Understanding Two Decades of Turbidity Dynamics in a Coral Triangle Hotspot: The Berau Coastal Shelf

Abstract

Turbidity serves as a crucial indicator of coastal water health and productivity. Twenty years of remote sensing data (2003–2022) from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellite were used to analyze the spatial and temporal variations in turbidity, as measured by total suspended matter (TSM), in the Berau Coastal Shelf (BCS), East Kalimantan, Indonesia. The BCS encompasses the estuary of the Berau River and is an integral part of the Coral Triangle, renowned for its rich marine and coastal habitats, including coral reefs, mangroves, and seagrasses. The aim of this research is to comprehend the seasonal and interannual patterns of turbidity and their associations with met-ocean parameters, such as wind, rainfall, and climate variations like the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). The research findings indicate that the seasonal spatial pattern of turbidity is strongly influenced by monsoon winds, while its temporal patterns are closely related to river discharge and rainfall. The ENSO and IOD climate cycles exert an influence on the interannual turbidity variations, with turbidity values decreasing during La Niña and negative IOD events and conversely increasing during El Niño and positive IOD events. Furthermore, the elevated turbidity during negative IOD and La Niña coincides with rising temperatures, potentially acting as a compound stressor on marine habitats. These findings significantly enhance our understanding of turbidity dynamics in the BCS, thereby supporting the management of marine and coastal ecosystems in the face of changing climatic and environmental conditions.

1. Introduction

Turbidity is a measure of the amount of light absorbed or scattered by total suspended matter (TSM) in the water column. It plays a crucial role in assessing water health and productivity. A high turbidity reduces sunlight penetration as it affects light availability and the depth of the photic zone, which is essential for photosynthesis by phytoplankton [1]. This decrease in light availability can hinder the growth of corals and seagrass meadows [2]. Furthermore, the TSM can settle on the seafloor, smothering benthic organisms. Additionally, the TSM can directly smother coral polyps and seagrass blades, reducing their growth rates [2].

In the Berau Coastal Shelf (BCS) area, located in East Kalimantan, Indonesia, the turbidity levels have significant implications for coastal ecosystems [3]. This region includes the estuary of the Berau River and 31 islands in the Berau Archipelago [3]. The BCS consists of barrier reefs in the northern part, with depths ranging from 20 to 50 m, while the southern part faces the shoreline, featuring shallower waters [4]. The BCS is recognized as part of the coral triangle, which has remarkable biodiversity, including various species of coral reefs, seagrasses, mangroves, sea turtles, reef fish species, and manta rays [3,5,6,7].

Turbidity is one of primary coastal ecosystem stressors in the BCS area, particularly because of the sediment and pollutants carried by the Berau River’s plume from the terrestrial environment. The increasing turbidity is correlated with a decrease in land cover due to clearing of the rainforest [8]. The seagrass meadows in the BCS respond strongly to the increasing sediment load by experiencing a reduction in seagrass cover [3]. Moreover, there is significant correlation between the turbidity levels and the changes in coral cover within the Berau archipelagic area [9]. Previous studies on the BCS have primarily used snapshot in situ observations [3,7] and limited remote sensing data [9,10,11]. However, such approaches fail to capture the spatial and temporal variations in turbidity, which can fluctuate, ranging from tidal to interannual scales. Additionally, the turbidity regime is strongly influenced by local processes such as currents, waves, and the type of bed sediment characteristics [10,11,12,13,14]. Furthermore, climate cycles, including rainfall, seasonal winds, the Indian Ocean Dipole (IOD), and the El Niño–Southern Oscillation (ENSO), also contribute to annual and interannual variability in the turbidity regime [12]. It is essential to understand the spatial and temporal variations in turbidity in order to enhance the knowledge regarding the effects of turbidity exposure on coastal ecosystems, particularly within the BCS.

Under climate change conditions, the amplitude and frequency of global climate variability will be altered [13,14]. In such a situation, understanding the specific relationship between global climate phenomena and regional and local oceanographic processes concerning turbidity variability is crucial to anticipating potential impacts of climate change. This understanding also serves as a basis for managing coastal ecosystems, particularly in the BCS, which is part of the Coral Triangle hotspot.

One alternative data source with significant spatial and temporal coverage is the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, which has been orbiting since 2002. This study utilizes continuous satellite imagery data from MODIS covering the period from 2003 to 2022 to investigate the spatial and temporal variations in turbidity on a monthly-to-interannual scale. The objectives of this study are as follows: (1) to examine the spatial and temporal patterns of turbidity in the Berau Coastal Shelf (BCS), focusing on seasonal and interannual variations, and (2) to identify potential met-ocean drivers of turbidity and assess the influence of the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). By addressing these objectives, this study aims to provide insights into the potential impacts of climate change on turbidity and how turbidity drivers affect marine ecosystems. Moreover, the findings of this study contribute to the improved management of marine ecosystems within the BCS area.

The structure of this paper is as follows: Section 2 describes the field sites. Section 3 explains the data and methods used. Section 4 and Section 5 present the results and discussion, respectively. Finally, Section 6 summarizes the conclusions.

2. Site Study

The Berau Coastal Shelf (BCS) (Figure 1) is an ecologically significant region, located within the Coral Triangle in the central Indo West Pacific. This area boasts a rich diversity in species and habitats, including coral reefs and seagrass meadows, sea turtles, and manta rays [3,7,15,16]. The flat reef of the BCS extends from the edge of the continental shelf, at depths of 20–50 m. The seagrass meadows live around the Derawan, Maratua, Samama, and Panjang islands, while mangroves grow around the mouth of the Berau River. The BCS is bordered by the Celebes Sea and the gate of the Makassar Strait to the east, which reaches depths of up to 3000 m. The BCS serves as the host of the Berau River watershed, with a discharge which varies from 20 to 2000 m³/s, with an average of 650 m³/s [8,17]. The tidal regime of the BCS is predominantly mixed and semi-diurnal, with a tidal range of about 1 m during neap tides and 2.5 m during spring tides.

The hydrodynamics circulation of the BCS is primarily influenced by the fresh water flow, winds, and tides. Freshwater discharge controls the hydrodynamics around the river mouth, while monsoonal winds play a significant role in driving the seasonal water circulation in the BCS. From July to September, the BCS experiences the southeast monsoon, characterized by prevailing winds blowing from the south, which induce northerly currents. From December to February, the BCS encounters the northwest monsoon, with prevailing winds blowing from the north, causing southerly currents. During Transition I (March–June), the northern winds weaken, accompanied by a reduction in current strength. Similarly, during Transition II, the southern winds subside, leading to a weakening of the currents as well [18].

The seasonal water circulation significantly affects the spreading of the freshwater river plume originating from the Berau River. The freshwater river plume follows the seasonal pattern of the currents, wherein, during the northeast monsoon, it spreads southward, while, during the southeast monsoon, it predominantly spreads northward. Similarly, during Transition I and II, when the winds and currents are weaker, the river plume becomes more concentrated near the river mouth [16,18].

Additionally, the tidal circulation predominantly follows an east–west flow, with increasing amplitude toward the coast. Meanwhile, the subtidal flow is dominated by a southward direction [4]. Furthermore, the BCS, bordered by the gate of the Makassar Strait, serves as a major pathway of the Indonesian Throughflow (ITF) currents. The ITF transfers water mass, heat, and salt from the Pacific Ocean to the Indonesian Archipelago. Consequently, the temperature and salinity in the BCS are also influenced by the water masses originating from the Pacific Ocean and transported by the ITF [19].

The seasonal precipitation in the BCS has two peaks, occurring approximately in April and November [20]. The interannual variation in precipitation in Kalimantan, in general, is influenced by the ENSO (El Niño–Southern Oscillation) and IOD (Indian Ocean Dipole) climate variability. High rainfall is highly correlated with La Niña episodes and a positive IOD, while low rainfall is correlated with El Niño and a negative IOD [21].

3. Data and Methods

3.1. Remote Sensing Data

The total suspended matter (TSM) data utilized in this study as indicators of turbidity were derived from the Aqua Modis Level 3 satellite product, featuring a spatial resolution of 4 km. The data provider performed atmospheric corrections and then aggregated and projected the data onto a well-defined spatial grid over a specified time period. This dataset comprises monthly data and spans the period from 2003 to 2022. The study area was defined by the coordinates 117.52° E to 119° E and 1.02° N to 2.5° N. The Aqua MODIS satellite product has been widely adopted for developing turbidity estimation algorithms, as summarized by Chen et al. (2015) [22]. Turbidity estimates from the MODIS satellite product have also been used for assessments of ocean health [23,24,25].

In this study, TSM data were extracted from measurements of remote sensing reflectance (rrs) at three specific wavelengths: 645 nm, 488 nm, and 555 nm. The calculation of TSM was conducted using the algorithm established by Zhang et al. (2010) [26]. The rrs data were obtained from the website https://oceancolor.gsfc.nasa.gov/ (accessed on 27 March 2023). To ensure the accuracy and reliability of the TSM calculations, calibration and validation were performed against field observation data and remote sensing processing results previously processes by Ambarwulan et al. (2012) [10].

The TSM data were processed to generate both mean climatology and monthly climatology values, providing insights into the spatial and temporal variation over the 2003–2022 period.

3.2. Met-Ocean Data

Met-ocean data were utilized in this study to analyze the dominant met-ocean variables that influence spatial and temporal turbidity variations. The met-ocean data considered in this research include the monthly means of zonal and meridional wind components, precipitation, sea surface temperature (SST), the Dipole Mode Index (DMI), and the ENSO index. These datasets were sourced from the ERA5 reanalysis product, downloaded from https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5 (accessed on 27 March 2023), with a spatial resolution of 0.25° × 0.25°. The wind components, precipitation, and SST data used in this study covered the marine area within the study region (117.52° E to 119° E and 1.02° N to 2.5° N) and were spatially averaged for analysis. Additionally, the DMI and ENSO indices were acquired from the NOAA website, while the SST was a product of the MODIS satellite. It is noteworthy that these datasets cover the same geographical area as the TSM data.

Although the ERA5 data are categorized as reanalysis products, they have been thoroughly tested and extensively used in various studies in the fields of oceanography and meteorology [27].

4. Results

4.1. Spatiotemporal Pattern

The spatial distribution of the mean climatological turbidity is shown in Figure 2. The highest TSM value is observed at the mouth of the Berau River, ranging 25–35 mg/L, and extending towards the northern side of the BCS, where it encompasses coral reef habitats. Notably, a high turbidity concentration is also noticeable in the southern region due to the presence of the Muara Tabalar River estuary. The mean TSM values gradually decrease towards the offshore area.

The distribution of monthly mean climatological TSM (Figure 3) is significantly influenced by the monsoon winds within the BCS. In March, the TSM concentration is still visible in the southern part of the river mouth due to weak winds and the TSM dispersion caused by the winds in February. In April and May, the TSM distribution remains concentrated near the river mouth and slightly expanding northward. This can be attributed to the direction of the winds and the weaker winds during the transition season, which limit the dispersion of the TSM. The lesser concentration observed in the southern area can be attributed to the presence of the Muara Tabalar estuary.

From June to August, the distribution of TSM becomes concentrated around the river mouth, subsequently spreading northward. This phenomenon is attributed to the prevailing southwest monsoon conditions during this period, characterized by intensified wind speeds primarily originating from the south [18]. The enhanced wind activity facilitates the northward dispersion of TSM. Notably, this dispersion pattern extends to the Berau Barrier Reef, situated to the north of the Berau River mouth.

From September to November (Transition II), a noticeable reduction in the TSM concentration near the river mouth is observed. This decrease in TSM dispersion could be attributed to the weakening of the wind and currents’ velocity, as well as the low precipitation levels during the transitional monsoon phase.

During the period from December to February, a different dispersion pattern emerges, characterized by southward spreads of the TSM. The spreading of TSM is induced by north-to-south winds. This complex interaction of wind and hydrological processes highlights the dynamic distribution of TSM within the BCS throughout the various monsoon phases.

In addition to the northward and southward dispersal associated with monsoonal winds, the TSM concentrations at the river mouth also exhibit fluctuations. High TSM concentrations are observed in May–July and December–January. These fluctuations, with two peaks annually, are associated with local rainfall on the island of Kalimantan and the river flow from the Berau River, which also experiences two peaks in intensity each year.

4.2. Time Series Analysis of Specific Regions

A time series analysis was conducted on the average results of three regions: northern, river mouth, and southern. The division of the averaging zones shown in these areas was selected according to the spatial pattern of the climatological mean of the TSM that showed the TSM spreading to these areas (Figure 2). The zone of spatial averaging is shown in Figure 1. The river mouth area is known to have the highest variability and an average of approximately 20 mg/L (Figure 4). This high variability in turbidity at the river mouth is attributed to TSM transported by river discharge.

In contrast, the northern and southern regions have mean TSM values that are not significantly different, with mean TSM values of 12 mg/L in the northern region and 10 mg/L in the southern region. However, the northern region has a higher variability compared to the southern region (Figure 4). This is because the northern region is closer to the river mouth, making its turbidity more influenced by the variability in turbidity due to river discharge.

The TSM in the southern region shows a high degree of seasonality, where the highest peak of TSM occurs in December, January, and February (Figure 5). This peak coincides with the northwest monsoon winds that drive the TSM towards the southern region. The box plot illustrating TSM variability in the southern region indicates that the monthly range of TSM variability is not significantly distinct. In the northern area, two high peaks of TSM are shown in January and June. The high TSM values during May–July are influenced by the southern monsoon winds, facilitating TSM transport towards the north. Meanwhile, the high TSM values during the period from December to February can be attributed to circular spreading in all directions. In the river mouth area, where turbidity is more influenced by river flow, the monthly median values remain relatively consistent at around 20 mg/L, with a fairly wide interquartile range. This median value indicates that the median turbidity induced by river flow is relatively consistent but with high variability. However, the TSM concentrations in March–April and September are slightly higher than in the other months. Notably, the variability in TSM in the river mouth area is the most pronounced, characterized by interquartile ranges reaching 25 mg/L, while, for the south and north areas, it hovers around 5–7 mg/L (Figure 5).

The higher variability in TSM observed in the northern region compared to the southern region can be attributed to the disproportionate freshwater discharge through the Berau Delta’s channels [28]. The ratio of freshwater outflow through its various channel outlets, specifically the north, middle, and south channels, is quantified as 5:4:1. This disproportionate freshwater discharge underscores the predominant role that both the northern and middle channels play in discharging freshwater, highlighting a substantial allocation of water resources towards these outlets compared to the southern channel. Consequently, the northern region, being closer to the primary freshwater discharge points, experiences greater fluctuations in TSM due to its proximity to the river mouth.

Spectral analysis was applied to the monthly time series data from these regions to expose the dominant variability within each area (Figure 6). The southern region showed a strong annual spectrum with a small peak in the semi-annual spectrum, whereas the northern region showed a strong semi-annual spectrum followed by an annual peak spectrum. The river mouth region showed multiple peaks, indicating high variability in that area. The spectral analysis indicated that the variability in the TSM at the river mouth ranged from intra-seasonal to interannual scales. The interannual variation observed in the river mouth area was significantly higher than that in the northern and southern regions.

4.3. TSM Concentration Versus Met-Ocean Data

4.3.1. Monthly Variation

To analyze the drivers behind the monthly variations in TSM, Pearson’s correlation calculations were conducted. These correlations were applied to the TSM concentrations in the northern, southern, and river mouth regions, in relation to crucial meteorological parameters. These parameters included precipitation, zonal, and meridional wind components, alongside the ENSO (El Niño Southern Oscillation) and IOD (Indian Ocean Dipole) indices. The NINO 3.4 index and the Dipole Mode Index (DMI) were used to represent ENSO and IOD phenomena. The results of these correlation calculations are detailed in

Table 1. Pearson’s R correlation coefficients for the monthly data of the TSM and the monthly data of precipitation, east–west winds, north–south winds, Ocean Dipole Mode (DMI), and El Niño–Southern Oscillation (ENSO) in the north, river mouth, and south areas of the BCS.

	Met-Ocean Variable	r Value	p Value	Correlation
TSM River Mouth	Precipitation	0.075	0.245	Not Significant
	Wind, Zonal	0.151	0.019	Significant
	Wind, Meridional	0.088	0.173	Significant
	ENSO	−0.084	0.192	Not Significant
	DMI	−0.061	0.349	Not Significant
TSM North	Precipitation	0.313	7.70 × 10−7	Significant
	Wind, Zonal	−0.050	0.442	Not Significant
	Wind, Meridional	−0.213	0.001	Significant
	ENSO	0.048	0.456	Not Significant
	DMI	−0.035	0.585	Not Significant
TSM South	Precipitation	0.275	1.55 × 10−5	Significant
	Wind, Zonal	−0.409	4.18 × 10−11	Significant
	Wind, Meridional	−0.590	7.29 × 10−24	Significant
	ENSO	−0.048	0.463	Not Significant
	DMI	−0.097	0.132	Not Significant

.

In the river mouth area, the monthly TSM concentrations showed no significant correlation with the total precipitation. However, in the northern and southern regions, the TSM concentrations showed a significant positive correlation with precipitation. This positive correlation implies that an increase in precipitation within the BCS is associated with an elevated distribution of TSM towards both the north and south areas. The lack of a significant relationship between the TSM and precipitation in the river mouth area may be attributed to the precipitation data used. The precipitation data employed for analysis were averaged spatially over the estuary and seas area, while turbidity at the estuary mouth was more directly influenced by river discharge, which was related to rainfall in the Berau River watershed.

Moreover, when examining the correlation between TSM and winds, the TSM concentrations in the river mouth and northern regions showed no significant correlation with either east–west or north–south wind components. Conversely, the TSM concentrations in the southern area showed a significant negative correlation with both east–west and north–south winds.

Additionally, the correlation calculations between the monthly TSM in the river mouth, northern, and southern regions showed no significant correlation with the monthly DMI and NINO 3.4 indices.

4.3.2. Interannual Variation

To analyze the interannual variations in the TSM concentration originating from the Berau River estuary, a 15-month moving average was applied to the TSM concentration, particularly focusing on the river mouth region. This same moving average technique was also applied to precipitation, wind (both zonal and meridional components), and IOD and ENSO index data. Subsequently, the TSM concentrations were subjected to a correlation analysis with the 15-month moving averages of precipitation, zonal and meridional wind components, and the ENSO and IOD indices.

In the river mouth area, we found an increase in the correlation of interannual TSM variations with precipitation, IOD, and ENSO compared to the monthly variations (

Table 2. Pearson’s R correlation coefficients for 15-month moving average values of the TSM in the river mouth and 15-month moving average of precipitation, east–west winds, north–south winds, Ocean Dipole Mode (DMI), and El Niño–Southern Oscillation (ENSO).

	Met-Ocean Variable	r Value	p Value	Correlation
TSM River Mouth	Precipitation	0.353	1.80 × 10−8	Significant
	Wind, Zonal	0.536	3.04 × 10−19	Significant
	Wind, Meridional	0.536	3.04 × 10−19	Significant
	ENSO	−0.543	7.99 × 10−20	Significant
	DMI	−0.397	1.65 × 10−10	Significant

). The correlation coefficients between the TSM concentrations and precipitation, ENSO, and IOD in the river mouth area were found to be 0.35, −0.54, and −0.35, respectively, all with p values < 0.05. Furthermore, the correlation between TSM and wind also showed an increased value of 0.536 in both zonal and meridional wind components. This indicates that interannual variations in the TSM are significantly associated with precipitation, ENSO, IOD, and surface wind patterns.

5. Discussion

5.1. Spatial and Temporal Distribution Patterns of TSM

One of the most influential variables affecting turbidity in the Berau Coastal System (BCS) is river flow. This is because turbidity in the BCS is caused by sediments transported from the river. Discharge data measured in the Berau River from 2006 to 2008 (Figure 7) show that discharge increases in May–July and November–January. Although the discharge data used are not as extensive as those for TSM analysis, they help explain the monthly climatology of the spatial–temporal pattern of turbidity at the river mouth, which shows increases during May–July and November–January (Figure 3). This is also supported by previous studies that indicate that river discharge is the most influential factor on the concentration of suspended material at the river mouth but not on its spatial dispersion [29]. Additionally, the high fluctuations in river discharge are also associated with a high variability in turbidity at the river mouth (Figure 5b). This pattern of river discharge is also related to the temporal pattern of turbidity in the northern and southern areas. In the northern area, which is closer to the river mouth, the influence of river discharge results in a pattern with two peaks per year in temporal variability, specifically in May–July and November–January (Figure 5a). This is also reflected in the spectral pattern, where semi-annual periods are dominant in the variability spectrum of turbidity in the northern area (Figure 6a). In contrast, the temporal pattern of turbidity in the southern area shows a single peak per year in November–January (Figure 5c), and the spectral pattern exhibits a strong annual period (Figure 6c). This indicates that turbidity variation in the southern area is more influenced by monsoon winds.

The investigation into how TSM is distributed across space and time in the BCS region provides valuable insights. The results indicate that monsoonal winds play a significant role in shaping the spatial distribution of TSM concentrations in tropical areas, while the influence of the Coriolis force remains relatively small [3,13,14,21,22,23,24]. Aligned with the seasonal variations, TSM distribution follows the monsoonal wind pattern, moving southward during the northeast monsoon season (December–March) and showing higher concentration toward the north during the southwest monsoon season (June–August). These results are consistent with the freshwater river plume distribution model, which also shows a southward and northward flow during the northeast and southwest monsoon seasons, respectively [16,18]. The distribution of TSM, which is controlled by the monsoonal winds, is also supported by the correlation between TSM and wind, which has a significant negative value, especially in the southern area, reaching −0.590 for the north–south wind direction. This negative correlation indicates that, when the wind blows towards the south, the concentration of TSM in the southern area will increase. In addition, the distribution towards the south is wider than that towards the north, which can be attributed to the stoke drift of tidal currents flowing towards the south [4]. These findings are in line with the established research emphasizing the interplay between various factors, including wind, tide, and local bathymetry [4,16,18,30,31,32,33].

In estuaries, coastal areas, and shelf regions at high latitudes, the spatial patterns of currents, mixing processes, and transport processes are influenced by the Coriolis force [34,35]. The Coriolis effect becomes significant when the internal Rossby radius of deformation is small. In the case of the Berau Continental Shelf, which is characterized by shallow depths and varying coastal features and is located near the equator, the internal Rossby radius of deformation is estimated to be in the order of 100 km. This relatively large scale suggests that the dynamics of the water column, including currents and mixing processes, are relatively weakly influenced by the Coriolis force over smaller spatial scales.

Previous studies demonstrated the significant influence of tidal dynamics on BCS river plume behavior, revealing that tides inhibit the offshore expansion of freshwater by intensifying mixing processes [4,18]. The rising and falling tides generate currents that disrupt the stratified layers of the river plume, enhancing the dispersion of nutrients and sediments while creating a denser mixture that confines the plume to a narrower coastal band. Unfortunately, their effect on turbidity dispersion is not clearly evident in the current study. This lack of clarity is primarily due to the temporal resolution of the data used. The monthly data resolution cannot capture the detailed transport phenomena induced by tides. For a comprehensive understanding of the transport induced by tides, data with a higher temporal resolution would be required. Previous studies have shown that turbidity dispersion and fluctuations caused by tides are better observed with high-resolution data [23,29,36]. This level of detail is necessary to accurately identify and analyze the contributions of tidal forces to turbidity dispersion within the BCS.

This study reveals spatial and temporal difference in the distribution patterns of TSM and freshwater river plumes. While TSM appears to disperse southward from December to February, an increase in TSM concentration can be observed in the northern region during the December–January period (Figure 3). In contrast, the freshwater river plume in the northern part of the BCS exhibits an increased presence only from March to September [18]. These contrasting distribution patterns between TSM and freshwater river plumes deserve attention. This distinctions can be attributed to the different properties of TSM and freshwater. The freshwater river plume has a lower density and can be more easily distributed by wind-driven currents, whereas the TSM has a higher density and cannot be directly controlled by wind-driven currents [37]. Instead, TSM distribution is primarily governed by river flow dynamics, which are dominant in estuarine regions.

This distinct pattern between TSM and freshwater river plume may also be linked to the relationship between TSM load from the Berau River and increased rainfall during the April–May and December–January periods. This observation aligns with previous studies that established the equatorial rainfall pattern in the northern Kalimantan region, characterized by two distinct rainy and dry seasons [20]. Furthermore, the significant correlation between the TSM concentrations in the northern and southern areas and precipitation underscores the direct connection between heightened rainfall and an increased TSM load, contributing to broader distribution in these regions.

5.2. Regional Climate Variability

The significant correlation between the TSM levels at the river mouth and both precipitation and ENSO suggests that turbidity within the BCS is influenced by regional phenomena. This relationship between TSM and La Niña events was particularly evident during the La Niña events in 2008, 2012, and 2022, when the TSM concentrations significantly increased, accompanied by a notable rise in precipitation (Figure 8). Conversely, during the extreme El Niño events in 2010, 2016, and 2020, there was a significant decrease in TSM and precipitation (Figure 8). Additionally, the negative correlation between the turbidity values and the Indian DMI indicates that, during negative IOD events, the turbidity levels tend to increase. This phenomenon is also linked to heightened rainfall in the BCS during negative IOD occurrences.

These ENSO (El Niño–Southern Oscillation) and IOD (Indian Ocean Dipole) phenomena are expected to undergo changes due to climate change [13,14,38]. Climate change is projected to intensify both La Niña and El Niño events, and, under its influence, extreme El Niño, La Niña, and IOD events will occur more frequently [13,39,40]. This study highlights the fact that climate phenomena at both regional and global scales can impact the turbidity patterns in the BCS, thereby posing potential threats to ecologically vital habitats.

The spectral analysis of the TSM both at the river mouth (Figure 6) and in the southern area (Figure 6) reveals a decadal oscillation pattern that can be linked to the Pacific Decadal Oscillation (PDO), which typically spans a 10–15 year cycle. During the positive phase of the PDO, the waters in the BCS and across Indonesia tend to experience a cooler sea surface temperature (SST) accompanied by a reduction in rainfall [21]. Conversely, during the negative phase of PDO, there is an increase in precipitation and a higher SST [21]. It is possible for these rainfall anomalies to subsequently influence the variations in TSM on a decadal scale.

5.3. Coastal Ecosystem Stressors

Coastal ecosystems in the BCS region face threats from several stressors, including turbidity, freshwater river plumes, and rising SST levels. An extreme and prolonged increase in the SST induces marine heatwaves, which are a primary driver of coral bleaching events, while moderate SST increases can influence the health and growth of coral reefs [41,42]. Similarly, seagrass ecosystems are also impacted by SST increases, leading to leaf bleaching and affecting seagrass health and growth [43]. Previous studies have indicated that the BCS and the surrounding area have experienced marine heatwaves characterized by prolonged increases in the SST. The duration and intensity of these marine heatwaves in the BCS area are closely linked to the climate variability associated with the ENSO and IOD [44].

Additionally, increasing turbidity reduces the penetration of light into the sea, which is crucial for the growth of corals and seagrasses. A high load of TSM can smother corals and seagrass leaves, further impacting their health and growth [2]. Coral reef habitats are highly sensitive to salinity changes induced by freshwater river plumes. About half of the coastal ecosystems located on coral islands within the BCS area face a significant risk of low-salinity water exposure because of these river plumes [3,16].

The relationship between the TSM and the SST is shown in Figure 8, indicating a positive relationship between annual variations in TSM and SST. This suggests that an increase in turbidity is accompanied by an elevated SST, as observed during La Niña events. During these events, the SST tends to rise above its normal levels, and, in extreme cases, this can trigger marine heatwaves, leading to widespread coral bleaching and the destruction of benthic flora habitats [41].

Furthermore, during La Niña events, precipitation in the BCS region increases (Figure 8), potentially leading to higher river discharge. The escalation in river discharge can influence the broader spread of low-salinity water from the river plume. The vulnerability of coastal ecosystems in the BCS can be further compounded by the threat of a compound stressor when the other stressors are simultaneously intensified.

6. Conclusions

In this study, we investigate the spatial and temporal patterns of turbidity as measured by total suspended matter (TSM), using remote sensing data from the Berau Coastal Shelf spanning a period of over 20 years. The variability in turbidity at the river mouth is largely influenced by river discharge, while the spatial and temporal distribution of turbidity in the northern and southern BCS is affected by met-ocean parameters, with seasonal winds and currents playing a significant role. The coupling of the Indian Ocean Dipole (IOD) and the El Niño–Southern Oscillation (ENSO) also has a significant impact on the interannual variations in turbidity. Notably, in terms of interannual variability, the increase in turbidity is often accompanied by rising temperatures, potentially creating a compound stressor for marine and coastal ecosystems in the BCS. Moreover, the implications of climate change, which modulate the frequency of IOD and ENSO events, can further worsen the decline of coastal habitats in the future. This study highlights the importance of understanding oceanographic processes at local, regional, and global scales in the management of BCS coastal ecosystems. However, it is worth noting that this study is limited to examining the modulating effects of met-ocean parameters on turbidity in the BCS. We recommend that future studies explore the influence of hydrological and terrestrial factors, particularly land-use changes, on sediment loads entering the BCS.