgaria (1989–1998). Central European Journal of Chemistry,1: 136–212.
• Singh, K.P., Malik, A. and 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.
• Singh, K.P., Malik, A., Mohan, D. and 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.
• Sinha, M.R., Dev, A., Prasad, A., Ghosh, M., and Tagore, R.N. 2011. Physicochemical examination and quality assessment of groundwater (Hand-Pump) around Patna main town, Bihar state, India. Journal of Chemical and Pharmaceutical Research, 3(3): 701-705.
• Solaraj, G., Dhanakumar, S., Murthy, K.R. and Mohanraj, R. 2010. Water quality in select regions of Cauvery Delta River basin, southern India, with emphasis on monsoonal variation. Environmental Monitoring and Assessment, 166:435-44
• South African Water Quality Guidelines. 1996. Agricultural Use: Livestock Watering. Department of Water Affairs and Forestry, Pretoria, 2nd ed., Vol. 4.
• Strickland, J.D.H. and Parsons, T.R. 1972. A practical handbook of seawater analysis, fisheries research boards of Canada. Bull, 167. Ottawa, pp: 310.
• Treseder, K.K. 2008. Nitrogen Additions and Microbial Bio- mass: A Meta-analysis of Ecosystem Studies. Ecological Letter, 11: 1111-1120.
• Vega, M., Pardo, R., Barrado, E., and Deban, L. 1996. Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32:3581–3592.
• Vega, M., Pardo, R., Barrado, E., & Deban, L. 1998. Assessment of seasonal and polluting effects on the qualityof river water by exploratory data analysis.Water Research, 32: 3581–3592.
• Wang, Y.S, Lou, Z.P., Sun, .C.C., Wu, M.L. and Han, S.H. 2006. Multivariate statistical analysis of water quality and phytoplankton characteristics in Daya Bay, China, from 1999 to 2002. Oceanologia, 48: 193-213.
• Wu, M.L. and Wang, Y.S. 2007. Using chemometrics to evaluate anthropogenic effects in Daya Bay, China. Estuarine, Coastal and Shelf Science, 72:732–742
• Wunderlin, D. A., Diaz, M. P., Ame, M. V., Pesce, S. F., Hued, A. C. and Bistoni, M. A. 2001. Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study: Suquia river basin (Cordoba, Argentina). Water Research, 35: 2881–2894.
• Zhao, O., Liu, S., Li, D., Z. Yang, Shikui, D., Cong, W., Zhaoling, Z.2012. Spatio-temporal variation of heavy metals in fresh water after dam construction: a case study of the Manwan Reservoir, Lancang River. Environmental Monitoring Assessment, 184:4253–4266.