Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu]
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| internalnotes | 1. Reza, R. & Singh, G. (2010). Heavy Metal Contamination and its Indexing Approach for River Water. International Journal of Environmental Science and Technology, 7(4): 785-792. 2. Sundaray, S.K., Panda, U.C., Nayak B. B. & Bhatta D. (2006). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of the Mahanadi river-estuarine system (India)--a case study. Environmental Geochemistry and Health, 28(4): 317-330. 3. Carpenter, S.R., Caraco, N.F., Correll, D.L., Howarth, R.W., Sharpley, A.N. & Smith, V. H. (1998). Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecology Application, 8: 559–568. 4. Jarvie, H. P., Whitton, B. A., & Neal, C. (1998). Nitrogen and phosphorus in east coast British rivers: speciation, sources and biological significance. Science of the Total Environment, 211: 79–109 5. Filik I. C., Emiroglu, O., Ilhan, S., Arslan, N., Yilmaz, V. & Ahiska, S. (2008). Application of multivariate statistical techniques in the assessment of surface water quality in Ulubat Lake. Turkey. Environmental Monitoring and Assessment, 144: 269-276. 6. Zhang, Y., Guo, F., Meng, W. & Wang, X. (2009). Water quality assessment and source identification of Daliao river basin using multivariate statistical methods. Environmental Monitoring and Assessment, 152: 105- 121. 7. Shrestha, S. & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniqueas: Fuji river basin Japan. Environnmental Modeling and Software, 22(4): 464-475. 8. Pejman, A. H., Bidhendi, G. R., Karbassi, A. R., Mehrdadi, N. & Bidendi, M.E. (2009). Evaluation of spatial and seasonal variations in surface water quality using multivariate statistical techniques. International Journal of Environmental Science and Technology, 6(3): 467-476. 9. Mayback & Helmer, (1998). The quality of rivers from pristine statge to global pollution. Palaeogr, palaeclamatol, palaeoecol. (Global planet sect) 75, 283-309. 10. Kuppusamy M. R. & Giridhar V. V. (2006). Factor analysis of water quality characteristics including trace metal speciation in the coastal environmental system of Chennai Ennore. Environment International, 32 (2): 174-179. 11. Tanriverdi, C., Alp, A., Demirkiran, A. R. & Ucjarde, F. (2010). Assessment of surface water quality of the Ceyhan River basin, Turkey. Environmental Monitoring & Assessment,167, 175-184. 12. Simeonova, P., Simeonova, V. & Andreev, G. (2003). Environmetric analysis of the Struma River water quality. Central European journal of Chemistry, 2: 121-126. 13. Huang, J., Ho, M. & Du, P. (2011). Assessment of temporal and spatial variation of coastal water quality and source identification along Macau Peninsular. Stochastic Environmental Research and Risk Assessment, 25: 353-361. 14. Ifabiyi, I.P. (1997). Variation in Water Gravity with Rainfall Incidences: A Case Study of Ogbe Stream Ile-Ife, Ife. Res. Publications Geogr, 6(1&2): 139-144. 15. Jaji M.O., Bamgbose, O., Odukoya O.O. & Arowolo T.A. (2007). Water Quality Assessment of Ogun River, South West Nigeria. Environment Monitoring Assessment, 133: 473-482. 16. Mazlum, N., Ozer, A. & Mazlum, S. (1999). Interpretation of water quality data by principal components analysis.Turkish Journal of Environmental Science, 23: 19-26. 17. Zhao, Z. & Cui, F. (2009). Multivariate statistical analysis for the surface water quality of the Luan River, China. Journal of Zhejiang University Science A, 10(1): 142-148. 18. Juahir, H., Zain, M.S., Yosoff, M.K., Ismail, T.T.H., Samah, A.M.A., Toriman, M.E. & Moktar, M. (2010b). Spatial assessment of Langtan River Basin (Malaysia) using environmentric techniques. Environment Monitoring Assessment, 173: 625-641. 19. Noor, A.S. & Khawar, S., (2010). Geochemical baselines of major, minor and trace elements in the tropical sediments of the Terengganu River Basin Malaysia. International Journal of Sediment Research, 25: 340-354. 20. Malaysia population census Department of Statistic population of Terengganu (2014). Online access on www.statitics.gov.my/portal/index.php?option=com 21. Kuala Terengganu city Council (MBKT), (2014). Online access on http://mbkt.terengganu.gov.my/jadual-pbt 22. Tobiszewski, M., Tsakovski, S., Simeonov, V. & Namiesnik, J. (2010). Surface water quality assessment by the use of combination of multivariate statistical classification and expert information.Chemosphere,80: 740-746. 23. 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. 24. Voudouris, K., Panagopoulos, A. & Koumantakis, J. (2000). Multivariate statistical analysis in the assessment of hydrochemistry of the Northern Korinthia Prefecture Alluvial Aquifer System (Paloponnese, Greece). Natural Resources Research, 9: 135-146. 25. Simeonova, P., Simeonova, V. & Andreev, G. (2003). Environmetric analysis of the Struma River water quality central. European journal of Chemistry, 2: 121-126. 26. 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. Analytical Chemical Acta 538, 355- 374. 27. McKenna Jr., J.E. (2003). An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modeling & Software, 18 (3): 205-220. 28. Jornson, R.A. & Wichern, D.W. (1992). Applied Multivariate Statistical Analysis, 3rdedn, Prentice – Hall lut., New Jersey. 29. Lattin, J., Carroll, D. & Green, P. (2003). Analyzing Multivariate Data. New York: Duxbury. 30. Wunderlin, D.A., Diaz, M.P., Ame, M.V., Pesce, S.F., Hued, A.C. & 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(12): 2881-2894. 31. Brumelis, G., Lapina, L., Nikodemus, O. & Tabors, G. (2000). Use of an artificial model of monitoring data to aid interpretation of principal component analysis. Environmental modelling and software, 15(8): 755-763. 32. Helena, B., Pardo, R., Vega, M., Barrado, E., Fernandex, J.M. & Fernendex, L. (2000). Temporal evolution of ground water composition in an alluvial aquifer composition in an alluvial aquifer (Pisuegariver, Spain) by principal component analysis. Water Research, 34: 807-816. 33. Abdul-Wahab, S.A., Bakheit, C.S. & Al-Alawi, S.M. (2005). Principal component and multiple regression analysis in modeling of ground-level ozone and factors affecting its concentrations. Environmental Modelin & Software, 20(10): 1263-1271. 34. Love, D., Hallbauer, D., Amos, A. & Hranova, R. (2004). Factor analysis as a tool in groundwater quality management: two southern African case studies. Physics & Chemistry of the Earth, 29: 1135-1143. 35. Kim, J.O. & Mueller, C.W. (1987). Introduction to factor analysis: what it is and how to do it. Quantitative Applications in the Social Sciences Series. Sage University Press, Newbury Park. 36. Liu, C.W., Lin, K.H. & Kuo, Y.M. (2003). Application of factor analysis in the assessment of groundwater in a Blackfoot disease area in Taiwan. Science of the Total Environment, 313(1-13): 77-89. 37. Yang, Y.H., Zhou, F., Guo, H.C., Sheng, H., Liu, H., Dao, X. & He, C.J. (2010). Analysis of spatial and temporal water pollution patterns in Lake Dianchi using multivariate statistical methods. Environmental Monitoring and Assessment, 170: 407-416. |
| originalfilename | 5938-01-FH02-ESERI-15-02842.jpg |
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| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=11671 |
| spelling | 11671 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=11671 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal UniSZA Unisza unisza image/jpeg inches 96 96 1416 40 40 791 2015-04-20 11:54:20 1416x791 5938-01-FH02-ESERI-15-02842.jpg UniSZA Private Access Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] Malaysian Journal of Analytical Sciences Multivariate Statistical techniques including cluster analysis, discriminant analysis, and principal component analysis/factor analysis were applied to investigate the spatial variation and pollution sources in the Terengganu river basin during 5 years of monitoring 13 water quality parameters at thirteen different stations. Cluster analysis (CA) classified 13 stations into 2 clusters low polluted (LP) and moderate polluted (MP) based on similar water quality characteristics. Discriminant analysis (DA) rendered significant data reduction with 4 parameters (pH, NH3 -NL, PO4 and EC) and correct assignation of 95.80%. The PCA/FA applied to the data sets, yielded in five latent factors accounting 72.42% of the total variance in the water quality data. The obtained varifactors indicate that parameters in charge for water quality variations are mainly related to domestic waste, industrial, runoff and agricultural (anthropogenic activities). Therefore, multivariate techniques are important in environmental management. 19 2 Malaysian Journal of Analytical Sciences Malaysian Journal of Analytical Sciences 338-348 1. Reza, R. & Singh, G. (2010). Heavy Metal Contamination and its Indexing Approach for River Water. International Journal of Environmental Science and Technology, 7(4): 785-792. 2. Sundaray, S.K., Panda, U.C., Nayak B. B. & Bhatta D. (2006). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of the Mahanadi river-estuarine system (India)--a case study. Environmental Geochemistry and Health, 28(4): 317-330. 3. Carpenter, S.R., Caraco, N.F., Correll, D.L., Howarth, R.W., Sharpley, A.N. & Smith, V. H. (1998). Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecology Application, 8: 559–568. 4. Jarvie, H. P., Whitton, B. A., & Neal, C. (1998). Nitrogen and phosphorus in east coast British rivers: speciation, sources and biological significance. Science of the Total Environment, 211: 79–109 5. Filik I. C., Emiroglu, O., Ilhan, S., Arslan, N., Yilmaz, V. & Ahiska, S. (2008). Application of multivariate statistical techniques in the assessment of surface water quality in Ulubat Lake. Turkey. Environmental Monitoring and Assessment, 144: 269-276. 6. Zhang, Y., Guo, F., Meng, W. & Wang, X. (2009). Water quality assessment and source identification of Daliao river basin using multivariate statistical methods. Environmental Monitoring and Assessment, 152: 105- 121. 7. Shrestha, S. & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniqueas: Fuji river basin Japan. Environnmental Modeling and Software, 22(4): 464-475. 8. Pejman, A. H., Bidhendi, G. R., Karbassi, A. R., Mehrdadi, N. & Bidendi, M.E. (2009). Evaluation of spatial and seasonal variations in surface water quality using multivariate statistical techniques. International Journal of Environmental Science and Technology, 6(3): 467-476. 9. Mayback & Helmer, (1998). The quality of rivers from pristine statge to global pollution. Palaeogr, palaeclamatol, palaeoecol. (Global planet sect) 75, 283-309. 10. Kuppusamy M. R. & Giridhar V. V. (2006). Factor analysis of water quality characteristics including trace metal speciation in the coastal environmental system of Chennai Ennore. Environment International, 32 (2): 174-179. 11. Tanriverdi, C., Alp, A., Demirkiran, A. R. & Ucjarde, F. (2010). Assessment of surface water quality of the Ceyhan River basin, Turkey. Environmental Monitoring & Assessment,167, 175-184. 12. Simeonova, P., Simeonova, V. & Andreev, G. (2003). Environmetric analysis of the Struma River water quality. Central European journal of Chemistry, 2: 121-126. 13. Huang, J., Ho, M. & Du, P. (2011). Assessment of temporal and spatial variation of coastal water quality and source identification along Macau Peninsular. Stochastic Environmental Research and Risk Assessment, 25: 353-361. 14. Ifabiyi, I.P. (1997). Variation in Water Gravity with Rainfall Incidences: A Case Study of Ogbe Stream Ile-Ife, Ife. Res. Publications Geogr, 6(1&2): 139-144. 15. Jaji M.O., Bamgbose, O., Odukoya O.O. & Arowolo T.A. (2007). Water Quality Assessment of Ogun River, South West Nigeria. Environment Monitoring Assessment, 133: 473-482. 16. Mazlum, N., Ozer, A. & Mazlum, S. (1999). Interpretation of water quality data by principal components analysis.Turkish Journal of Environmental Science, 23: 19-26. 17. Zhao, Z. & Cui, F. (2009). Multivariate statistical analysis for the surface water quality of the Luan River, China. Journal of Zhejiang University Science A, 10(1): 142-148. 18. Juahir, H., Zain, M.S., Yosoff, M.K., Ismail, T.T.H., Samah, A.M.A., Toriman, M.E. & Moktar, M. (2010b). Spatial assessment of Langtan River Basin (Malaysia) using environmentric techniques. Environment Monitoring Assessment, 173: 625-641. 19. Noor, A.S. & Khawar, S., (2010). Geochemical baselines of major, minor and trace elements in the tropical sediments of the Terengganu River Basin Malaysia. International Journal of Sediment Research, 25: 340-354. 20. Malaysia population census Department of Statistic population of Terengganu (2014). Online access on www.statitics.gov.my/portal/index.php?option=com 21. Kuala Terengganu city Council (MBKT), (2014). Online access on http://mbkt.terengganu.gov.my/jadual-pbt 22. Tobiszewski, M., Tsakovski, S., Simeonov, V. & Namiesnik, J. (2010). Surface water quality assessment by the use of combination of multivariate statistical classification and expert information.Chemosphere,80: 740-746. 23. 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. 24. Voudouris, K., Panagopoulos, A. & Koumantakis, J. (2000). Multivariate statistical analysis in the assessment of hydrochemistry of the Northern Korinthia Prefecture Alluvial Aquifer System (Paloponnese, Greece). Natural Resources Research, 9: 135-146. 25. Simeonova, P., Simeonova, V. & Andreev, G. (2003). Environmetric analysis of the Struma River water quality central. European journal of Chemistry, 2: 121-126. 26. 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. Analytical Chemical Acta 538, 355- 374. 27. McKenna Jr., J.E. (2003). An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modeling & Software, 18 (3): 205-220. 28. Jornson, R.A. & Wichern, D.W. (1992). Applied Multivariate Statistical Analysis, 3rdedn, Prentice – Hall lut., New Jersey. 29. Lattin, J., Carroll, D. & Green, P. (2003). Analyzing Multivariate Data. New York: Duxbury. 30. Wunderlin, D.A., Diaz, M.P., Ame, M.V., Pesce, S.F., Hued, A.C. & 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(12): 2881-2894. 31. Brumelis, G., Lapina, L., Nikodemus, O. & Tabors, G. (2000). Use of an artificial model of monitoring data to aid interpretation of principal component analysis. Environmental modelling and software, 15(8): 755-763. 32. Helena, B., Pardo, R., Vega, M., Barrado, E., Fernandex, J.M. & Fernendex, L. (2000). Temporal evolution of ground water composition in an alluvial aquifer composition in an alluvial aquifer (Pisuegariver, Spain) by principal component analysis. Water Research, 34: 807-816. 33. Abdul-Wahab, S.A., Bakheit, C.S. & Al-Alawi, S.M. (2005). Principal component and multiple regression analysis in modeling of ground-level ozone and factors affecting its concentrations. Environmental Modelin & Software, 20(10): 1263-1271. 34. Love, D., Hallbauer, D., Amos, A. & Hranova, R. (2004). Factor analysis as a tool in groundwater quality management: two southern African case studies. Physics & Chemistry of the Earth, 29: 1135-1143. 35. Kim, J.O. & Mueller, C.W. (1987). Introduction to factor analysis: what it is and how to do it. Quantitative Applications in the Social Sciences Series. Sage University Press, Newbury Park. 36. Liu, C.W., Lin, K.H. & Kuo, Y.M. (2003). Application of factor analysis in the assessment of groundwater in a Blackfoot disease area in Taiwan. Science of the Total Environment, 313(1-13): 77-89. 37. Yang, Y.H., Zhou, F., Guo, H.C., Sheng, H., Liu, H., Dao, X. & He, C.J. (2010). Analysis of spatial and temporal water pollution patterns in Lake Dianchi using multivariate statistical methods. Environmental Monitoring and Assessment, 170: 407-416. |
| spellingShingle | Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] |
| summary | Multivariate Statistical techniques including cluster analysis, discriminant analysis, and principal component analysis/factor analysis were applied to investigate the spatial variation and pollution sources in the Terengganu river basin during 5 years of monitoring 13 water quality parameters at thirteen different stations. Cluster analysis (CA) classified 13 stations into 2 clusters low polluted (LP) and moderate polluted (MP) based on similar water quality characteristics. Discriminant analysis (DA) rendered significant data reduction with 4 parameters (pH, NH3 -NL, PO4 and EC) and correct assignation of 95.80%. The PCA/FA applied to the data sets, yielded in five latent factors accounting 72.42% of the total variance in the water quality data. The obtained varifactors indicate that parameters in charge for water quality variations are mainly related to domestic waste, industrial, runoff and agricultural (anthropogenic activities). Therefore, multivariate techniques are important in environmental management. |
| title | Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] |
| title_full | Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] |
| title_fullStr | Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] |
| title_full_unstemmed | Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] |
| title_short | Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] |
| title_sort | assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai terengganu] |