Journal of Chemistry
Volume 2017 (2017), Article ID 1590329, 12 pages
https://doi.org/10.1155/2017/1590329

Research Article

Assessment of Near-Bottom Water Quality of Southwestern Coast of Sarawak, Borneo, Malaysia: A Multivariate Statistical Approach

Chen-Lin Soo,¹ Cheng-Ann Chen,1,2 and Shabdin Mohd-Long¹

¹Faculty of Resource Science and Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
²Borneo Marine Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia

Correspondence should be addressed to Cheng-Ann Chen; chengann@ums.edu.my

Received 27 March 2017; Accepted 15 May 2017; Published 14 June 2017

Academic Editor: Wenshan Guo

Copyright © 2017 Chen-Lin Soo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The study on Sarawak coastal water quality is scarce, not to mention the application of the multivariate statistical approach to investigate the spatial variation of water quality and to identify the pollution source in Sarawak coastal water. Hence, the present study aimed to evaluate the spatial variation of water quality along the coastline of the southwestern region of Sarawak using multivariate statistical techniques. Seventeen physicochemical parameters were measured at 11 stations along the coastline with approximately 225 km length. The coastal water quality showed spatial heterogeneity where the cluster analysis grouped the 11 stations into four different clusters. Deterioration in coastal water quality has been observed in different regions of Sarawak corresponding to land use patterns in the region. Nevertheless, nitrate-nitrogen exceeded the guideline value at all sampling stations along the coastline. The principal component analysis (PCA) has determined a reduced number of five principal components that explained 89.0% of the data set variance. The first PC indicated that the nutrients were the dominant polluting factors, which is attributed to the domestic, agricultural, and aquaculture activities, followed by the suspended solids in the second PC which are related to the logging activities.

1. Introduction

Coastal water quality is one of the worldwide environmental concerns and is of general growing concern in Malaysia. However, most studies were focused on microbiological and heavy metal contamination in West Malaysia [1–5]. Sarawak, which is in East Malaysia, is the largest state of Malaysia. Although deterioration of the coastal environment due to increasing population and urbanization is noticeable in Sarawak [6], the study conducted on Sarawak coastal water is scarce. Aquaculture and domestic sewage with high nutrients content is being discharged directly into rivers [7] while deforestation for timber production and agricultural development has increased soil erosion and inputs of fertilizers in Sarawak River [8, 9], all of which could lead to increased sedimentation and eutrophication in coastal areas.

Regular monitoring is recognized to be an essential step for the characterization of water quality, and the data is useful in subsequent management decisions for the coastal ecosystem. Comprehensive study on surface water quality has been conducted worldwide but near-bottom water quality is often being neglected in water quality monitoring. Subsurface and near-bottom water often exhibited distinct different water quality due to inadequate mixing in deep water column [7, 10, 11]. Water quality is a principal factor that influences the biota community structure and health condition [12–16]. The study on near-bottom water quality is necessitated and pertinent to demersal fish and benthos community structure.

Multivariate statistical techniques have been proven to be useful in dealing with large sets of monitoring data and provide valuable insights into water quality study [17–21]. Among them, cluster analysis (CA) and principal component analysis (PCA) have been applied in the assessment of spatial variation of tidal river and freshwater forest streams water quality in Sarawak [7, 9, 22]. However, the study on Sarawak coastal water quality is scarce; and the application of CA and PCA for the assessment of the Sarawak coastal water quality has not yet been conducted. Hence, this study aimed to investigate the southwestern Sarawak coastal water quality and to identify pollution sources contributing to the spatial variations in Sarawak coastal water quality by the integration of CA and PCA methods.

2. Materials and Methods

2.1. Study Area and Sampling Stations

The present study was conducted in the southwestern region of Sarawak, Borneo, Malaysia, where the capital city of Sarawak, Kuching, was located. The stations stretched from the coastal area near Batang Saribas in the most eastern part of the region to the coastal area at Sematan which is the most western part of the region. A total of 11 stations were selected along the coastline with approximately 225 km length (Figure 1).

Figure 1: Study area and sampling stations along the coastline of the southwestern region of Sarawak.

2.2. Field Collection and Laboratory Analysis

Samplings were conducted in February 2012 along the coastline of the southwestern region of Sarawak. In situ parameters including salinity, temperature, pH, and dissolved oxygen (DO) were measured using a multiparameter water quality meter (PCD650, Eutech). The turbidity and transparency were measured using a turbidity meter (Mi415, Milwaukee) and a Secchi disk with measuring tape, respectively. Triplicate water samples were taken from the near-bottom water column using a 2-L Wildco® Van Dorn water sampler. All sampling bottles were acid-washed, rinsed, and dried before use. Water samples were placed in an ice box and transported to the laboratory for further analysis [23].

All water analyses were performed in triplicate according to standard procedures [23, 24]. Chlorophyll a (Chl-a) was determined from samples filtered through a 0.7 μm Whatman GF/F filter and extracted for 24 h using 90% (v/v) acetone. Total suspended solids (TSS) were assayed as the difference between the initial and the final weight of a 0.7 μm Whatman GF/F filter, after filtration of an adequate sample volume and drying at 105°C. For five-day biochemical oxygen demand (BOD₅), it was determined as the difference between the initial and the final DO content, after a five-day period of incubation of the sample in the dark at 20°C.

Triplicate water samples were filtered through a 0.7 μm Whatman GF/F filter and composited prior to the nitrogen and phosphorus analyses. Inorganic phosphorus (IP) was determined by the colorimetric ascorbic acid method while total phosphorus (TP) was determined as IP after the potassium persulfate digestion of the sample. Organic phosphorus was calculated as the difference between TP and IP. Ammonium-nitrogen (-N) and nitrite-nitrogen (-N) were determined by the phenate method and colorimetric diazotization method, respectively. Nitrate-nitrogen (-N) was determined by the ultraviolet spectrophotometric method while total nitrogen (TN) was determined as -N after the potassium persulfate digestion of the sample. Organic nitrogen (ON) was calculated as the difference between TN and inorganic nitrogen (-N, -N, and -N). A five-point calibration curve was constructed for each chemical analysis. Blank and standard solutions were treated in a similar way to the sample.

2.3. Statistical Analysis

All data were tested for normality and equal variance with the Shapiro-Wilk test and Levene’s test, respectively. Nonparametric tests were used in the subsequent statistical analyses as the data were not normally distributed and unequal in variances. The Kruskal-Wallis test was carried out to determine the significant differences between the 11 sampling stations. Cluster analysis was used to investigate the grouping of the sampling stations using the water quality parameters collected at the study area. -score standardization of the variables and Ward’s method using squared Euclidean distances were used as a measure of similarity. A dendrogram was used to interpret the result of the cluster analysis. The cluster was statistically significant at a linkage distance < 60% and the number of clusters was decided by the practicality of the results [25]. The Spearman rank correlation was performed to determine the relationship among all the parameters. Principal component analysis (PCA) was conducted to characterize the loadings of all water quality parameters for each of the PCs obtained having eigenvectors higher than one (Kaiser criterion). The component has significant loading on a variable when the loading is greater than 0.4 [26]. The data were square-rooted and standardized prior to the analysis. The quality of data for PCA was confirmed with the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy test and Bartlett’s test of sphericity. All the statistical analyses were carried out by using the Statistical Package for the Social Sciences (SPSS Version 22, SPSS Inc., 1995).

3. Results

3.1. Coastal Water Quality in the Southwestern Region of Sarawak

Figure 2 illustrates that salinity of the near-bottom coastal water increased steadily from station 1 to station 11. Salinity was significantly low (p value ≤ 0.05) at stations 1, 2, and 3 with a mean of 23.4 whereas salinity at stations 8 and 11 was more than 31. Temperature was significantly low (p value ≤ 0.05) at stations 5, 7, and 9 (<28°C) whereas the highest temperature value was observed at station 1 (36°C). DO was significantly high (p value ≤ 0.05) at stations 1, 2, and 3 with a mean value of 6.0 mg/L but was significantly low (p value ≤ 0.05) at stations 4, 6, and 8 with a mean value of 4.8 mg/L. Nevertheless, all DO values complied with the Malaysia Marine Water Quality Criteria and Standard (MWQS) for an area near estuarine water and river mouth as all DO values in the coastal water were more than 4 mg/L (Table 1). The pH value was relatively consistent from station 4 to station 11, ranging from 7.2 to 7.9, whereas significantly high (p value ≤ 0.05) pH values were observed at stations 1, 2, and 3 with a mean value of 8.6. Significantly low (p value ≤ 0.05) turbidity values (5.4 NTU–27.8 NTU) were observed at stations 5, 7, 8, 9, and 11. Stations 1, 2, and 3 contained the highest turbidity values ranging from 120.7 NTU to 793.7 NTU with significantly low (p value ≤ 0.05) transparency of 0.1 m. The highest transparency value of 2 m was observed at station 7.

Table 1: Sarawak coastal water quality standard according to the Malaysia Marine Water Quality Criteria and Standard (MWQS) [27].

Station
DO
TSS
PO₄
NH₃
NO₂
NO₃

1
Complied
Exceeded
Complied
Complied
Complied
Exceeded

2
Complied
Exceeded
Complied
Complied
Exceeded
Exceeded

3
Complied
Exceeded
Complied
Complied
Exceeded
Exceeded

4
Complied
Complied
Complied
Complied
Complied
Exceeded

5
Complied
Complied
Complied
Complied
Complied
Exceeded

6
Complied
Complied
Complied
Complied
Complied
Exceeded

7
Complied
Complied
Complied
Complied
Complied
Exceeded

8
Complied
Complied
Complied
Complied
Complied
Exceeded

9
Complied
Complied
Complied
Complied
Complied
Exceeded

10
Complied
Complied
Complied
Complied
Complied
Exceeded

11
Complied
Complied
Complied
Complied
Complied
Exceeded

MWQS
4 mg/L
100 mg/L
0.075 mg/L
0.070 mg/L
0.055 mg/L
0.060 mg/L

The parameter that violated the standard guideline value was indicated in italics.

(a)

(b)

(c)

(d)

(e)

(f)

Figure 2: In situ parameters include (a) salinity, (b) temperature, (c) DO, (d) pH, (e) turbidity, and (f) transparency along the coastline of southwestern Sarawak. The same letter indicates no significant difference between the stations at value > 0.05.

Figure 3 illustrates that Chl-a concentration ranged from 0.1 mg/m³ to 3.5 mg/m³ along the Sarawak coastline but it was not significantly different between stations (p value > 0.05). Chl-a concentrations at most stations were categorized as oligotrophic status except those at stations 8, 9, and 10 (mesotrophic status) and station 1 (eutrophic status) in the present study (Table 2). TSS was significantly high (p value ≤ 0.05) at stations 1, 2, and 3, ranging from 196.1 mg/L to 477.8 mg/L, which exceeded the MWQS. On the other hand, station 4 to station 11 contained less than 100 mg/L of TSS and complied with the MWQS. BOD₅ concentrations in Sarawak near-bottom coastal water ranged from 0.9 mg/L to 2.6 mg/L. The BOD₅ was significantly low at stations 4, 5, and 6 with a mean value of 1.1 mg/L. Significantly high (p value ≤ 0.05) BOD₅ was observed at stations 1, 2, 3, and 7 where the BOD₅ was more than 2 mg/L.

Table 2: Trophic status of Sarawak coastal water [28].

Station
Chl-a
TP
TN

1
Eutrophic
Mesotrophic
Oligotrophic

2
Oligotrophic
Eutrophic
Mesotrophic

3
Oligotrophic
Hypertrophic
Hypertrophic

4
Oligotrophic
Hypertrophic
Oligotrophic

5
Oligotrophic
Mesotrophic
Oligotrophic

6
Oligotrophic
Mesotrophic
Oligotrophic

7
Oligotrophic
Hypertrophic
Oligotrophic

8
Mesotrophic
Mesotrophic
Oligotrophic

9
Mesotrophic
Eutrophic
Oligotrophic

10
Mesotrophic
Mesotrophic
Oligotrophic

11
Oligotrophic
Mesotrophic
Oligotrophic

Trophic level
Oligo: Chl-a < 1 mg/m³
Oligo: TP < 0.01 mg/L
Oligo: TN < 0.26 mg/L

Meso: 1 < Chl-a < 3 mg/m³
Meso: 0.01 < TP < 0.03 mg/L
Meso: 0.26 < TN < 0.35 mg/L

Eutro: 3 < Chl-a < 5 mg/m³
Eutro: 0.03 < TP < 0.04 mg/L
Eutro: 0.35 < TN < 0.4 mg/L

Hyper: Chl-a > 5 mg/m³
Hyper: TP > 0.04 mg/L
Hyper: TN > 0.4 mg/L

(a)

(b)

(c)

Figure 3: Water quality parameters include (a) Chl-a, (b) TSS, and (c) BOD₅ in coastal near-bottom water column along the coastline of southwestern Sarawak. The same letter indicates no significant difference between the stations (p value > 0.05).

The highest TP (0.130 mg/L) and OP (0.123 mg/L) concentrations were observed at station 7 as illustrated in Figure 4. Stations 3, 4, and 7 were categorized as hypertrophic status in TP while stations 2 and 9 were categorized as eutrophic status (Table 2). TP concentrations at stations 1, 5, 6, 8, 10, and 11 (≈0.016 mg/L) were significantly lower (p value ≤ 0.05) than at station 7 and were categorized as mesotrophic status. OP concentration at stations 1, 5, 6, 10, and 11 (≈0.006 mg/L) was significantly lower (p value ≤ 0.05) than at station 7. IP concentration in Sarawak near-bottom coastal water ranged from 0.006 mg/L to 0.025 mg/L. Stations 2 and 3 contained significantly high (p value ≤ 0.05) concentrations of IP (>0.020 mg/L) whereas stations 5 to 8 and station 11 contained significantly low (p value ≤ 0.05) IP concentrations (<0.010 mg/L). The IP concentration of near-bottom Sarawak coastal water complied with the MWQS although the highest IP concentration at station 2 (≈0.074 mg/L of PO₄) was close to the guideline of 0.075 mg/L of PO₄. The compositions of organic and inorganic phosphorus fluctuated drastically in coastal water along the Sarawak coastline. Phosphorus content at stations 4 and 7 was mainly OP which constituted more than 70% of the TP. Coastal water at stations 1, 2, and 10 contained mainly IP which contributed 62% to 94% of the TP. Phosphorus content at other stations was rather uniform with 46% of IP and 54% of OP.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

Figure 4: Water quality parameters include (a) TP, (b) IP, (c) OP, (d) TN, (e) -N, (f) -N, (g) -N, and (h) ON along the coastline of southwestern Sarawak. The same letter indicates no significant difference between the stations (p value > 0.05).

TN was significantly high at station 2 (0.320 mg/L) and station 3 (0.478 mg/L) where they were categorized as mesotrophic and eutrophic status, respectively. TN concentrations at other stations ranged from 0.078 mg/L to 0.245 mg/L which were categorized as oligotrophic status. Stations 6, 9, and 10 contained significantly low (p value ≤ 0.05) -N (≤0.003 mg/L) and contributed the least to the nitrogen content in the coastal water (≤2%). The highest -N concentration was observed at station 2 (0.025 mg/L) followed by station 3 (0.020 mg/L) whereas the highest composition of -N was observed at stations 4 and 5 (≈13%). The high -N concentrations at station 2 (≈0.081 mg/L of NO₂) and station 3 (≈0.065 mg/L of NO₂) exceeded the MWQS (0.055 mg/L of NO₂) in Malaysia (Table 1). The -N concentrations ranged from 0.015 mg/L to 0.041 mg/L along the Sarawak coastline but exhibited a peak of 0.088 mg/L at station 3. Nevertheless, the unionized ammonia (NH₃) concentrations of the Sarawak near-bottom coastal water were low, ranging from 0.0003 mg/L to 0.0229 mg/L, and complied with the MWQS (0.070 mg/L of NH₃). -N contributed from 10% to 37% of the TN where the lowest percentage of -N was observed at station 2 while station 5 recorded the highest -N percentage of TN composition followed by station 10 which was more than 30%. -N concentration steadily increased from station 1 (0.076 mg/L) to station 3 (0.180 mg/L) and remained significantly low (p value ≤ 0.05) from station 4 to station 10 with a mean value of 0.044 mg/L. Nevertheless, -N at station 8 contributed the highest composition (60%) of TN although its concentration was relatively low (0.048 mg/L). According to MWQS, NO₃ in Sarawak coastal water exceeded the guideline value of 0.06 mg/L where the NO₃ concentrations ranged from 0.14 mg/L to 0.80 mg/L. Like -N, ON concentration also steadily increased from station 1 (0.115 mg/L) to station 3 (0.190 mg/L) and was significantly higher (p value ≤ 0.05) than those at most of the stations. Station 7 (0.110 mg/L) and station 9 (0.135 mg/L) also contained significantly high (p value ≤ 0.05) ON concentrations. Significantly low (p value ≤ 0.05) ON concentration (0.008 mg/L) was observed at station 5 where it contributed the least to the nitrogen content (9%) when compared to those at other stations that contributed from 30% to 63% of TN.

3.2. Cluster Analysis

Figure 5 illustrates that near-bottom water quality of the southwestern coast of Sarawak can be grouped into four significant clusters at a linkage distance < 60% [25]. Cluster 1 consisted of station 1 which was located near the river mouth of Batang Saribas while cluster 2 consisted of station 2 and station 3 which were located near Batang Lupar and Batang Sadong, respectively. Station 7 which was located near the Sibu Laut River was grouped as cluster 3. Those other stations were grouped as cluster 4.

Figure 5: Clusters of the 11 sampling stations located along the coastline of southwestern Sarawak.

3.3. Correlation

Table 3 shows that most of the nitrogen (TN, -N, -N, -N, and ON) was significantly (p value ≤ 0.05) and positively correlated ( > +0.6) with pH, DO, and BOD₅ and significantly (p value ≤ 0.05) and negatively correlated ( < −0.6) with salinity. TN was significantly (p value ≤ 0.05) and positively correlated ( = +0.725 to +0.939) with -N, -N, -N, and ON while TP was significantly (p value ≤ 0.05) and positively correlated ( = +0.984) with OP. Although IP was not significantly (p value > 0.05) correlated with TP and OP, it was significantly (p value ≤ 0.05) and positively correlated ( > +0.6) with TN, -N, -N, and ON. Salinity was significantly (p value ≤ 0.05) and negatively correlated ( > −0.6) with pH, DO, turbidity, TSS, and IP. Significantly positive correlations (p value ≤ 0.05; > +0.7) were observed between turbidity, TSS, and BOD₅.

Table 3: Correlation matrix (p value ≤ 0.05) of the in situ and ex situ parameters collected from the 11 sampling stations. Chl-a was excluded from the table as it was not significantly correlated (p value > 0.05) with other parameters.

Parameter
Salinity
Temp.
pH
DO
Turbidity
Transparency
TSS
BOD₅
TP
IP
OP
TN
-N
-N
-N
ON

Salinity

−.839
−.634
−.733
+.603
−.778

−.607

−.655
−.609
−.741
−.675

Temp.

+.652

+.684

+.844
+.606

pH
−.839
+.652

+.778
+.749

+.798
+.849

+.799
+.611
+.854
+.823
+.697

DO
−.634

+.778

+.887

+.790
+.678
+.629
+.702
+.698

Turbidity
−.733
+.684
+.749

+.931
+.729

Transparency
+.603

−.678

TSS
−.778
+.844
+.798

+.931

+.740

BOD₅

+.606
+.849
+.887
+.729

+.740

+.795
+.629

+.677
+.796

TP

+.984

IP
−.607

−.678

+.684

+.670
+.735
+.617

OP

+.984

TN
−.655

+.799
+.790

+.795

+.684

+.843
+.725
+.939
+.929

−N
−.609

+.611
+.678

+.629

+.843

+.775
+.691

−N
−.741

+.854
+.629

+.670

+.725

+.833

−N
−.675

+.823
+.702

+.677

+.735

+.939
+.775
+.833

+.784

ON

+.697
+.698

+.796

+.617

+.929
+.691

+.784

3.4. Principal Component Analysis

A total of five principal components (PCs) were obtained with eigenvalues more than one which accounted for around 89.0% of the total variance in the 17 in situ and ex situ water quality parameters of the Sarawak coastal water (Table 4). The first component (PC1), accounting for 50.9% of the total variance in the data sets of the coastal water, has significant positive loadings on DO, pH, BOD₅, TN, -N, -N, and ON. The PC2 accounting for 16.9% of the total variance has significant negative loading on salinity and positive loadings on temperature, pH, turbidity, TSS, and -N. The PC3 (7.5% of the total variance) has significant positive loading on IP and negative loading on transparency while the PC4 (7.1% of the total variance) has significant positive loadings on TP and OP. Finally, the PC5 (6.5% of the total variance) is significantly and positively loaded on Chl-a but negatively loaded on -N.

Table 4: Loadings of the in situ and ex situ water quality parameters on the first five Varimax-rotated PCs (eigenvalue > 1) along the coastline of southwestern region Sarawak.

Rotated component matrix

Parameter
Component

1
2
3
4
5

Salinity

−0.641

Temperature

+0.836

DO
+0.878

pH
+0.561
+0.760

Turbidity

+0.647

Transparency

−0.877

Chl-a

+0.870

TSS

+0.812

BOD₅
+0.800

TP

+0.972

IP

+0.825

OP

+0.960

TN
+0.821

-N
+0.826

-N

+0.603

−0.575

-N
+0.712

ON
+0.697

Initial eigenvalue
8.7
2.9
1.3
1.2
1.1

% of variance
50.9
16.9
7.5
7.1
6.5

Cumulative %
50.9
67.8
75.3
82.4
89.0

Rotation converged in 6 iterations.

4. Discussion

The present study demonstrated that near-bottom coastal water quality varied substantially along the southwestern Sarawak coastline. Stations 1, 2, and 3 were located near the river mouth of three big rivers which are Batang Saribas, Batang Lupar, and Batang Sadong, respectively. Cluster analysis grouped the three stations as cluster 1 and cluster 2 indicates that they shared more similar characteristics in water quality than stations that were grouped in clusters 3 and 4. Particularly, they all contained significantly (p value ≤ 0.05) lower salinity value and significantly (p value ≤ 0.05) higher pH, DO, turbidity, and TSS values than those at other stations which are located near relatively smaller river basins. Among them, the highest Chl-a, TSS, and BOD₅ values were observed at station 1; hence, it was separated from stations 2 and 3 and grouped as cluster 1. These three stations also showed sign of deterioration in water quality when compared to other stations. Suspended solids in coastal water of these three stations exceeded the guideline value of the MWOS. IP content at station 2, -N content at station 3, and -N content at the two stations also exceeded the guideline value of the MWQS. Station 1 was the only station along the coastline where Chl-a status was categorized as eutrophic status. High suspended solids and nutrient content were often due to the increase in land use in the surrounding area [30, 31]. Deterioration of water quality in this region is most probably due to the deforestation and oil palm plantation [32]. Reference [33] also reported that a spit was formed in the Baram River mouth and continued to expand due to the erosion associated with deforestation and land use changes in the upstream region.

Coastal water quality at stations 4 to 11 was relatively good except for station 7. The particular station contained high organic content as indicated by high BOD₅, TP, OP, and ON and was grouped as cluster 3. Station 7 was located near the Sibu Laut River which forms the western boundary of the Kuching Wetland National Park. Shrimp farms and villages were located along the river which contributed substantial organic matter to the river and subsequently the coastal area [7, 34].

Coastal water quality at other stations was relatively good and mostly complied with the MWQS, except for -N where all stations violated the MWQS. The high -N content in Sarawak coastal water is most probably due to the high -N sources from surface river runoff through agriculture and domestic wastewater discharge. The negative correlation between salinity and nitrogen and positive correlation between pH and nitrogen indicated the contribution of riverine nitrogen source to the Sarawak coastal water. Reference [7] demonstrated that the Sibu Laut River contained high -N concentration which is in agreement with the -N concentration in the coastal water. In addition, the high DO content in coastal water also accelerates the decomposition and nitrification process where organic content was converted to the end product of -N.

The present study demonstrated that Sarawak near-bottom coastal water was rich in total phosphorus where it was categorized from mesotrophic to hypertrophic status. Stations 3, 4, and 7 were categorized as hypertrophic status where the phosphorus was mainly organic phosphorus. Likely sources of phosphorus are dwellings and industries [30, 31] as significantly higher phosphorus concentrations were observed near shrimp farms and domestic wastewater discharges in the area [7]. Similarly, [30] demonstrated that total phosphorus concentrations were significantly higher in subbasins with high densities of wastewater treatment plants and agricultural activities during summer. On the other hand, total nitrogen content in Sarawak coastal water was low where most of the stations were categorized as oligotrophic status except stations 2 and 3 which were categorized as mesotrophic and hypertrophic status, respectively.

The present study demonstrated that Sarawak coastal water has the widest ranges of salinity, temperature, and pH when compared with those in other coastal areas in Malaysia (Table 5). This is most probably due to the substantial number of riverine inputs into the coastal area of Sarawak. The DO value in the present study was found to be relatively higher than those in both Penang Island and Langkawi Island (<4 mg/L) but it was relatively lower than that in Port Dickson (5.5–6.6). Comparatively, the turbidity, -N, and TP values in the present study were lower than those in the coastal area of Penang Island. The coastal water in Penang Island was also recorded with the highest turbidity (1750.8 NTU), -N (0.50 mg/L), and TP (0.199 mg/L) in Malaysia. The authors [29] demonstrated that the pollution was contributed from various sources and discharges from the existing mainland itself. On the other hand, the Chl-a concentration in the present study was found to be lower than that in coastal water of Langkawi Island where the authors attributed the high Chl-a concentration to the monsoonal runoff in the area. The -N and IP concentrations in the present study were lower than those in coastal water of Port Dickson. The authors [4] attributed the high nutrient content in Port Dickson sea to growth in tourism, shipping, small industries, and urbanization. Nevertheless, the -N, -N, and IP concentrations in Sarawak coastal water were higher than those in coastal waters of Port Dickson and Langkawi Island.

Table 5: Summary of coastal water quality in Malaysia.

Area
Salinity (ppt)
Temp. (°C)
DO (mg/L)
pH
Turbidity (NTU)
Chl-a (mg/m³)
-N (mg/L)
-N (mg/L)
-N (mg/L)
TP (mg/L)
IP (mg/L)
Reference

Pulau Tuba, Langkawi
33.1–34.0
27.4–29.5
3.8–6.5
7.7–8.2
ND
5.67–12.4
ND
0.001–0.004
0.002–0.027
ND
0.000–0.001
[3]

Port Dickson
29.7–30.0
28.6–28.9
5.5–6.6
8.2–8.3
ND
ND
0.12–0.18
ND
0.01–0.05
ND
0.06–0.09
[4]

Northeast of Penang Island
ND
ND
3.7–4.9
7.5–8.0
21.4–1750.8
ND
ND
ND
0.30–0.50
0.088–0.199
ND
[29]

Southwestern of Sarawak
23.0–31.7
26.2–36.0
4.5–6.1
7.2–8.6
5.4–793.7
0.1–3.5
0.015–0.088
0.002–0.025
0.031–0.180
0.013–0.130
0.006–0.025
Present study

The value was converted from μg/L to mg/L. The value was converted from mg PO₄/L to mg P/L. ND: not determined.

The PCA was used to explore the most crucial factors determining the spatial variations in physicochemical parameters of the near-bottom coastal water of southwestern Sarawak. The PC1 indicates that organic pollution and nitrogen enrichment occurred in the present study area as it has significant positive loadings on BOD₅, TN, -N, -N, and ON. These factors indicate an inflow of effluents from longhouses and residential area, aquaculture wastewater discharge, and agricultural surface runoff which largely consisted of organic and nitrogen pollutants. The PC1 has the largest proportion of the total variance indicating that sewage and aquaculture discharge and agricultural runoff are the major source of coastal water contamination in southwestern Sarawak. The result is in agreement with the PCA study of [7] where high positive loadings (>0.8) on IP, -N, -N, TN, and Chl-a in PC1 were found in the tidal river that drains into Sarawak coastal area.

In addition to organic and nitrogen enrichment, accumulation of suspended solids occurred in Sarawak coastal water as indicated by the high positive loading on TSS in PC2. The positive loadings on turbidity and -N are associated with the presence of suspended solids whereas the negative loading on salinity in PC2 suggests that freshwater inflow was a key factor in suspended solids variation. The Sarawak forest is subjected to high timber harvesting pressure rendering sedimentation problem in its forest streams [8, 35–37]. Logging activities in the surrounding area have caused sedimentation and increased suspended solids level in the river and subsequently into the coastal area. Reference [9] demonstrated that logging was the main factor in regulating water quality of Sarawak forest streams compared to sewage discharge. In the present study, the Sarawak coastal water quality demonstrated different trend where dwellings, aquaculture, and agriculture were the major source compared to logging activities. This is most probably due to the study in [9] that was conducted in inland freshwater forest streams which were subjected to active logging activities and lower population densities. Phosphorus enrichment in Sarawak coastal water was described in PC3 and PC4 with positive loadings on IP, TP, and OP. Finally, the PC5 indicating sign of eutrophication in Sarawak coastal water and the growth of phytoplankton are stimulated by the high concentration of -N.

5. Conclusions

The present study demonstrated that environmental conditions in southwestern Sarawak near-bottom coastal waters have been altered due to increasing population and resulting development. Results showed that -N concentration exceeded the MWQS in the coastal waters. Suspended solids exceeded the guideline value when receiving freshwater input from large river basins that were subjected to deforestation and oil palm plantation. TP content in Sarawak near-bottom coastal waters was categorized as eutrophic and hypertrophic status in regions receiving sewage discharge and runoff. The CA indicated that the coastal water showed spatial heterogeneity and can be grouped into four significant clusters. The PCA indicated that dwellings, aquaculture, and agriculture are the major factor contributing to the spatial variations on Sarawak near-bottom coastal water quality followed by logging activities.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Acknowledgments

The authors appreciate the financial supports provided by the Ministry of Higher Education (MOHE), Malaysia, through FRGS (07(03)/786/2010(67)), and the Universiti Malaysia Sabah and Universiti Malaysia Sarawak through GKP0015-STWN-2016 and the facilities provided by Universiti Malaysia Sarawak.

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