Document Type: ORIGINAL RESEARCH PAPER

Authors

1 Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia

2 Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor DE, Malaysia

Abstract

Rapid development and population growth have resulted in an ever-increasing level of water pollution in Malaysia. Therefore, this study was conducted to assess water quality of Selangor River in Malaysia. The data collected under the river water quality monitoring program by the Department of environment from 2005 to 2015 were used for statistical analyses. The local water quality indices were computed and a trend detection technique and cluster analysis were applied, respectively, to detect changes and spatial disparity in water quality trends. The results showed that the river water is of good quality at all stations, with the exception of 1SR01 and 1SR09 located upstream, which recorded moderate water quality indices of 68 and 71, respectively. The results of trend analysis showed downward trends in dissolved oxygen, biochemical oxygen demand and ammonia nitrogen, for most water quality stations, as well as increasing trends in chemical oxygen, suspended solids, pH and temperature for most stations. In addition, the results of cluster and time series analyses showed that the trend variation in dissolved oxygen, pH, and temperature between the station clusters is relatively low as compared to chemical oxygen demand, biochemical oxygen demand, suspended solids, and ammonia nitrogen. With the peak concentration of 13 mg/L for dissolved oxygen observed in cluster 2 in 2014, and the highest decrease in suspended solids (8 mg/L) observed in cluster 1 for 2015. This finding demonstrates that these combined statistical analyses can be a useful approach for assessing water quality for adequate management of water resources.

Graphical Abstract

Highlights

  • Trend analysis showed downward trends in DO, NH3-N, and BOD for most water quality stations, as well as increasing trends in COD, SS, pH and TEMP for most stations;
  • Cluster analysis indicated that the first cluster is located downstream, the second cluster upstream and the third cluster in the middle of the river;
  • The time trend variation in DO, pH, and TEMP between the station clusters is relatively low as compared to BOD, COD, SS, and NH3-N;
  • The combined statistical analyses can be a useful approach for assessing water quality for adequate management of water resources.

Keywords

Main Subjects

Aliyu, G. A.; Jamil, N.R.B.; Adam, M.B.; Zulkeflee, Z., (2019). Assessment of Guinea Savanna River system to evaluate water quality and water monitoring networks. Global J. Environ. Sci. Manage., 5: 345–356 (12 pages). 

Antonopoulos, V.Z.; Papamichail D.M.; Mitsiou, K.A., (2001). Statistical and trend analysis of water quality and quantity data for the Strymon River in Greece. Hydrol. Earth Syst. Sci., 5: 679–692 (14 pages).

Behmel S.; Damour, M.; Ludwig, R.; Rodriguez, M.J., (2016). Water quality monitoring strategies — A review and future perspectives. Sci. Total Environ., 571: 1312–1329 (18 pages).

Bloesch, J.; Sandu, C.; Janning, J., (2012). Integrative water protection and river basin management policy: The Danube case. River Syst., 20: 129–144 (16 pages).

Camara, M.; Jamil, N.R.; Abdullah, A.F.B., (2019). Impact of land uses on water quality in Malaysia: a review. Ecol. Process., 8: 10 (10 pages).

CCME, (2015). Guidance manual for optimizing water quality monitoring program design.(88 pages).

Chapman D. V.; Bradley, C.; Gettel, G.M., (2016). Developments in water quality monitoring and management in large river catchments using the Danube River as an example. Environ. Sci. Policy. 64: 141–154 (14 pages).

DOE, (2007). Malaysia Environmental Quality Report 2006. Department of Environment(3 pages).

Drápela, K. ;  Drápelová, I., (2011). Application of Mann-Kendall test and the Sen’s slope estimates for trend detection in deposition data from Bílý Kříž (Beskydy Mts., the Czech Republic) 1997-2010 (14 pages).

EEA, (2016). Surface water quality monitoring — European Environment Agency (3 pages).

Fulazzaky, M.A.; Seong, T.W.; Masirin, M.I.M., (2010). Assessment of Water Quality Status for the Selangor River in Malaysia. Water Air Soil Pollut., 205: 63–77 (15 pages).

Gazzaz, N.M.; Yusoff, M.K.; Aris, A.Z., (2012). Artificial neural network modeling of the water quality index for Kinta River (Malaysia) using water quality variables as predictors. Mar. Pollut. Bull., 64: 2409–2420 (12 pages).

Gupta, V.K.; Tyagi, I.; Agarwal, S.; Singh, R.; Chaudhary, M.; Harit, A.; Kushwaha, S., (2016). Column operation studies for the removal of dyes and phenols using a low cost adsorbent. Global J. Environ. Sci. Manage, 2(1): 1–10 (10 pages).

Hatvani, I. G.; Kovács, J.; Kovács, I. S.; Jakusch, P.; Korponai, J., (2011). Analysis of long-term water quality changes in the Kis-Balaton Water Protection System with time series-, cluster analysis and Wilks’ lambda distribution. Ecol. Eng., 37(4): 629–635 (7 pages).

Jiang, C.; Xiong, L.; Wang, D., (2015). Separating the impacts of climate change and human activities on runoff using the Budyko-type equations with time-varying parameters. J. Hydrol., 522: 326–338 (13 pages).

Juahir, H.; Zain, S.M.; Mohd, (2011). Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques. Env. Monit. Assess., 173: 625–641 (17 pages). 

Kamal, J.M.; Ramjee, C., (2019). Principal Component Analysis for Water Quality Assessment of the Ganga River in Uttar Pradesh, India. Water Resour., 46: 789–806 (18 pages).

Khalil, B.; Ouarda, T.B.M.J., (2009). Statistical approaches used to assess and redesign surface water-quality-monitoring networks. J. Environ. Monit., 11: 1915 (15 pages).

Kovács, J.; Kovács, S.; Magyar, N., (2014). Classification into homogeneous groups using combined cluster and discriminant analysis. Environ. Model. Software. 57:52–59 (8 pages).

Kükrer, S.; Mutlu, E., (2019). Assessment of surface water quality using water quality index and multivariate statistical analyses in Saraydüzü Dam Lake, Turkey. Environ. Monit. Assess., 191: 71 (16 pages).

Kusin, F.M.; Muhammad, S.N.; Zahar, M.S.M.; Madzin, Z., (2016). Integrated River Basin Management: incorporating the use of abandoned mining pool and implication on water quality status. Desalin. Water Treat., 57: 29126–29136 (11 pages).

Ling, T.Y.; Soo, C.L.; Heng, T.L.E., (2018). Water Quality Assessment of Tributaries of Batang Baleh in Sarawak Using Cluster Analysis. Sci. World. J., 2018: 1–9 (9 pages).

Luo, P.; He, B.; Takara, K., (2011). Spatiotemporal trend analysis of recent river water quality conditions in Japan. J. Environ. Monit., 13: 2819 (11 pages).

MD, S.U.C.; Faridah, O.; Wan, Z.W.; Jaafar, N.C.M., (2018). Assessment of Pollution and Improvement Measure of Water Quality Parameters using Scenarios Modeling for Sungai Selangor Basin. Sains. Malaysiana., 47: 457–469 (13 pages).

Othman, F.; Chowdhury, M.S.; Wan, J.W.Z, (2018). Assessing Risk and Sources of Heavy Metals in a Tropical River Basin: A Case Study of the Selangor River, Malaysia. Polish. J. Environ. Stud., 27: 1659–1671 (13 pages).

Sakai, N.; Alsaad, Z.; Thuong, N.T., (2017). Source profiling of arsenic and heavy metals in the Selangor River basin and their maternal and cord blood levels in Selangor State, Malaysia. Chemosphere, 184: 857–865 (9 pages).

Sanders, T.G., (1983). Design of networks for monitoring water quality. Water Resources Publications. (328 pages).

Santhi, V.A.; Mustafa, A.M., (2013). Assessment of organochlorine pesticides and plasticisers in the Selangor River basin and possible pollution sources. Environ. Monit. Assess., 185: 1541–1554(14 pages).

Tanos, P.; Kovács, J.; Kovács, S., (2015). Optimization of the monitoring network on the River Tisza (Central Europe, Hungary) using combined cluster and discriminant analysis, taking seasonality into account. Enviro.n Monit. Assess., 187: 575 (14 pages).

Ullah, K. A.; Jiang, J.; Wang, P., (2018). Land use impacts on surface water quality by statistical approaches. Global J. Environ. Sci. Manage, 4(2), 231–250 (20 pages).

Wan, L.; Li, Y.C.; (2018). Time series trend analysis and prediction of water quality in a managed canal system, Florida (USA). IOP Conf. Ser. Earth Environ. Sci., 191: 012013 (12 pages).

Wang, Y.B.; Liu, C.W.; Liao, P.Y.; Lee, J.J., (2014). Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters. Environ. Monit. Assess., 186: 1781–1792 (12 pages).

Ward, J.H., (1963). Hierarchical Grouping to Optimize an Objective Function. J. Am. Stat. Assoc., 58: 236–244 (9 pages).

Xile, D.; Changhe, L., (2012). Evaluation and Trend Analysis of Surface Water Quality in Zhengzhou in 1998–2008. Chinese J. Popul. Resour. Environ., 10: 44–51 (8 pages).

  

HOW TO CITE THIS ARTICLE:

Camara, M.; Jamil, N.R.B.; Abdullah, F.B., (2019). Variations of water quality in the monitoring network of a tropical river. Global J. Environ. Sci. Manage., 6(1): …,…


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