Abstract
This study is focused on water quality of Melen River (Turkey) and evaluation of 26 physical and chemical pollution data obtained five monitoring stations during the period 1995–2006. It presents the application of multivariate statistical methods to the data set, namely, principal component and factor analysis (PCA/FA), multiple regression analysis (MRA) and discriminant analysis (DA). The PCA/FA was employed to evaluate the high–low flow periods correlations of water quality parameters, while the principal factor analysis technique was used to extract the parameters that are most important in assessing high–low flow periods variations of river water quality. Latent factors were identified as responsible for data structure explaining 72–97% of the total variance of the each data sets. PCA/FA was supported with multiple regression analysis to determine the most important parameter in each factor. It examines the relation between a single dependent variable and a set of independent variables to best represent the relation in the each factor. Obtained important parameters provided us to determine the major pollution sources in Melen River Basin. So factors are conditionally named soil structure and erosion, domestic, municipal and industrial effluents, agricultural activities (fertilizer, irrigation water and livestock wastes), atmospheric deposition and seasonal effects factors. DA applied the data set to obtain the parameters responsible for temporal and spatial variations. Assessment of high–low flow period changes in surface water quality is an important aspect for evaluating temporal and spatial variations of river pollution. The aim of this study is illustration the usefulness of multivariate statistical analysis for evaluation of complex data sets, in Melen River water quality assessment identification of factors and pollution sources, for effective water quality management determination the spatial and temporal variations in water quality.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Amiri BJ, Nakane K (2009) Modeling the linkage between riverwater quality and landscape metrics in the Chugoku District of Japan. Water Resour Manag 23:931–956
APHA-AWWA-WPCF (1999) In standard methods for the examination of water and wastewater, 20th edn. American Public Health Association, Washington
Boyacıoğlu H, Boyacıoğlu H (2006) Water pollution sources assessment by multivariate statistical methods in the Tahtali Basin, Turkey. Environ Geol 54:275–282
Brumelis G, Lapina L, Nikodemus O, Tabors G (2000) Use of an artificial model of monitoring data to aid interpretation of principal component analysis. Environ Model Softw 15:755–763
Crowther J, Kay D, Wyer MD (2001) Relationships between microbial water quality and environmental conditions in coastal recreational waters: the Fylde Coast, UK. Water Res 35(17):4029–4038
Dixon W, Chiswell B (1996) Review of aquatic monitoring program design. Water Res 30:1935–1948
Dogan E, Sengorur B, Koklu R (2009) Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique. J Environ Manag 90:1229–1235
Düzce Governorship Environment and Forest Directorship (2007) Düzce Environment State Report, Düzce
Freund RJ, Wilson WJ (1998) Regression analysis—statistical modeling of a response variable. Academic Press
Kannel PR, Lee S, Kanel SR, Khan SP (2007) Chemometric application in classification and assessment of monitoring locations of an urban river system. Anal Chim Acta 582:390–399
Kottı ME, Vlessıdıs GA, Thanasoulıas NC, Evmırıdıs NP (2005) Assessment of river water quality in Northwestern Greece. Water Resour Manag 19:77–94
Kowalkowski T, Zbytniewski R, Szpejna J, Buszewski B (2006) Application of chemometrics in river water classification. Water Res 40:744–752
Liu CW, Lin KH, Kuo YM (2003) Application of factor analysis in the assessment of groundwater quality in a Blackfoot disease area in Taiwan. Sci Total Environ 313:77–89
Maillard P, Santos NAP (2008) A spatial–statistical approach for modeling the effect of non-point source pollution on different water quality parameters in the Velhas River Watershed—Brazil. J Environ Manag 86:158–170
Mainstone CP, Parr W (2002) Phosphorus in rivers—ecology and management. Sci Total Environ 282–283:25–47
Mallin MA, Williams KE, Esham EC, Lowe RP (2000) Effect of human development on bacteriological water quality in coastal watersheds. Ecol Appl 10(4):1047–1056
Ouyang Y (2005) Evaluation of river water quality monitoring stations by principal component analysis. Water Res 39:2621–2635
Ouyang Y, Nkedi-Kizza P, Wu QT, Shinde D, Huang CH (2006) Assessment of seasonal variations in surface water quality. Water Res 40:3800–3810
Panda UC, Sundaray SK, Rath P, Nayak BB, Bhatta D (2006) Application of factor and cluster analysis for characterization of river and estuarine water systems—a case study: Mahanadi River (India). J Hydrol 331:434–445
Pekey H, Karakaş D, Bakoğlu M (2004) Source apportionment of trace metals in surface waters of a polluted stream using multivariate statistical analyses. Mar Pollut Bull 49:809–818
Sengörür B, İsa D (2001) Sakarya Nehri’ne Ait Su Kalite Gözlemlerinin Faktör Analizi. Turk J Eng Environ Sci, Tübitak 25:415–425
Shrestha S, Kazama F (2007) Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji River Basin, Japan. Environ Model Softw 22(4):464–475
Simeonov V, Stratis JA, Samara C, Zachariadis G, Voutsa D, Anthemidis A, Sofonioub M, Kouimtzis TH (2003) Assessment of the surface water quality in Northern Greece. Water Res 37:4119–4124
Singh KP, Malik A, Sinha S (2005) Water quality assessment and apportionment of pollution sources of Gomti River (India) using multivariate statistical techniques—a case study. Anal Chim Acta 538:355–374
Singh KP, 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 Res 38:3980–3992
Sliva L, Williams DD (2001) Buffer zone versus whole catchment approaches to studying land use impact on river water quality. Water Res 35(14):3462–3472
Tinsley EAH, Brown SD (2000) Handbook of applied multivariate statistics and mathematical modeling. Academic, San Diego
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 Res 32(12):35
Wang X (2001) Integrating water-quality management and land-use planning in a watershed context. J Environ Manag 61:25–36
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
About this article
Cite this article
Koklu, R., Sengorur, B. & Topal, B. Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey). Water Resour Manage 24, 959–978 (2010). https://doi.org/10.1007/s11269-009-9481-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-009-9481-7