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– Bioscience Research, 2019 volume 16(S1): 59-68 60 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.