Sea level rise (SLR) is a serious issue around the world that affects the hydrodynamic behaviour of river and coastal waters. This work presents the hydrodynamic pattern modelled for the region and prediction of oil spill spreading at Pulai River estuary and southwest Johor Strait before and after SLR phenomenon using TELEMAC-2D. The hydrodynamic calibration and validation were in good agreement between measured and modelled values. The mean absolute error (MAE) of water level is less than 3% and average difference in speed and direction of current is less than 10% and 30°, respectively. These values meet the impact evaluation assessment by the Department of Irrigation and Drainage (DID), which is less than 10% for water level and less than 30% and 45° for current speed and direction, respectively. Permanent service for mean sea level (PSMSL) analysis shows an increased water level of 0.35 m after SLR rise by year 2100. Currents also increase with the effect of SLR. At the Pulai River, the observed spill trajectory remains the same before and after SLR but in open seas, the affected oil spillage area at the anchorage zone is estimated to increase 28% after SLR compared to 2015. It is predicted that SLR increases water level, currents and oil spill spreading at open seas.

Sea level rise (SLR) may potentially change the morphodynamics of coastal areas, marine habitats and ecosystems, infrastructure and socio-economy of the human population, due to climate change. According to Sathiamurthy (2013), SLR increases peak stage levels and modifies hydrodynamic behaviour in open seas and tidal rivers in terms of peak flow and velocity. Therefore, the increase in SLR is predicted to change the flow of floating particles or debris on the water surface. The effect of SLR is further enhanced due to the impact of urbanization. One common occurrence of pollution on the sea surface is oil spillage, which has polluted various locations including open or rough sea (1 km from shore), open sea close to shore (<1 km from shore), estuaries, sheltered and calm waters, on shore and also ice waters. Urbanization that enhances oil drilling, port transhipment, oil refineries and recreational boats increases oil spillage in the ocean. In general, oil slick disperses and degrades naturally on the sea surface if spillage is far from the shoreline. However, a large quantity of oil spill occurrence close to a coastline threatens marine life and immediate response is required. Numerical modelling of oil spill serves as a powerful tool with low computational cost to investigate the spill behaviour. Many oil spill models have been used to study the behaviour of oil spills in two dimensions (Mike21, Delft2D and TELEMAC-2D). The numerical model in TELEMAC-2D provides short-term forecasting in relatively calm waters. The two approaches to track oil particles are the Lagrangian and Eulerian models (Zheng et al. 2002; Papadimitrakis et al. 2006). The Lagrangian model uses a large set of hydrocarbon packets advected by current and wind action whereas mass and momentum equations of the oil slick are solved in the Eulerian oil spill model (Goeury et al. 2014). The behaviour of spilled oil is affected by the physical, chemical and biological processes which include spreading, advection, evaporation, dissolution, emulsification, photo-oxidation, sedimentation and biodegradation. Oil particles are formed when an oil slick breaks up due to upper layer turbulence and the action of breaking waves (Chao et al. 2001). Oil particles stay in the water column for a long period and pollute the deep water environment. Unless oil particles are ingested into the deep ecosystem or geochemically modified, suspended oil deep residues have a residence time up to 250 years (Lee 1980).

Situated at the southern region of Peninsular Malaysia, Johor coastal waters are located between the Strait of Malacca and the South China Sea. The water level and current flow in the Malacca Straits is mainly driven by the Indian Ocean (semi-diurnal tide) whereas water level in the South China Sea is driven by the Pacific Ocean (diurnal tide) (Simoon 2010). Tidal fluctuations play a very important role in the advection of oil particles. An initial release of spill during different tidal situations and the impact of SLR will result in different movement of the oil trajectory. Thus, the aim of this study is to simulate the influence of SLR on the changes of behaviour of oil spill movement. The objectives of this study include: (i) to analyse velocity profile of the study area before and after SLR, (ii) to investigate oil spill movement in the Pulai River after SLR and (iii) to compare the influence of SLR on spreading of oil spillage at anchorage zone. The result of this study can be used as a basis for a thorough regional oil spill contingency plan for the country.

Study area

The Port of Tanjung Pelepas (PTP) is located on the waterways of the Johor Strait and situated in a sheltered bay at the Pulai River estuary at coordinates latitude: 1°21.92′ N, longitude: 103°.05′ E. Due to PTP's strategic location at the intersection of east-west international trade lanes and the high port productivity, the port continues to expand and attract a greater volume of vessel traffic. Well known for its high efficiency, PTP ranks in the top 20 of the World Port Rankings in 2016 (AAPA 2016). The model is developed to position the study area of the PTP to be located at the centre of the domain so that it is not affected by the simulated values of the boundaries. The mesh in the model was built using a pre-processor, BLUEKENUE 64 that generates unstructured mesh with gradually increased size at growth rate 1.08 as it moves further away from the study area (Figure 1). The grid lengths range from a distance of 10 m to 500 m. The bed level in the model domain ranges from 40 m below chart datum (CD) in the deeper areas to 0 m above CD along the coastline (Figure 2). The model domain covers an approximate area of 42 × 40 km and is bounded by tidal conditions at the eastern (Kukup) and western (Raffles) regions. From the sea level rise analysis, the predicted value of SLR at year 2100 was used as an increment value to the existing water level values to be implemented in the model's boundary.

Figure 1

Model mesh.

Figure 2

Model bathymetry.

Figure 2

Model bathymetry.

Close modal

Hydrodynamic model

Several major coastal modelling software tools (HEC-RAS, LISFLOOD-FP, TELEMAC-2D, Mike21 and Delft2D) are used to model hydrodynamics of flow. The HEC River Analysis System (HEC-RAS) performs one-dimensional steady flow using comprehensive 1D Saint-Venant equations for unsteady flow and water temperature modelling (Kumar et al. 2017). LISFLOOD-FP is an inundation model distinctively developed to exploit the high-resolution topographic data set and adopt it to a 2D approach (Bates & De Roo 2000). TELEMAC-2D is used to simulate free surface flows in two dimensions of a horizontal space. Periáñez (2007) utilized a model which includes a 2D average barotropic model to obtain tidal current coupled with a reduced gravity model to obtain water circulation in the Strait of Gilbraltar-Alboran Sea.

This study will focus on the model system TELEMAC-2D which has been developed by the National Hydraulic and Environmental Laboratory of the Research and Development Directorate of the French Electricity Board (EDF-DRD). Bathymetry of the domain was taken from the admiralty charts and superimposed with survey data from Johor Port Authority in June 2015. The tidal elevations required along the tidal boundaries were interpolated and used to drive the model. The tidal input data were obtained from Tide Table Malaysia 2015 at the boundary of Kukup and Raffles station.

An estimated value of 100 m3/s was used as the discharge upstream and the model was run for a period of 3 days. The water level and velocity components were derived from the results of the model. The river discharge estimation will not have any significant effect on the hydrodynamic simulation as the area of interest is focused at the centre of the configuration.

Oil spill modelling

The spreading and fate of oil particles on the water surface is determined by gravitational, viscous and surface tension and also weathering processes (Vethamony et al. 2007). In Malaysia, the oil spill models used include RADARSAT image processing, GIS and SAR images, to determine oil spill trajectory (Marghany 2000; Assilzadeh & Mansor 2001). However, there is still little knowledge on the impact of climate change on oil spill movement at the Malacca Straits, southeast of Johor.

One direct impact of climate change is sea level rise that impacts coastal environment by increasing beach erosion, inundation of land, flood and storm damage, salinity of coastal aquifers and coastal ecosystem loss. Increase in water depth results in larger significant wave heights and further elevating water depths on flat reefs (Storlazzi et al. 2011). This is expected to elevate the spreading of oil particles. Increase in salinity of coastal aquifers results in further chemical mixing with oil components and escalates deterioration of coastal water quality. Therefore, an understanding of potential future changes in sea level and ocean is important in coastal management. In the present study, a TELEMAC-2D oil spill model was used to simulate spill trajectories and weathering processes in the model simulation. The oil spill module follows the mixed Eularian and Lagrangian approach based on the volume fraction of particles.

Sea level rise analysis

Sea level was projected to rise between 0.18 and 0.59 m by the end of the 20th century (1980–1990) and continues to increase at a higher rate from 2.4 to 3.8 mm/year between 1993 and 2003 compared to 1.3–2.3 mm/year between 1961 and 2003 (Sathiamurthy 2013). This shows that coupled with urbanization, changes in rainfall pattern and global warming, sea level is expected to increase in the coming decades. The melting of ice caps, thermal expansion/contraction of the oceans, deformation of the ocean basin and land uplift/subsidence make a major contribution to SLR for the long-term period (Din et al. 2012).

Changes in sea level have been measured at a number of fixed tide gauge stations around the globe and also through satellite altimetry, to determine global and regional sea level change. The primary source of information on sea level change over the past century is tide gauge measurements. In this study, a linear regression analysis is carried out using data obtained from the Permanent Service for Mean Sea Level (PSMSL-www.psmsl.org) to determine the 100-year projection for potential of SLR in comparison to results of previous studied of SLR. This study will focus on Kukup tides to estimate the increase in projected water level in 2100. The estimated mean SLR by 2100 is 0.35 m from the PSMSL analysis based on the linear regression equation (Figure 3). Referring to the equation in Figure 3, the gradient increases approximately 4.1067 mm per year. Therefore, it can be estimated that from 2015 to 2100, there will be a projected increase of 0.35 m in water level.

Figure 3

Projected sea level rise at Kukup in 2100 (PSMSL 2019).

Figure 3

Projected sea level rise at Kukup in 2100 (PSMSL 2019).

Close modal

However, according to results from the SLR study by NAHRIM as reported by Awang & Hamid (2013), the estimated increase in water level by 2100 is 0.235 m, as shown in Figure 4. The estimated increase in tidal levels by the PSMSL analysis is higher than estimated by NAHRIM's report projection. Therefore, in this study, the higher value of 0.35 m is used to increase the current water level data to simulate the hydrodynamic of the study area and understand the effect of SLR on current conditions and oil spillage.

Figure 4

Projected sea level rise in 2100 (Awang & Hamid 2013).

Figure 4

Projected sea level rise in 2100 (Awang & Hamid 2013).

Close modal

Hydrodynamic model analysis

The calibration and validation of the model was done by comparing water level and current magnitude during spring and neap tide conditions (Figures 57). The measured water level of the specific site is used for model calibration during the spring tide (13 to 15 October 2015) and the same model is validated against water level for the neap tide (20 to 22 October 2015). The simulated and measured data showed that the model reproduced the phase as well as the amplitude closely with the predicted tides, but the simulated currents were slightly higher than the measured currents. This could be due to the lack of salinity value input that limits the model simulation. The model accuracy can also be improved with the inclusion of wave input as one of the boundary layers as this model runs on tide as input condition at the model boundary. The mean absolute error (MAE) of the water level in the model has a difference of 2.0% (spring tide) and 1.0% (neap tide) and this value meets the impact evaluation assessment by DID (Keizrul 2001) which is less than 10%. Meanwhile, the average difference in speed and direction of current during spring and neap is 6.0% (21.3°) and 7.0% (28.1°), respectively. These values agree with the DID standards where speed and direction of current should be less than 30% and 45°, respectively (Keizrul 2001). In general, water level during spring tide is higher than neap condition and velocity during ebb is stronger than during flood tide. This concludes that the estuary has a good flushing system from the Pulai River into the sea.

Figure 5

Calibration and validation curves of water level during spring (left) and neap tide (right).

Figure 5

Calibration and validation curves of water level during spring (left) and neap tide (right).

Close modal
Figure 6

Calibration and validation curves of spring (left) and neap tide (right) current magnitude.

Figure 6

Calibration and validation curves of spring (left) and neap tide (right) current magnitude.

Close modal
Figure 7

Calibration and validation curves of spring (left) and neap tide (right) current direction.

Figure 7

Calibration and validation curves of spring (left) and neap tide (right) current direction.

Close modal

Figure 8 shows the velocity profile at the area before and after SLR conditions. It can be seen that the velocity within the river channel does not alter much after SLR, but the current velocity at the Johor Strait seawards recorded a higher velocity value, approximately an increase of 0.1–0.3 m/s. This could be due to an increase in tidal range that relates to decreased bed friction. Significant increase in current velocity may trigger additional erosion at the entrance channel of Pulai River (Kumbier et al. 2018). Figure 9 shows the difference in velocity at the navigation channel during ebb tide before and after SLR. The velocity along the river shows minimal increase but the velocity along the navigation channel and Malacca Straits shows a higher increase in velocity magnitude. The ebb velocity increases with increasing SLR. The phenomenon would likely increase the ebb velocity surrounding the area of the navigation channel.

Figure 8

Velocity profile before (left) and after SLR (right) during ebb tide.

Figure 8

Velocity profile before (left) and after SLR (right) during ebb tide.

Close modal
Figure 9

Comparison of current velocity profile at year 2105 and projected year 2100 (after SLR).

Figure 9

Comparison of current velocity profile at year 2105 and projected year 2100 (after SLR).

Close modal

Oil spill at Tanjung Bin (TB) before and after SLR

This paper further discusses the flow of initial instantaneous heavy fuel spillage only at the mouth of the Pulai River (1°19′39.29″N, 103°33′23.95″E) within a period of 24 hours under calm weather conditions. The spill is released before and after SLR phenomenon to identify the difference in the stranded mass, dissolved mass and the evaporated mass. The transportation and weathering process of the oil over time was obtained based on the 2D simulation of the spill for a period of 24 hours.

The spill trajectory is printed at the 2nd, 8th, 16th and 24th hour to determine the spreading of oil particles on the water surface. Surrounding the spill location are a few sensitive environmental receptor areas including Pulau Kukup, Tanjung Piai and the mangrove wetland along Sungai Pulai that has been designated as the Ramsar site. The mangrove mudflats and biodiversity will be badly affected in any instance of oil tracers found in the area. The trajectory of initial spill is observed for two scenarios: before and after the impact of SLR at the potential spill area (Tanjung Bin and anchorage zone).

Figure 10 shows the initial spill at the river mouth during neap tide in 2015 and the oil drift spread at the specified time intervals. The spill drifts in a northerly direction at the 2nd hour and continues to spread within the estuary for about 0.85 km2. At the 8th hour, the spill starts to settle at the banks of PTP and Tanjung Bin, contaminating an area of 2.86 km2 and then continues to spread until the 24th hour, affecting an area of approximately 6.08 km2. In this case, the operation of ships at the port will be affected as the oil slick surface area dominates the entrance of the river.

Figure 10

Simulation of oil spill spreading at TB after 24 hours for the year 2015.

Figure 10

Simulation of oil spill spreading at TB after 24 hours for the year 2015.

Close modal

Figure 11 shows the initial spill at the river mouth in 2100 and its subsequent spread at the specified time intervals.

Figure 11

Simulation of oil spill spreading at TB after 24 hours for the year 2100.

Figure 11

Simulation of oil spill spreading at TB after 24 hours for the year 2100.

Close modal

Initially, the spill drifted in the northerly direction and continues to spread at the 2nd hour about 0.9 km2. At the 8th hour, the spill starts to contaminate the waterway affecting an area of 3.08 km2 and continues to spread up to an area of 6.46 km2 at the 24th hour. Although the effect may seem insignificant in Figures 8 and 9, in comparison to the affected area, it is clearly shown through a rough estimation that the affected area after SLR is slightly higher than the current condition. Therefore, any hydrocarbon spill at any location after SLR will leave a larger spreading effect in the estuary.

Oil spill at anchorage zone

At the entrance of the navigation channel lie different floating vessel units (FSU) that are positioned in the coastal waters of the Johor Strait used by the offshore oil and gas industry for the production and processing of hydrocarbons and for the storage of oil. Location of the FSU is determined within the Johor Port Limit to predict the movement of oil spillage that occurs within 24 hours. Figures 12(a)–12(d) depict the movement of heavy fuel oil spill only at a specified location at the anchorage zone whereas Figures 12(e)–12(h) show the effect of SLR after 100 years if the initial spill is at the anchorage area.

Figure 12

Oil spill spreading at anchorage zone after 24 hours in 2015 (a)–(d) and 2100 (e)–(h).

Figure 12

Oil spill spreading at anchorage zone after 24 hours in 2015 (a)–(d) and 2100 (e)–(h).

Close modal

The 2nd hour of the spill in both scenarios shows only a slight difference in heavy fuel oil dispersion. At the 8th hour, the slick is seen to expand about 10 km2 but the effect of SLR is estimated to affect 7.5 km2, which is slightly smaller than the affected area. This is possibly due to a change in the hydrodynamic pattern as the increase in water level retains the oil particles in the specific area. The movement of oil slick shows a slight difference during the 16th and 24th hour of the spill as deeper waters tend to retain the spill longer in the domain. Figure 12(e) shows the affected area if spill at year 2100 is estimated to be larger (52.5 km2) than year 2015 (approximately 36 km2). If no actions are taken after a 1-day period, the spill is expected to drift and head away from the estuary, polluting an estimated area of 123 km2 in the current situation and 158 km2 after SLR. This shows that the effect of increase of SLR will affect a larger area after 24 hours due to increasing velocity that will have higher probability to cause the oil particles to drift away from the original source to the shoreline which will result in potential coastal damage and higher clean-up cost.

Within a day's interval, the percentage of oil mass remaining decreases over time due to weathering processes acting on the oil particles. An initial spillage in the river and anchorage zone shows that the percentage of mass of moving oil in the domain decreases over 24 hours.

The percentage of remaining oil discharged at the river with SLR is about 59% to 61% after a day. At the anchorage zone, the percentage of mass balance in the domain is high (97%), which means that there are lower or possibly no particles stranded along the shoreline in the domain as the spillage is in the open sea. At the river, 38–40% of the oil was stranded along the shores whereas no amount of oil was caught stranded when initial spill is at the anchorage zone. According to Goeury et al. (2014), the oil will be stranded along the coastline if the slick thickness is greater than the water level under the oil slick or when the size of bottom roughness is greater than the water level. This shows that a major part of the reduction in mass of oil is due to oil being deposited along the shoreline. The stranded oil escalates after the 4th hour and oil particles adhere to the banks along the river. This phenomenon suffocates the mangroves along the Pulai River and will cause damage to the mangrove ecosystem if no immediate action is taken within the first 4 hours of spill.

Understanding the percentage of oil dissolved is important in the view of toxicity to understand the concentration of oil that has dissolved in the water column. At different locations, approximately 0.13% of oil dissolved within 24 hours. The percentage of dissolved mass is less than 1%, which means that it is very difficult for heavy fuel oil to dissolve within the water column. Any action taken, such as spraying dispersants, may not be the most effective manner to remove the oil completely from the water column as only a very small percentage of oil will diffuse and mix with the water. By spraying dispersants, the oil may break up into smaller particles, and diffuse into the water column. However, it does not fully dissolve as the percentage of dissolution is very minimal and may resurface once again when the particles clump together.

Heavy fuel oil evaporates at a slow rate due to higher viscosity and higher boiling point. The evaporation model used is based on the pseudo-component approach whereby the change in mass of the petroleum component is characterized and modelled based on the thermodynamic phase equilibrium equation. The percentage of evaporated oil on the water surface after 24 hours is less than 1.03% when initial spill is in the river. This shows that the evaporation rate in 1 day is very slow and most of the oil remains in the water body even though the temperature of Malaysian waters is relatively high compared to sea surface temperature in other countries. Evaporation at anchorage zone is higher (3.65%), probably due to the larger spreading at the sea surface, allowing slightly bigger surface area for hydrocarbon particles to be evaporated. This is in agreement with past studies by Goeury et al. (2012), that the exactly opposite nature of light crude oils can lose up to 75% of their volume in a few days in an occurrence of oil spillage since light oils have comparatively low viscosity, and dispersion occurs at a higher rate due to increased surface area, thus, increasing evaporation rate (Christiansen 2003; Janeiro et al. 2008).

In general, for both scenarios, the remaining mass of oil in the domain projected in the year 2015 for SLR is slightly lower than the current condition and stranded mass is higher at the coast. Evaporated mass is expected to increase as global warming may increase the surface temperature and accelerate the particles' evaporation process.

Nonetheless, the findings of this study have to be seen in light of some limitations. First, the boundary condition solely depends on water level data and is suggested to use wave or current parameters as input for boundary conditions to drive the model. The second limitation concerns the study area, which is constrained to modelling the existing condition of 2015 but foresees that in 2100, the completion of Forest City and other reclamation projects around the area should be taken into consideration for more accurate hydrodynamic simulation. Sedimentation analysis was not reviewed in the current model and there is a possibility that sedimentation or erosion may occur due to SLR condition. Therefore, data collection of the latest bed bathymetry needs to be included for future references. Finally, climate change, which means warmer temperature of sea water, needs to be taken into consideration for further development of the model.

In conclusion, the TELEMAC-2D simulated the hydrodynamic condition around the PTP coastal waters and the calibration and validation of simulated values were in conformity with the measured values. With the influence of SLR at the year 2100, it can be concluded that the water level and velocity in the area show a slight increase compared to existing condition. In the river, oil spill movement remains the same after SLR. In the open seas, the oil drifts pollute an approximate area of 158 km2 after SLR is largely spreading compared to the existing condition. As SLR will potentially increase current values in 2100, velocity increases and movement of particles will collide more frequently with each other, leading to a larger area of oil spreading. The spillage would also react differently under harsher environmental conditions, such as under storm surge or strong wind condition, which is not included in this simulation. Hence, a thorough inclusion of wind and wave factors are recommended to further improve the model so that oil spillage can be modelled accurately and prepare the related authorities for effective response.

The authors would like to acknowledge the support of Research University Grant (reference number: 17H85) under Universiti Teknologi Malaysia and Fundamental Research Grant Scheme (reference number: 4F607) under the Ministry of Higher Education. The authors wish to thank Johor Port Authority and Port of Tanjung Pelepas Malaysia for the cooperation in environmental and secondary data collection.

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