Available online freely at www.isisn.org Bioscience Research Print ISSN: 1811-9506 Online ISSN: 2218-3973 Journal by Innovative Scientific Information & Services Network RESEARCH ARTICLE BIOSCIENCE RESEARCH, 2019 16(S1): 59-68. OPEN ACCESS

Marine water quality index trend from eight-year study of Klang Estuary

Mohd Saiful Samsudin1, Azman Azid2*, Kamaruzzaman Yunus1

1Kulliyyah of Science, International Islamic University Malaysia, Kuantan, Pahang, Malaysia 2Faculty Bioresources and Food Industry, Universiti Sultan Zainal Abidin (UniSZA), Besut Campus, Terengganu, Malaysia

*Correspondence: [email protected] Revised: 06 Oct. 2019, Accepted: 08 Oct. 2019 e-Published: 11 Nov. 2019 Reviewed by: Dr. Saiful Iskandar Khalit, Dr. Fathurrahman Lananan In the context of marine water quality monitoring, detailed information concerning the marine water quality index is importance. The paper presents the analysis of 8-year period trend (2010-2017) marine water quality index and the other marine water quality parameters fluctuations in the Klang estuary, which is have the famous Port Klang, the one of the largest and busiest ports in peninsular Malaysia. The 2010–2017 data employed in this study entailed 12 marine water quality parameters. In order to investigate the trend analysis, the nonparametric Mann-Kendall statistical test has been used. The result shows the upward trends for MWQI, Salinity, COND, TEMP, DO and O&G and downward trends for pH, TUR, TSS, coliform, PO4, NH3N and NO3. in 8-year period in Klang estuary. The results indicated Klang Estuary has experienced a mild pollution trend due to anthropogenic influence from domestic activities in the vicinity of the estuary. Keywords: Marine water quality index, estuary, trend analysis, long-term monitoring,

INTRODUCTION manifestation of multiple effect situation at higher The estuary area is an important economic hierarchal levels of biological organization. zone where most of the major commercial ports The Klang estuary is surrounded by numerous are situated at this heavily urbanized and industrial areas like Westport Industrial Estate, industrialized area. Estuaries are, in this manner, Pandamaran Industrial Park, Teluk Gong dynamic ecological systems where seawater is Industrial Park and Pulau Indah Industrial Park. acquired by the tides yet is diluted by freshwater For the meantime, land use encircling the estuary flowing in from waterways and rivers especially in is mainly for residential, industrial, plantation, and mangrove ecosystem (Ibrahim et al., 1996, commercial activities (Omar et al. 2018). Besides, Samsudin et al., 2019). Nowadays, mangroves the estuary is a familiar spot for fishing activities ecosystems in Malaysia are exposed to for local population and home for various aquatic urbanisation areas and disturbed by urban and animals. Changes in marine water quality have industrial run-off which comprises traces of heavy important impacts on estuary ecosystems, such metals in dissolved form (Kamaruzzaman et al., as changes in phenology and in species 2009). These extraneous organic and inorganic distribution, the facilitation of species invasions chemicals released by these urban communities and the deterioration of water quality. Once the and industries indicate injurious effects which estuary is harmed either by anthropogenic cause detriment to the environment. Above a activities or natural threats, they will become a certain pollutant threshold, the pollutant- source for releasing pollutants. Estuary loss will responsive biomarker would eventually lead to the also diminish estuarine water quality, curtail Samsudin et al., Marine water quality Index trend of the Klang Estuary in the years 2010-2017 biodiversity, exterminate fish nursery habitat and 2017). The obtained results were analysed in the fish catches and adversely affect adjacent coastal context of long-term marine water quality. habitats (Sandilyan and Kathiresan, 2014, Samsudin et al., 2019). MATERIALS AND METHODS In Malaysia, the study on marine water in estuary is negligible and only limited data are Study Area available concerning the marine water quality The analysis was performed using secondary (MWQ) of the mangrove’s estuarine zones data from monitoring station located in Klang (Samsudin et al., 2019). To assess the MWQ, estuary (N03°00.06′, E101°23.24′) conducted by marine water quality index (MWQI) has been Department of Environment Malaysia (Figure 1). established to provide category for surface marine The surface marine water sampling carried out 4 water by computing the sub-index of standard times per year. The Klang estuary situated at the parameters such as dissolved solid (DO), nitrate downstream of Klang River basin, where is the (NO3), phosphate (PO4), unionized ammonia most important basin in the state of Selangor (NH3), faecal coliform, oil and grease (O&G) and (Abdullah, 1995). This basin is a fourth and the total suspended solid (TSS). According to largest basin approximately 120 km of 80 km in Malaysia Environmental Quality Report 2017, Selangor and 40 km in Kuala Lumpur. Estimated mangrove estuarine and river mouth water are total area of the Klang River basin covers 1.290 classified as Class E (Malaysian Marine Water km2 (Rahman, 2010). Port Klang is the one of the Quality Criteria and Standard). The MWQI scales largest and busiest ports in peninsular Malaysia. ranges from 0 to 100 which classify the MWQ This port divided into three subsidiary commercial from “Poor” to “Excellent” (DOE, 2018). ports such as North, South, and West Port that One of the most effective statistical methods are protected by surrounding mangrove forests. for determining long-term changes in hydrology Several notable activities in this area include and climatology is the nonparametric Mann– farming, industrial factories (palm oil, cement, Kendall test (Burn and Elnur, 2002, Ptak et al., food, and electrical), and shipping (Sany et al., 2019). In this study, Mann-Kendall trend test has 2013). been applied to detect the trends of marine water quality index and the parameters which contributes to the pollution of the Klang estuary. The advantage of the Mann–Kendall test is that it does not require a priori knowledge of the distribution of analysed variables and is therefore preferred over parametric tests (Hirsch et al., 1991). For the purpose of to calculate the sign and magnitude of trends, Sen’s slope 100 estimator is preferred in literature (Sen, 1968). Sen’s slope estimator is less sensitive to outliers not requiring that the variables have Gaussian probability distribution. Finally, the Pettitt test was used to detect the changing point, and then the dataset can be divided into two sub-sequences (Pettitt, 1979). The non-parametric test had been widely used to detect significant trends in time series. It also has the advantage that their power and Figure 1; Sampling and monitoring station of significance are not affected by the actual Klang estuary distribution of the data (Ptak et al., 2019). Thus, this method is highly suitable to be applied in Data Collection detecting trends of skewed hydrologic time series A secondary dataset of marine water was containing outliers (Jamwal et al., 2011, Samsudin identified based on availability of data starting et al., 2017, Ptak et al., 2019). The objective of from 2010 to 2017. The data were collected and the paper was to analyse a long-term marine monitored by Department of Environment water quality index and the parameters variations Malaysia consisted of 12 marine water in the Klang estuary on the 8-year-period (2010–

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Samsudin et al., Marine water quality Index trend of the Klang Estuary in the years 2010-2017 parameters namely as Temperature (TEMP), pH, If DO < 3, or DO > 10, SI =10% (3) Turbidity (TUR), Conductivity (COND), Salinity, dissolved oxygen (DO), total suspended solid ii) SINH3 was sub index of unionized (TSS), faecal coliform, ammoniacal nitrogen (NH3- ammonia, where N), nitrate (NO3), oil and grease (O&G) and -4.6(NH ) SINH3 = 100exp 3 (4) phosphate (PO4).

Data Pre-treatment iii) SIFC was sub index of faecal Preliminary processing on the data matrix coliform, where which included the reassembling the data was SIFC = 100exp-0.005(FC) carried out initially (Gazzaz et al., 2012, Samsudin et al., 2019). Data which were below the detection If FC ≥ 500 MPN, SI = 8% (5) limit were complemented with values equal to half the detection limit. The total number of missing iv) SITSS was sub index of total data in the data points was very small (∼3 %) suspended solids, where compared to the overall data. In order to facilitate SITSS = 95.8exp-0.0043(TSS) the data analysis, the nearest neighbour method which examines the distance between each point If TSS > 100 mg/L, SI = 20% (6) and the closest point to it (Azid et al., 2014). The nearest neighbour method is the simplest v) SIO&G was sub index of oil and scheme, where the end points of the gaps are grease, where used as estimates for all missing values SIO&G = 98exp-0.21(O&G) (7) (Dominick et al., 2012, Azid et al., 2014). According to Azid et al., (2014), the equation vi) SINO3 was sub index of nitrate, where -0.35(NO ) applied in this method is shown in Eq. 1: SINO3 = 94.83exp 3 (8)

푥2−푥1 푦 = 푦 푖푓 푥 ≤ 푥 + [ ] or 푦 = 푦 푖푓 푥 > 푥 + vii) SIPO4 was sub index of phosphate, 푖 1 2 푖 1 푥2−푥1 where [ ] (1) -0.002(PO x1000) 2 SIPO4 = 95.2exp 4 (9)

The MWQI was evaluated based on 0 ≤ MWQI ≥ where y is the interpolant, x is the time point of the 100 range where MWQ = 0 was considered as interpolant, 푦1 and 푥1 are the coordinates of the “Poor” while MWQ = 100 was considered as “Excellent”. starting point of the gap, and 푦2 and 푥2 are the endpoints of the gap. Box and Whisker Plot Marine Water Quality Index The box and whisker plot is a picturing data MWQI was used as a method to reflect the which signify the descriptive statistics of the data marine water quality status and its category. set. The famous ‘stem and leaf diagram’ in box MWQI was calculated by multiplying individual plot are representing data semi graphically sub index (SI). According to the Malaysia (Tukey, 1990; Samsudin et al., 2017, Samsudin et Environmental Quality Report 2017 (DOE, 2018), al., 2019). Based on Kannel et al., (2011), this MWQI was acquired using the following equation: method facilitated to investigate the patterns of water quality and pollution sources. The star or MWQI = 푆퐼퐷푂0.2 × 푆퐼푁퐻30.16 × 푆퐼퐹퐶0.14 × asterisks are outrageous outliers that signify 푆퐼푇푆푆0.14 × 푆퐼푂&퐺0.13 × 푆퐼푁푂30.12 × 푆퐼푃푂40.11 (2) cases with values more than three times the height of the boxes. Where: Mann-Kendall Trend Test Statistics of Random

Sample Data i) SIDO was sub index of dissolved The nonparametric Mann-Kendall statistical oxygen for 3 ≥ DO ≥ 7, where test (Mann, 1945; Kendall, 1975, Yue and Wang, SIDO = -85.816 + 55.476 (DO) – 2002, Samsudin et al., 2017) has been commonly 4.142(DO)2 applied to evaluate the significance of a trend at a

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Samsudin et al., Marine water quality Index trend of the Klang Estuary in the years 2010-2017 site. The Mann-Kendall test statistic 푆 is defined as listed below: RESULTS

푛−1 푛 Descriptive Statistics and Box and Whisker 푆 = ∑푖=1 ∑푗=푖+1 푠푔푛 (푋표 − 푋푖) (10) Plot Table 1 showed the descriptive analysis in where the 푋표 are the sequential data values, 푛 is the length of the data set, and Klang estuary for 2010-2017. The mean for TSS, O&G, coliform, NH3N, and NO3 was found above 1 휃 > 0 permissible limit according to Malaysia Marine 푠푔푛(휃) = { 0 푓표푟 휃 = 0 (11) Water Quality Criteria and Standards Class E. −1 휃 < 0 However, the mean for TEMP, DO and PO4 was in good reading. Based on Mann (1945) and Kendall (1975), when The descriptive statistics visualized in the box 푛 ≥ 8, the statistic 푆 is approximately normally and whiskers plot. Box and whisker plots of all distributed with the mean and the variance given marine water quality parameters for 2010-2017 by were shown in Figure 2. The red crosses in the box and whiskers plot correspond to the means 퐸 [푆] = 0 (12) and the central horizontal bars are the medians. The lower and upper limits of the box are the first 푛(푛−1)(2푛+5)−∑푛 푡 푙(푙−1)(2푙+5) and third quartiles, separately. Points in blue are 푉푎푟(푆) = 푙=1 푙 (13) 18 minimum and maximum for each species. The box plot's horizontal width has no statistical where 푡푙 is the number of ties of extent 푙. The meaning. The outliers defined as values that did standardized test statistic Z is computed by not fell within the inner fences or whiskers. The star or asterisk was outrageous outliers signified 푆−1 푆 > 0 value more than three times the height of the box. √푉푎푟(푠) 푍 = { 푆+1 푓표푟 푆 = 0 (14) As the results, almost all the parameters indicated √푉푎푟(푆) 푆 < 0 the outliers (except pH, PO4 and NO3). Annual Mann-Kendall Trend Test The standardized Mann-Kendall statistic 푍 follows Mann-Kendal test was applied to the marine the standard normal distribution with mean of zero water quality parameters data to validate the and variance of one under the null hypothesis of increasing or decreasing trends in Klang estuary. no trend. A positive 푍 value indicates an upward The Mann-Kendall statistics computed on the 8- trend and vice versa. The P value (probability year annual data (2010-2017). Table 2 presents value p) of the Mann-Kendall statistic 푆 of sample Mann-Kendall’s non-parametric tests, in addition data can be estimated using the normal to an estimate for the slope with 95% confidence cumulative distribution function: bound. In this study, a confidence level of 95%, was applied in the Mann-Kendall trend test. The 푝 = 0.5 − Ф(|푍|) (15) ‘confidence level’ percentage which is used to indicate the reliability of an estimate could be Where calculated by subtracting the probability (p) from 1 (Confidence = 1-p %). A confidence level of 95% 푡2 1 |푍| − Ф(|푍|) = ∫ 푒 2 푑푡 (16) confidence corresponds to α = 0.05. In all cases √2휋 0 where the process satisfies the null hypothesis of a given test, the α values fall within the 95% of If the P value is small enough, the trend is quite confidence band around the nominal significance unlikely to be caused by random sampling. At the level α (0.05). Besides each test name is the significance level of 0.10, if p ≤ 0.10, then the computed test statistics and its associated p- existing trend is assessed to be statistically value. P-values are the smallest level of significant. significance at which the null hypothesis would be

rejected. This study showed the null hypothesis is

that, there is no trend in the available data.

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Figure 2;Box and whiskers plot for all marine water quality parameters

Table 1; Descriptive statistic for physical-chemical parameters Parameter Minimum Maximum Mean SD Permissible Limit TEMP (°C) 29.28 38.47 31.90 2.22 2 DO (mg/l) 5.05 7.41 6.46 0.72 4 pH 7.28 7.95 7.52 0.19 NA TUR (NTU) 55.32 60.40 57.06 1.72 NA Cond (mS/cm) 39.50 58.77 45.77 4.90 NA Salinity (ppt) 26.41 36.55 28.89 2.55 NA TSS (mg/L) 10 761 129 213 100 O&G (mg/L) 0.50 2.40 0.96 0.59 0.14 coliform 270 5400 1888 1791 100 (MPN/100ml)

PO4 (mg/L) 0.01 0.10 0.03 0.04 0.075

NH3 (mg/l) 0.00 0.49 0.09 0.16 0.07

NO3 (mg/l) 0.01 0.40 0.11 0.12 0.06

Table 2; Trends of marine water quality parameters in Klang estuary

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Samsudin et al., Marine water quality Index trend of the Klang Estuary in the years 2010-2017

p-value Sen's Parameter Kendall's tau S Var(S) alpha trend (Two-tailed) slope MWQI 0.2546 7.0000 64.3333 0.4544 0.05 1.579167 upward pH -0.1429 -4.0000 0.0000 0.7195 0.05 -0.0099 downward Salinity (ppt) 0.1818 5.0000 64.3333 0.6180 0.05 0.0448 upward Cond (mS/cm) 0.0364 1.0000 64.3333 1.0000 0.05 0.1 upward TUR (NTU) -0.0364 -1.0000 64.3333 1.0000 0.05 -0.0011 downward TEMP (C) 0.2546 7.0000 64.3333 0.4544 0.05 0.196187 upward DO (mg/L) 0.1429 4.0000 0.0000 0.7195 0.05 0.107991 upward TSS (mg/L) -0.0714 -2.0000 0.0000 0.9049 0.05 -3.67308 downward O&G (mg/L) 0.1091 3.0000 64.3333 0.8031 0.05 0.0388 upward coliform -0.2857 -8.0000 0.0000 0.3988 0.05 -71.4241 downward (MPN/100ml) PO4 (mg/L) -0.2646 -7.0000 61.6667 0.4448 0.05 -0.00355 downward NH3 (mg/l) -0.0714 -2.0000 0.0000 0.9049 0.05 -0.00166 downward NO3 (mg/l) -0.2143 -6.0000 0.0000 0.5484 0.05 -0.01536 downward

Figure 3; Annual trends of marine water quality parameters in Klang estuary

Sen’s slope found a positive or negative value which quantified levels of the Mann-Kendall test

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(Bouza-Deaño et al., 2008). A positive value of Klang river flows to Klang estuary through the statistic S exhibits an increase in constituent densely populated area in the urban city of Kuala concentrations of the parameters over time, while Lumpur. Along the way the river transported a negative value of statistic S exhibits a decline in different kinds of particulates into the surface constituent concentrations of the parameters over water, resulting in the variation of pollution time. In reference to hydrological years, a sources (point and non-point). Based on Sany et significant trend is noticeable, but not statistically al., (2013), the area is affected by pollution from significant; however, the changes of fluctuations non-point sources, for example port development particularly occurred in the scope of the activities, shipping and land runoff from rivers and parameters. Salinity, COND, TEMP, DO and O&G mangrove forests. showed the upward trend in 8-year period in The DO in water is acts as an indicator of Klang estuary. Meanwhile, the downward trend physical, chemical and biological activities of the has been detected for several physico-chemical water body. There is strong correlation between parameters in Klang estuary during 2010-2017 the amount of fresh water in the streams/rivers period such as pH, TUR, TSS, coliform, PO4, and DO. The higher the availability of fresh waters NH3N and NO3. Detection of downward trends for in the water bodies, the higher the amount of DO these parameters indicates that there is an and vice versa. Diffusion of nutrients and improvement of marine water quality. Figure 3 pesticides from agricultural field and domestic visualized the annual trends of marine water waste disposal from Klang estuary increased, and quality parameters in Klang estuary. These results very likely to decrease the amount of DO in Klang indicated there is anthropogenic contribution to estuary. It is though not surprising that the relation the Klang estuary which includes organic between DO is inversely proportional with the eutrophication pollution from domestic decrease trend in NH3N and NO3. The alliances wastewater. between these parameters are suspected to be resulting from the municipal waste discharge (Wyrwas and Zgoła-Grześkowiak, 2013). The YEAR / MWQI Mann-Kendall test showed the upward trend of 100 O&G concentration. Besides, this parameter has 95 exceeded the permissible limit of Malaysia Marine 90 Water Quality Criteria and Standards (0.140 85 mg/L). This is believed that the nonpoint source 80 from fishery boats is major contribute to the high 75 concentration of O&G in Klang estuary. Based on MWQI 70 Omar et al., (2018), the estuary is a well-known 65 spot for fishing activities for local population and 60 55 home for various aquatic animals such as fish, 50 mollusks, cockles, and mussels. 2010 2012 2014 2016 2018 NO3 is the most oxidized forms of nitrogen YEAR and the end product of the aerobic decomposition of organic nitrogenous matter (Mustapha, 2013).

Figure 4; Annual Trend of MWQI in Klang The trend of NO3 in the Klang estuary may be estuary (2010-2017) mainly due to organic materials receiving from the catchment area in the basin. NO3 may find its way MWQI was calculated from year 2010 to 2017. into water bodies through oxidation of ammonia According to Table 2 and Figure 4, the Mann- form of nitrogen to NO3 formation (Mustapha Kendall test and Sen’s slope demonstrated a 2013). The decrease in trend of NH3N is concern positive trend in annual value of MWQI (Sen’s because of its potential to create positively impair slope = 1.5792), the increase in trends of MWQI water quality. According to Shrestha and Kazama over the period of study specifies that the quality (2007), this organic waste leads to the anaerobic of the marine water in Klang estuary is getting conditions, hence resulted in the formation of better form year to year. ammonia and organic acids that cause the reduction of pH (Figure 3). Besides, the pH may decrease once the TEMP increase (Samsudin et DISCUSSION al., 2019). The downward trend of NH3N will literally result to the fluctuation in the water

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temperature. PO4 and coliform showed the of view of water management. A significant part of downward trend from 2010-2017. The result the Klang estuary will further intensify this un- suggested that both parameters are suspected to favorable condition in terms of both quantity and be originated from the animal faecal, surface quality of water. As an application potential, the runoffs and sewage treatment plant effluent situation captured by the analysis of the MWQI in discharge (Chigor et al., 2010) and it is potentially Klang estuary, considered along its entire course, due to the high loading of dissolved organic should be recorded for the future reference and matter or other liquid organic waste deposited into marine water monitoring program the estuary. The primary sources of TSS in receiving CONFLICT OF INTEREST waters are agricultural and residential run-off. The authors declared that present study was Several factors can contributes to TSS and TUR performed in absence of any conflict of interest. in surface water for such as, decrease in the river /stream bank vegetation and uncontrolled ACKNOWLEGEMENT increase in population and urbanization in recent The authors would like to thank the Water & times especially in developing countries can Marine Division, Department of the Environment speed up the process of soil erosion and can (DOE) for their permission to utilize the marine contributes to the level of suspended particles water quality data for this study. such as clay and silt (Huang et al. 2007). Land based activities that cause erosion and AUTHOR CONTRIBUTIONS contributed to the suspended solids transported SMS designed and performed the experiments downstream by Klang and Langat River, could and also wrote the manuscript. AA and KY influence the quantity of sediment deposited in the designed experiments and reviewed the estuary (Haris and Aris, 2015). The significant manuscript. All authors read and approved the increase in these solids can impact the health of final version. the stream and the organism that live there Copyrights: © 2019@ author (s). (Gupta et al. 2003). Fortunately, the decreasing This is an open access article distributed under the trend of TSS and TUR in Klang estuary will terms of the Creative Commons Attribution License increase the clarity of the water which will (CC BY 4.0), which permits unrestricted use, increase the amount of sunlight able to penetrate distribution, and reproduction in any medium, the water, thus increasing the photosynthetic rate. provided the original author(s) and source are The Mann-Kendall resulted the declining trend credited and that the original publication in this MWQI for Klang estuary from 2010-2017 (Figure 4). This result suggested the improvement of journal is cited, in accordance with accepted marine water quality in Klang estuary. The academic practice. No use, distribution or decreasing trend of several component of MWQI reproduction is permitted which does not comply parameters (TSS, coliform, NO3, NH3 and PO4) with these terms. contribute to the decreasing of MWQI trend. REFERENCES CONCLUSION Abdullah, A.R., 1995. Environmental pollution in This study determined the trends in marine Malaysia: trends and prospects. TRAC water quality parameters between 2010-2017 trends in analytical chemistry, 14(5), pp.191- using Mann-Kendall test. The results presented in 198. this paper reveal positive trends in MWQI as well Azid, A., Juahir, H., Toriman, M.E., Kamarudin, as DO, NH3N, NO3, TSS, coliform and PO4. As M.K.A., Saudi, A.S.M., Hasnam, C.N.C., these results indicate Klang estuary has Aziz, N.A.A., Azaman, F., Latiff, M.T., experienced a mild pollution trend due to Zainuddin, S.F.M., Osman, M.R., Yamim, M., anthropogenic influence from domestic activities 2014. Prediction of the level of air pollution in the vicinity of the estuary. Further studies using using principal component analysis and a consistent time period of analyses is required to artificial neural network techniques: A case derive at any spatial pattern. study in Malaysia. Water, Air, & Soil In summary, the methods applied in this study Pollution, 225(8), 2063. are successful in the assessment of marine water Bouza-Deaño, R., Ternero-Rodriguez, M., & quality trends in Klang estuary. The results gained Fernández-Espinosa, A. J., 2008. Trend in this study are notably important from the point study and assessment of surface water

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