Three-Dimensional Hydrodynamics Simulation of Manila Bay

Symposium on Infrastructure Development and the Environment 2006 7-8 December 2006, SEAMEO-INNOTECH University of the Philippines, Diliman, Quezon City, PHILIPPINES

THREE-DIMENSIONAL HYDRODYNAMICS SIMULATION OF MANILA BAY

1Tanuspong POKAVANICH, 2Kazuo NADAOKA

1 Graduate Student, Dept of Mechanical and Environmental Informatics, Tokyo Institute of Technology 2 Professor, Dept of Mechanical and Environmental Informatics, Tokyo Institute of Technology

Abstract: To reconstruct a complex circulation of Manila Bay, the study utilized a three- dimensional turbulent flow model. The model took into account effects from various external governing factors including tide, river discharge, solar radiation, and wind. The mathematical model was calibrated with field survey data obtained in 2001. The simulated bay current pattern showed a clear combination between barotropic flow driven by ocean tide and baroclinic flow from stratified system inside the bay. The temporal analysis showed strong linkage between bay’s hydrodynamics and semi-diurnal tidal component. The study conducted a lot of sensitivity tests to quantify the magnitude and how each governing factors contribute to the overall bay circulation. Results suggested that the strong stratification inside the bay was mainly created by freshwater loads from rivers. The wind stresses appeared to response for the near-surface freshwater distribution, discharged from the surrounded rivers.

Key Words: Manila Bay, Hydrodynamics simulation, Three-dimensional model, Bay circulation, Combined effect flow

1. INTRODUCTION

Manila Bay is a semi-enclosed bay located on the southwestern part of Luzon Island between latitude 14o15’- 14o85’ and longitude 120o35’- 121o00’ (Figure1). The bay width varies from 22km at its mouth to maximum of about 60km. Its length is about 53km with the average depth of 20m. Manila Bay is a very important water body of Philippines and extensively used for various purposes. The bay receives discharged water from numerous sources includes 26 river’s catchments (account for about 17,000 km2.), highly polluted domestic and industrial refused water drained from Metro Manila and Laguna De Bay. Although M. Prudente et al. (1997) inferred that fish of Manila Bay are still not adversely affected by heavy metal contamination (i.e. Hg, Pb, Cd), there are plenty of evidences on it already symptom from too much nutrition load which course euthophication problem. In the 90s, there used to be a regular occurrence of the planktonic bloom during the southwest monsoon (IMSWES workshop, 2000). Jacinto et al. (1998) noted that rough estimates of the discharge of inorganic nutrients into the bay is approximately 40x106 mol/yr of inorganic P and 600x106 mol/yr of inorganic N. With increasing population and still

ineffective waste management, values of waste loading rates are higher today. The coupled environmental pressure from increasing population and rapid developments of Metro Manila and the bay’s surrounding provinces urgently ask for a comprehensive study to better understand it’s hydrodynamic and water quality characteristics. Manila Bay owns a very narrow mouth so residence time of water inside the Bay is relatively longer. De Las Alas and Sodusta (1985) simulated the response of Manila Bay to the quasi-steady forcing by prevailing winds. They concluded that the individual average wind blow at specific period of the year controlled bay’s circulated gyres differently. There are Northeasterly winds, with speeds averaging about 5m/s from October to January (Figure2a); Southeasterly winds, with speeds ranging from 3 to 6m/s from February to May (Figure2b); and Southwesterly winds, with speeds of 5 to 7 m/s from June to September (Figure2c). Villanoy and Martin (1997) modeled the bay’s current from the combined effects of ocean tide and uniformed wind. They suggested a relative importance between tide and wind induced current to the overall bay circulation. Their tidal-driven 2- dimensional hydrodynamic indicated that the residual tidal velocities are strongest at the mouth where it enters the bay north of Corregidor and exits to the South. Moreover, their results of wind-driven circulation from Southwesterly wind (Figure2d), showed the existence of two asymmetrical counter-clockwise gyres similar to the works of De Las Alas and Sodusta (1985), except that the location of convergence a bit deviates to the West.

The bay exhibits a strongest stratification during rainy season from the higher air temperature and outstanding discharge amount. In contrast, the bay shows a relatively uniform water column throughout the year (IMSWES workshop, 2000). The evidences on a temporal and spatial variation of its hydrodynamic governing parameters (e.g. salinity, temperature and wind) demonstrate a necessity of 3-dimensional modeling (IMSWES workshop, 2000; Tamura et al., 2003). The realistic simulation should, therefore, be able to reconstruct the bay’s circulation base on combined driven forces including a density driven. The present research aimed to study a complex circulation of Manila Bay by combining a tide-induced current, a density-driven current and a wind-driven current. The study conducted various numerical experiments to investigate the bay’s 3-dimensional hydrodynamic characteristics to quantify the roles of each current-induced factor.

2. SIMULATION MODEL

2.1 Governing Equations

A well established three-dimensional turbulence flow model (Delft3D-Flow) from Delft Hydraulic-Netherlands, was used in this study. The governing equations written in orthogonal curvilinear co-ordinate (ξ,η) are as follows:

Continuity equation ∂ζ 1 ∂((d +ζ )UG ) 1 ∂((d + ζ )VG ) + ηη + ξξ = Q (1) ∂t Gξξ Gηη ∂ξ Gξξ Gηη ∂η

Equation of motions (in ξ -direction)

2 ∂u u ∂u v ∂u ω ∂u uv ∂ Gξξ v ∂ Gηη + + + + − − fv ∂t Gξξ ∂ξ Gηη ∂η d + ζ ∂σ Gξξ Gηη ∂η Gξξ Gηη ∂ξ

1 1 ∂ ∂u   (2) = − Pξ + Fξ + 2 ν v  ρ0 Gξξ (d + ζ ) ∂σ  ∂σ 

Figure1. Manila Bay location, field survey points, Sangley meteorological station, simulated grid, locations of major ( ) and minor ( ) discharge point.

Figure2. Wind driven circulation model of Manila Bay after De Las Alas and Sodusta

(1985;a-c), and Villanoy and Martin (1997;d). Large arrows indicate wind direction. (Picture from Fernando P. Siringan et al., 1998)  2 2   1 ∂ u 1 ∂ u  Fξ =ν H + (3)  G G ∂ξ 2 G G ∂η 2   ξξ ξξ ηη ηη  1 g ∂ζ d + ζ 0  ∂ρ ∂σ ∂ρ  P = + g  + dσ ′ (4) ξ ∫  ρ0 Gξξ Gξξ ∂ξ ρ0 Gξξ σ  ∂ξ ∂ξ ∂σ  f = 2Ωsinφ (5)

Transport of matters (Sanility&Heat)

  ∂(d + ζ )c 1 ∂[ Gηη (d + ζ )uc] ∂[ Gξξ (d + ζ )vc] ∂ωc +  +  + + λd (d + ζ )c − S ∂t G G ∂ξ ∂η ∂σ ξξ ηη        d + ζ  ∂ Gηη ∂c ∂ Gξξ ∂c  1 ∂  ∂c      =  DH + DH  + DV  (6) G G ∂ξ  G ∂ξ  ∂η  G ∂η  d + ζ ∂σ  ∂σ  ξξ ηη   ξξ   ηη 

Equation of state (Eckart,1985)

1000× (5890 + 38t − 0.375t 2 + 3s) ρ = , (7) (1779.5 +11.25t − 0.0745t 2 − (3.80 + 0.01t)s) + 0.6980(5890 + 38t − 0.375t 2 + 3s) where u and v are the horizontal velocity, ω the vertical velocity, g the gravitational acceleration, Q the contribution per unit area from discharge and withdrawal of water, precipitation and evaporation, Pξ the pressure gradients, Fξ the unbalance of horizontal

Raynold’s stresses, fv is the coriolis terms, ν H and ν V are the horizontal and vertical eddy viscosity, DH and DV are the horizontal and vertical eddy diffusivity, λd the first order decay process, S the source and sink terms per unit area due to the discharge, withdrawal of water and the exchange of heat through the free surface, ρ the water density, s the salinity, t temperature. The study assumed ν H and DH to be a constant. The ν V and DV are calculated from the second order k − ε turbulent closure model (Uittenbogaard et al., 1992). The boundary conditions (in ξ -direction) are written as follows. At the surface:

ν H ∂u 1 r = τ s cos(θ ), (8) H ∂σ σ =0 ρo r 2 τ s = ρaCdU10 (9)

At the bottom:

ν H ∂u 1 = τ b , (10) H ∂σ σ =−1 ρo r r r gρoub ub τ b = 2 , (11) C3D

g ∆zb C3D = ln(1+15 ) (12) κ ks

where τ s and τ b are the shear stress on the water surface and sea bottom, Cd the wind drag coefficient, H the total water depth, ρ a and ρ0 the air and water density, U10 the average wind speed at 10 meter above free surface, θ the angle between wind stress vector and local direction of the gird line, C3D the 3D Chezy coefficient, ks the Nikuradse roughness length. At the water surface, the heat exchange is modeled by taking into account the separate effects of solar (short wave) and atmospheric (long wave) radiation, and heat loss due to back radiation, evaporation and convection (Murakami et al., 1985). The bed stress formulation is related to the current just above the bed. There is no transported flux across the bottom. At the open and close boundaries, the salinity of seawater is assumed to be uniform. The water temperature was set to be stepwise that consisted by two different temperature layers, the warmer above (See table1). There is no flow through all close boundaries.

2.2 Model Setup and Calibration

The simulation was carried out using a sigma coordinate system with horizontal orthogonal curvilinear grid. Table1 shows the computation conditions of the hydrodynamic model. Figure1 shows the horizontal grid system, the locations of river discharge surrounding the bay, and the field data stations. The meteorological concerned data (e.g. solar radiation, air temperature, relative humidity, wind) obtained from Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) (Figure1 and Figure7). The simulation continue for two weeks to cover a cycles of neap and spring tide, from 3rd -17th October, 2001. The model was calibrated against field survey data near the mouth of Manila Bay of Tamura et al. (2003). Due to the absent of actual fresh water discharge record, the study assumed the steady discharge condition in all rivers. The river discharges were treated to be one of the calibrated parameter and was derived from calibration process to obtain the best matching between field and simulated results. The corresponding river discharge characteristics are shown in Table1. Figure3 shows the comparison of field data and modeling after calibration.

3. RESULTS AND DISCUSSIONS

3.1 Combined Effects Circulation

The model was run with the external forcing after spin-up period. Simulated results display a clear typical estuarine flow, combination of barothophic and baroclinic flow forced by offshore ocean tide and in-bay stratification, respectively. There is a clear different of current vector field between the near-surface layer and the lower layer during the interested period (Figure 4). The freshwater from the surrounding river flows out from the bay in the upper layers while the higher density water (cooler and more salinity contain) enters in the lower layer (Figure 6). The upper layer outflow is restricted to flow out from the bay during flood and high tide, however being accelerated during ebb and low tide. The water level distribution indicates the slightly increase of tidal wave magnitude toward the bay head end with the maximum tidal range near Pampanga bay. This fact affects the tidal

wave shoaling effect on the gentle smooth slope. Figure 5 shows the overall upper and lower layer residual current, distribution of salinity and water temperature. It seems that the submerged current supplies the cool water concentrate near the left bank and correspondingly creates a big clockwise gyre inside the bay. The circulation also reflects to the overall temperature distribution in which the water is warmer along the north to southwest bank where the water depth also relatively shallower. The near surface salinity distribution skew clock-wisely follow the upper layer mean flow. However, the low salinity water appears to concentrate more on the west border close to the source of major freshwater discharging sites. With the combined effect of fresh water discharge and periodic solar radiation, it is seen that, water column stratification pronounces more toward the bay head end. The fluctuation of water temperature also shows the higher in magnitude there (Figure 7).

Table1: Computational conditions of the hydrodynamic model.

Contents Selected Value Model Area Approx. 5500 Sq.km.

Horizontal meshes 115 * 62 Grid (see Figure1)

Vertical Layers 15 layers (non-uniform)

Sea level Ocean tide model (Matsumoto et al., 2000)

Meteorological condition Sangley meteorological station (see Figure1)

River discharge conditions 5 major rivers and 19 minor rivers with assume constant salinity (0 ppt) and water temperature (29.5 Celsius). Discharge magnitude is calibrated basing on field investigation (C.L.Villanoy et al., 2005) [Pampanga 120, Bulacn-Meycauyan 180, Balanga 60, Pasig 90, Minor rivers 10] unit: m3/s

Horizontal eddy viscosity and 10 m2/s and 5 m2/s diffusivity

Vertical eddy viscosity and k − ε model diffusivity

Background vertical eddy 0.0001 m2/s and 0.00005 m2/s viscosity and diffusivity

Bed roughness Manning 0.03

Sea surface roughness Large and Pond (1981)

Calculation period 15 days

Figure3. Comparison between field survey and simulation of water level at station AW, cross-sectional horizontal velocities, salinity and water temperature during Ebb and Flood.

Figure4. Simulated halocline, thermocline and the corresponding two-layers circulation.

20 cm/s 20 cm/s 7

Upper layer Lower layer

Temperature Salinity (ppt)

Figure5. The upper and lower 25-hours average mean flow and resultant surface water temperature and salinity distribution.

3.2 Semi-diurnal Tide Dependency

Tidal currents play a dominated role controlling the back and forth movement of water parcel in coastal bays in which they show strong relation with the moving up and down of sea level. Manila bay hydrodynamic is also greatly influenced by mixed-tide offshore fluctuation composing of M2, S2 semi-diurnal and O1, K1 diurnal tidal constituent. Their magnitudes are 0.16, 0.06, 0.21, 0.25 meter respectively. Generally, sea level oscillation pattern produces similar tidal current pattern with magnitude and phase difference. In this study, the simulation results suggested differently. Figure 7 shows relationship of the bay

water level with magnitude principle flow velocity at three points (positions show in Figure 6) in the bay. The analysis shows that the strongest current does not occur during the highest sea level oscillation (spring tide) but neap tide. Moreover, the semi-diurnal signal of water movement appears during the diurnal tidal period. This fact has once been reported by C.L.Villanoy and O.C.Cabrera (2005) from their field work at the mouth of Pampanga river. The simulation results suggest the important of semi-diurnal tidal component to the hydrodynamic of Manila bay. The discrepancy of tides and tidal currents could be attributed to the geophysical feature with small opening to the sea of the bay. The narrow mouth may have screened the diurnal component of the tide causing the bay hydrodynamic to exhibit more semidiurnal properties.

0.6

0.4

0.2 0.6 0 0.4 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 -0.2 0.2 -0.4 0.6 0 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 -0.6 0.4 -0.2 0.2 -0.4 0 Upper layer -0.6 t -0.6 -0.4 -0.2 0 0.2 0.4 0.6 Lower layer -0.2

-0.4 Unit: meter/sec

-0.6 Figure6. Scatter plot of modeled North and East velocity components showing non-zero residual current of upper and lower layer.

3.3 Separated Contribution from Each Hydrodynamic Driven Factors

In general coastal sea, the tidal current seems to govern the short-term hydrodynamic fluctuations which are classified into two types; barotropic and baroclinic. A barotropic circulation is seen in the case where there is no stratification, the same tidal current flows in the upper and lower layers. A baroclinic response is seen in the case where the stratification is developed, the direction of the tidal current in the lower layer is opposite to that of upper layer. Apart from tidal current, residual flow plays a more important role for long-term material transport in the coastal sea. The main components of residual flow in the coastal sea are tide-induced residual current, wind-driven current and density-driven current (T.Yanagi, 1999). This study aim to quantify the influent of each major governing factors (i.e. tides, low salinity of freshwater, water temperature changes and surface wind stresses) to the overall bay circulation by the numerical experiment. Based on 4 different running scenarios, in which each governing factors are separately applied, the study derived the resultant velocity fields of the instantaneous flow (snapshot at ebbing) and mean flow (25hour averaged). Figure8 and Figure9 illustrate the resultant velocity field in the upper and lower layers, showing the instantaneous and mean flow respectively.

WATER LEVEL 0.6 0.4 Actual Water level Semi-diurnal Comp. 0.2 0 meter -0.2 -0.4 Date -0.6 9 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 PRINCIPLE FLOW VELOCITY: MIDBAY 0.6 Actual flow - Submerged flow Actual flow - Surface flow 0.4

Figure7. Temporal changes in the upper and lower layer hydrodynamic characteristics of Manila Bay. Figures show a mutual interaction between tide and density induced current that appears to be a major contributed factor controlling a two layers back and forth flow pattern of the bay. However the similar control mechanism can not be seen in the mean flow analysis.

The tidal residual current seems to be minimal compare to other factor. Salinity difference creates an opposite velocity field between the upper and lower layer. The similar pattern in both instantaneous and mean salinity-induced flow reveal the important of it to the short and long-term transport of matter inside the bay. Moreover, comparing Figure9 and Figure5, the sea saltiness may responsible for the overall clockwise circulation near the bay head end. Minimal temperature-induced current can be noticed at any timescale and seem to limit to the area close to the bay mouth. With the 5 m/s Northeasterly wind (the prevailing wind from December to January, F.P.Siringan (1998)), it appears that the corresponded current to the wind direction is limited to the near surface layer. Wind driven current also promotes a bay-ward flow in the lower layer. Note that, the present model yields the lower layer wind-induced current with a good agreement to the wind driven circulation model of De Alas Alas (1985) (Figure9 and Figure2). The additional sensitivity tests of steady-uniform wind blow from different directions are performed to confirm the influent of wind of the overall fresh water distribution inside the bay. Figure10 compare the effect wind blow at 3 m/s (the average magnitude from Sangley station) from North- West (NW), North-East (NE), South-East (SE) and South-West (SW) to the overall bay salinity distribution. However reminding that, the actual wind field inside the bay showed a strong fluctuation in both time and space (Tamura el al, 2003).

4. CONCLUSION

The three dimensional hydrodynamic simulation of Manila Bay which has taken into account the combine effects of barothophic and baroclinic circulation is established. The simulated outcome suggests that Manila Bay hydrodynamic nature is strongly controlled by the integrated effect from various external factors i.e. offshore tidal fluctuation, river discharges, water temperature change from solar radiation, and wind driven current. Mean flow analysis suggests that the bay might probably be supplied with nutrient as well as sediment from the South China sea as there is a clear submerged residual flow toward the bay. To achieve the more realistic simulation of Manila bay, the authors recommend to gather good set of comprehensive river discharge and wind data. The desired data set should contain both temporal and spatial information.

ACKNOWLEDGMENTS

The author wishes to express sincere thanks to Dr. C.L.Villanoy and O.C.Cabrera and members of Marine Science Institute, University of the Philippines for their useful references and guided data for the Manila bay’s river discharges. Thanks to Dr. F.P.Siringan, National Institute of Geological Sciences, University of the Philippines for his valuable discussions. Acknowledge is also due to the TokyoTech International Research Course for Environment 2004 to provide the author a one-year research opportunity making possible this study.

UPPER LAYER

Figure8. Resultant instantaneous velocity fields driven by separate contribution from different factor.

UPPER LAYER

10 cm/sec LOWER LAYER

TIDES SALINITY TEMPERATURE WINDS Figure9. Resultant residual velocity fields (mean current) driven by separate contribution from different factor.

Figure10. Near surface salinity distribution corresponding to the different steady and 3 m/s uniform wind condition. The darker color indicates the higher salinity water.

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