ORIGINAL ARTICLE

Modelling of hydrodynamic circulation in Benoa Bay, Bali

Nining Sari Ningsih • Muchamad Al Azhar

Received: 29 February 2012 / Accepted: 14 August 2012 / Published online: 1 September 2012

� JASNAOE 2012

Abstract A simulation of water level, velocity, salinity,

and temperature in the Bay of Benoa has been carried out

using a three-dimensional hydrodynamic Estuarine and

Coastal Ocean Model incorporating a main characteristic

of southward transport of the Indonesian throughflow at the

offshore area of the bay. In other respects, two types of

boundary conditions have been tested: (1) specifying ele-

vation at all boundaries; and (2) implementing a combi-

nation of elevation and velocity at the boundaries.

Performance of the model results has been quantified in

terms of mean absolute errors, root-mean square errors, and

correlation coefficients based on the availability of water

level and current data. The general agreement between

simulated and observed values of water elevation and

currents is encouraging. Errors in computed water levels

are less than 5 % of the local tidal range, and correlations

between the data and model exceed 0.95. Meanwhile,

errors and correlations for simulated currents are less than

22 % and are about 0.75, respectively.

Keywords A three-dimensional hydrodynamic model �ECOM � Benoa Bay � Correlation coefficient � Root-mean

square error

1 Introduction

The Benoa Bay (BB) is a shallow and tidal estuary situated

on Bali’s south-eastern coast, Indonesia (Fig. 1). The bay is

about 5 km wide, 7 km long, and \21 m deep. Like other

estuaries, a land–sea boundary of the BB is dynamically

active in which the land side can be wet and the sea side

can be dry. The BB is protected by a narrow sandy Benoa

Peninsula and Serangan Island. The southern tip of the

island is separated from the northern tip of the peninsula by

a navigable (±1 km) stretch of water, which is a main

entrance to Benoa Harbour located in the bay. Meanwhile,

the northern tip of the island is separated from the mainland

at high and mid tides by a very shallow channel, which is

±400 m at its narrowest point. Off the main entrance, the

depths increase gradually eastward about 90 m before

Badung Strait begins. Directly connected with the Badung

Strait is Lombok Strait, which is one of the major passages

delivering the Indonesian throughflow (ITF) into the Indian

Ocean (Susanto et al. [1]; Gordon et al. [2]).

Shore line of the BB is naturally protected by a green

belt of mangrove forest. However, condition of the man-

grove forest has declined through the years because of

alteration of its function, such as development of extensive

aquaculture (shrimp ponds) and land reclamation. Similar

to other estuarine environments, the bay suffers from a

number of serious environmental problems, such as

eutrophication due to nutrient loading, biological pollution

from untreated sewage effluent discharge, pollution caused

by port activities and vessels entering the Benoa Harbour

(Fig. 1), which is the port for tourist day-trip boats, a pri-

vate marina, fishing vessels off-loading their catch of tuna

and squid, and anchored inter-island ferries.

To predict and mitigate these kinds of estuarine prob-

lems, a detailed knowledge of hydrodynamics, which

N. S. Ningsih (&) � M. A. Azhar

Research Group of Oceanography, Faculty of Earth Sciences

and Technology, Bandung Institute of Technology (ITB),

Bandung, Indonesia

e-mail: nining@fitb.itb.ac.id

N. S. Ningsih

Lab Tek XI Building, 1st Floor, J1. Ganesha 10,

Bandung 40132, Indonesia

M. A. Azhar

Department of Geography and Geology,

University of Copenhagen, Copenhagen, Denmark

123

J Mar Sci Technol (2013) 18:203–212

DOI 10.1007/s00773-012-0195-9

governs the motion of estuarine water and materials, is

required in the BB. It is important to obtain an accurate

calculation of water level and velocity both for scientific

and practical reasons, especially related to water quality

management. However, this important subject has so far

not been extensively studied in the bay, both based on

observations and numerical models. From the view point of

numerical simulation, to our knowledge, numerical studies

having been carried out in the BB are on residual current of

M2 tide (Hendrawan et al. [3]) and phosphate transport

(Hendrawan and Ardana [4]). These studies used a two-

dimensional hydrodynamic model of the Princeton Ocean

Model (POM) from Blumberg and Mellor [5] and specified

tidal water level for the model forcing. Although both

studies have demonstrated tide-driven circulation patterns

in the bay, performance of the simulated velocity, which is

a useful tool for water quality modeling of the modeled

region, has not been quantified due to the lack of obser-

vational data. In addition, to the best of our knowledge,

there has been no numerical study which (1) takes into

account a main characteristic of southward transport of the

ITF that is expected influencing the water circulation in the

Badung Strait, as the offshore region of the BB, as well as

in the Lombok Strait, and (2) considers a different type of

open boundary condition for better simulation results in the

BB. These are the main motivations of the present study.

Furthermore, because observational data of water level and

current velocity were available for model validation, we

also address quantifying performance of the model results

in terms of mean absolute errors, root-mean square (RMS)

errors, and correlation coefficients as conducted by

Blumberg et al. [6]. These data were provided by the

Hydro-Oceanographic division of the Indonesian Navy

(DISHIDROS TNI-AL).

∗

SI

BP

BH

N↑

NB

EB

SB

SI

BP

BH

(b)

(c)

M

B

Lombok Strait

Bali

Lombok

(a)

Fig. 1 a Location of the Benoa Bay (B) and Stations of Meneng

(M) and Benoa (B); b satellite map of the Benoa Bay derived from

Google Maps; c model domain and orthogonal curvilinear coordinate

system. Alphabet letters in b and c denote Benoa Harbour (BH),

Benoa Peninsula (BP), Serangan Island (SI), Northern Boundary

(NB), Eastern Boundary (EB), and Southern Boundary (SB). Location

of the validation point for water elevation and current velocity is

denoted by asterisk. Dotted (solid) lines in c denote shoreline (openboundary lines)

204 J Mar Sci Technol (2013) 18:203–212

123

In the current study, a three-dimensional (3D) simula-

tion of estuarine circulation in the BB have been carried

out using the Estuarine, Coastal and Ocean Model (ECOM)

developed by Blumberg and Mellor [5, 7] within the

framework of a single grid system. The outline of this

paper is as follows. After this introduction, a description of

the applied model is described in Sect. 2. Next, initial

conditions and model forcing functions are given in Sects.

3 and 4, respectively. Section 5 provides the simulation

results and their performance. In Sect. 6, we present our

conclusions.

2 Model description

The ECOM implemented in this study has been widely and

successfully applied to simulate hydrodynamics of oceanic,

coastal, and estuarine waters (e.g., Blumberg and Goodrich

[8]; Blumberg and Galperin [9]; Galperin and Mellor [10];

Ezer and Mellor [11]; Blumberg et al. [12]; Chen and

Beardsley [13]; Allen et al. [14]; Blumberg et al. [6];

Vinogradova et al. [15], and Zuo et al. [16]). The numerical

model solves the conservation equations for mass,

momentum, heat, and salt. The governing equations are

formulated in local orthogonal curvilinear coordinates in

the horizontal and the r-coordinate system in the vertical.

The horizontal curvilinear system allows one to resolve

a complex geometry of the BB coastline, whereas the

r-coordinate system permits one to achieve a better sim-

ulation of both the surface and bottom mixed layers. The

model incorporates a mode splitting technique, solving

vertically integrated equations for the fast processes

(external mode) and 3D equations for the slower processes

(internal mode). Further details of this model can be found

in HydroQual [17].

Figure 1a–c shows the model domain of about

10 km 9 9 km (115�1203000–115�1705400E and 8�4402200–8�4901400S) and the horizontal, orthogonal curvilinear grid

system employed in this study. The grid consists of

57 9 50 segments in the horizontal plane, and 6 r-levels in

the vertical plane. The model domain encompasses the

south-western part of the Badung Strait as the offshore area

of the Benoa Peninsula and Serangan Island, the main

entrance channel to the Benoa Harbour, the shallow

channel separating the mainland and the Serangan Island,

and the Benoa Harbour waters, as shown in Fig. 1c. The

horizontal grid is non-uniform in space, varying from 30 m

in the main entrance channel to about 900 m in the offshore

area. The finest grid corresponds to the region where

observational data for validation are available, namely the

ship entrance channel (marked by an asterisk (*) in

Fig. 1c). Depth data were created from a bathymetric chart

provided by the DISHIDROS TNI-AL. Minimum water

depth is set to 3 m (the model does not allow for grid cells

to fall dry) and the maximum water depth located at the

offshore area is approximately 90 m. Time steps for the

external and internal modes used in the simulation are

0.75 s and 6 s, respectively. The applied model was run for

28 days (3–30 October 2004), which covered periods of the

observational data used for validation, namely 13–27

October 2004 for water elevation and 16–29 October 2004

for current velocity.

3 Initial conditions

Initial conditions for elevation, velocity, salinity, and

temperature are necessary to be specified to start the

computations. Velocity components were set to zero and

initial water surface was assumed horizontal through the

model domain. Due to the lack of temperature and salinity

(TS) data, as an approximation, 3D initial conditions for the

TS were set using monthly mean TS fields obtained from a

horizontal resolution of 1/4� of the 2001 World Ocean Atlas

(WOA01) (Boyer et al. [18]). Because the study area is smaller

compared with the resolution of the WOA01 data, the initial

conditions of TS are uniform in horizontal space but vary in

depth. In this simulation, we chose a 10-day spin-up period,

which is judged to be sufficient for removing the effects of

approximate initial conditions.

4 Model forcing functions

The present study is one of the early attempts to simulate

such a complex estuarine system of the BB and its sur-

rounding area and to as accurately as possible predict the

hydrodynamic behavior of the system by using limited data

sets. Following the suggestion of WL | Delft Hydraulics

[19], there are two types of simulation have been con-

ducted in this study: (1) applying elevation at all bound-

aries (hereafter referred to as EM1 simulation), and (2)

prescribing a combination of elevation and velocity at

the boundaries (hereafter known as EM2 simulation). In the

EM1 simulation, the sea level is specified along the

northern, eastern, and southern boundaries (Fig. 1c).

Meanwhile, in the EM2 simulation, the normal velocity

component is imposed along the northern boundary and the

sea surface elevation is prescribed along the eastern and

southern boundaries (Fig. 1c). It is expected that the fluxes

that are a result of this velocity component will better

represent the main characteristic of southward transport of

the ITF in the offshore area of the BB and improve the

computed results.

In general, the model is driven by tidal elevation fluc-

tuations, elevation gradient, current velocity, wind fields,

J Mar Sci Technol (2013) 18:203–212 205

123

and TS fields. Due to lack of local data, surface heat flux

and freshwater fluxes from rivers, which are quite impor-

tant in introducing lower salinity input and stratification,

and in creating coastal front around the BB waters, were

not included in this current model.

4.1 Elevation boundary condition

As mentioned before, the mainly-southward flowing of the

ITF is expected to influence the water circulation in the

Badung Strait, as the offshore region of the BB, which is

directly connected with the Lombok Strait. Based on 1-year

time series of along-channel currents in year 2004 provided

by the International Nusantara Stratification and Transport

(INSTANT) program, it can be clearly seen that the along-

channel currents in the Lombok Strait mainly flowing to

the south, especially in October 2004 as the month of our

simulation, as shown in Fig. 3 of Gordon et al. [2] and in

Fig. 7 of Kartadikaria et al. [20]. The INSTANT was a

project to directly measure the leakage of warm and fresh

waters from the Pacific Ocean into the Indian Ocean via the

Indonesian passages, known as the ITF. One of the main

passages is the Lombok Strait. Five nations were involved

in the INSTANT program: Indonesia, France, the USA,

Australia, and the Netherlands (http://www.marine.csiro.

au/*cow074/index.htm).

The ITF is induced by differences in sea surface height

(SSH) between the Pacific and Indian Oceans (Kamenko-

vich et al. [21]) in which the SSH in the Pacific Ocean is

higher than the height in the Indian Ocean. Therefore, in

order to simulate a main characteristic of southward

transport of the ITF that is expected influencing the water

circulation in the offshore region of the BB, we took into

account space-varying mean sea level (MSL) along open

boundary conditions in the model domain, as an approach

to generate elevation gradient for producing the mainly-

southward flows. This kind approach of elevation gradient

has also been applied by Blumberg et al. [6] to study

hydrodynamics of the New York Harbour region. Unfor-

tunately, measured MSL are not available for specifying

boundary conditions in this model domain. Therefore, as an

approximation, MSL boundary conditions were linearly

interpolated from MSL data of Stations of Meneng (8�70S;

114�230E, marked by M in Fig. 1a) and Benoa (8�450S;

115�130E, marked by B in Fig. 1a) provided by the Uni-

versity of Hawaii Sea Level Center (http://ilikai.soest.

hawaii.edu).

In addition to the MSL induced elevation gradient, tidal

elevation is also applied along the open boundaries. The

tidal elevation data was derived from the tide model driver

(TMD) of Padman and Erofeeva [22]. The TMD is a

Matlab package for accessing the harmonic constituents,

and for making predictions of tide height and currents. The

TMD has 1/4� 9 1/4� resolution and eight tidal constitu-

ents (M2, S2, N2, K2, K1, O1, P1, and Q1) and was used

for predicting the tidal elevations at the open boundaries.

In the implemented ECOM, the resulting water level

utilizes a formulation developed by Reid and Bodine [23],

which is expressed as,

g� go ¼ kt �un g=Dð Þ�1=2 ð1Þ

where g is the sea level at the open boundary, go is the

known (assigned) tidal in which the MSL being embedded,

�un is the model-predicted depth-averaged velocity per-

pendicular to the open boundary, g is the acceleration due

to gravity, D is the depth of the grid cell, and kt is the

LaGrange multiplier. This formulation allows longwave to

radiate through the boundaries. After carrying out model

calibration, it is found that kt ¼ 0:5 provides the best match

between the model results and the observational data.

4.2 Velocity boundary condition

The velocity boundary condition used in the second sim-

ulation is formulated as follows:

ogot¼ � o�unD

onð2Þ

where, in this case, �un is the known (given) depth-averaged

velocity perpendicular to the open boundary and n is the

coordinate normal to the boundary. In the Eq. 2, the sea

level g at the open boundary is calculated based on the

known velocity. In this study, because measured velocity is

not available for specifying boundary conditions, the �un is

approximated by the tidal velocity data of the TMD.

4.3 Temperature and salinity boundary conditions

The ECOM provides two types of the TS open boundaries:

inflow and outflow. If the flow is into the domain

(inflowing boundaries), one must specify the TS values

being advected into the domain; if the flow is outward

(outflowing boundaries), the values inside the domain need

to be advected out using the following formulation:

o

otT ; Sð Þ þ un

o

onT; Sð Þ ¼ 0 ð3Þ

where the subscript n is the coordinate normal to the

boundary, T is the temperature, and S is the salinity.

Temperature and salinity need to be prescribed from

data at inflowing boundaries. Due to lack of TS data along

inflowing boundary conditions, they were approximated by

using monthly data of the WOA01. This monthly mean

for TS fields, of course, do not represent true variations

of temperature and salinity for a particular simulation

period.

206 J Mar Sci Technol (2013) 18:203–212

123

4.4 Meteorological forcing function

For surface forcing, 6-h wind data with 2.5� 9 2.5� reso-

lution provided from the National Centers for Environ-

mental Prediction (NCEP) were imposed in the model

domain. During the simulation period of 3–30 October

2004, the average wind speed in the BB is 1.9 m/s in a

northeastward direction. Such coarse resolution of the wind

field data, of course, does not represent accurately enough

aspects of the local climate in the BB region. However, due

to the narrow BB area and the weak wind speed, it is

assumed that water circulations in the region are not sig-

nificantly affected by the wind fields. In addition, the heat

flux computation specified by the air temperature, relative

humidity, barometric pressure, wind speed, shortwave solar

radiation, and cloud cover was not taken into account in

this study.

5 Model results

Firstly, we quantified performance of the model results

based on the available data of water level and current

velocity at a validation point located in the ship entrance

channel (marked by an asterisk (*) in Fig. 1c). These data

were provided by the DISHIDROS TNI-AL office. The

velocity data were obtained by an Acoustic Doppler

Current Profiler (ADCP). Figures 2 and 3 show comparison

between the simulation results and observations of water

levels and near-surface currents (z = -2 m), respectively,

both for the EM1 and EM2 simulations. The general

agreement between the simulated results and those of the

observations is reasonably encouraging.

Table 1 shows detailed values of mean absolute errors,

correlation coefficients, and RMS errors between the sim-

ulated and observed values of water elevation and velocity.

In the case of the EM1 simulation, the correlation coeffi-

cient and mean absolute error between the simulated values

of water elevation and those of the observations are about

0.977 and 0.131 m, respectively, while for the u-velocity

component, the correlation coefficient is 0.781 and the

RMS error is 0.113 m/s, whereas for the v-velocity compo-

nent, the correlation coefficient is about 0.706 and the RMS

error is about 0.067 m/s. Following Blumberg et al. [6], we

also present errors in computed water levels and currents with

respect to the data range (Table 2). For the EM1 simulation,

error in computed water levels is about 4.5 % of the local tidal

range, whereas RMS error in currents is about 21.5 % of the

velocity range. Better simulation results will be probably

obtained if freshwater fluxes from rivers, a more appropriate

elevation gradient along the boundaries, and an adequate

estimation of the effect of the bottom friction in reproducing

the non-linear interaction of currents with the bottom topog-

raphy are specified in the model.

Ele

vati

on

(m

)E

leva

tio

n (

m)

Date (DD/MO/YR)Data

Model

(a)

(b)

Fig. 2 Comparison of water

levels during October 13–27,

2004 between the simulation

results (blue line) and

observation (red line) in the

validation point (marked by

asterisk in c), for the simulation:

a using elevation at all the

boundaries (the EM1

simulation); b specifying a

combination of elevation and

velocity at the boundaries (the

EM2 simulation) (color figure

online)

J Mar Sci Technol (2013) 18:203–212 207

123

Secondly, we compared model performance of the EM1

simulation with that of the EM2 simulation. In this current

study, it was found that the use of the combination of

elevation and velocity at the boundaries (the EM2 simu-

lation) does not significantly improve the computed results

in the BB. For the EM2 simulation, the correlation coef-

ficients between the model and data of water elevation and

current velocity increase by 0.004 and 0.017, respectively.

Meanwhile, the mean absolute error of water elevation

decreases by 0.019 m (0.6 %) and the RMS error of

velocity reduces by 0.005 m/s (1.3 %), as shown in

Tables 1 and 2. The possible source of the insignificant

improvement appears to be associated with the tidal

velocity data of the TMD used along the boundary do not

adequately represent true circulation of the BB offshore

area.

5.1 Current circulation patterns

To limit the presentation, results of the circulation pattern

are presented for near-surface currents (z = -1.5 m) and

spring tide only. The circulation pattern of near-surface cur-

rents during spring tide condition both for the EM1 and EM2

simulations are presented in Figs. 4 and 5, respectively.

The Figs. 4 and 5 clearly show the existence of currents

that flow back and forth representing flood and ebb

U-Velocity (m/s) U -Velocity (m/s)

V-V

elo

city

(m

/s)

V-V

elo

city

(m

/s)

Data ( ); Model ( )(a) (b)

U-corr. coeff. = 0.781V-corr.coeff. = 0.706Mean corr. coeff. = 0.744U-RMS errror = 0.113V-RMS errror = 0.067Mean RMS error = 0.090

U -corr. coeff. = 0.834V -corr.coeff. = 0.689Mean corr. coeff. = 0.761U -RMS errror = 0.106V -RMS errror = 0.063Mean RMS error = 0.085

Fig. 3 Comparison of near-surface currents (z = -2 m) during October 16–29, 2004 between the simulation results (blue solid square) and

observation (red diamond) in the validation point (marked by asterisk in c): a the EM1 simulation; b the EM2 simulation (color figure online)

Table 1 Mean absolute errors, correlation coefficients, and RMS errors between the simulated and observed values of water elevation and

velocity

Types of

simulation

Water elevation (f) u-Velocity component v-Velocity component Mean correlation

coefficient

of velocity

Mean RMS

errors of

velocity (m/s)Correlation

coefficient

Mean absolute

errors (m)

Correlation

coefficient

RMS

errors (m/s)

Correlation

coefficient

RMS

errors (m/s)

EM1 simulation 0.977 0.131 0.781 0.113 0.706 0.067 0.744 0.090

EM2 simulation 0.981 0.112 0.834 0.106 0.689 0.063 0.761 0.085

Table 2 Mean absolute errors and RMS errors with respect to the data range

Types of simulation Water elevation (f) u-Velocity component v-Velocity component Mean RMS

errors of

velocity (%)Data range

(m)

Mean absolute

errors (%)

Data range

(m/s)

RMS errors

(%)

Data range

(m/s)

RMS errors

(%)

EM1 simulation 2.90 4.5 0.7 16.1 0.25 26.8 21.5

EM2 simulation 2.90 3.9 0.7 15.1 0.25 25.2 20.2

208 J Mar Sci Technol (2013) 18:203–212

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conditions in the BB. In general, during the spring flood

condition, the currents flow into the BB (Figs. 4a, 5a),

whereas they flow out of the bay at spring ebb condition

(Figs. 4c, 5c). The near-surface currents are strongest at the

ship entrance channel associated with narrowing effects

with a maximum speed of about 0.7 m/s during both spring

flood and ebb tides. Meanwhile, during the slack waters

(Figs. 4b, d, 5b, d), the currents at the entrance are weak

with a speed of about 0.1–0.2 m/s. On the other hand, at the

offshore area, the model well reproduces the main char-

acteristic of southward transport of the ITF that is expected

influencing the water circulation at the region (Figs. 4, 5).

The current circulation patterns of both EM1 and EM2

simulations, in general, are similar at the whole model

domain. Except for the offshore area, the current velocity

of the EM2 simulation is stronger than that of the EM1

simulation (Figs. 4, 5). In addition, during neap tide, the

flow patterns generally remains unchanged, but the mag-

nitudes of speeds, associated with the smaller tidal range,

decreases by approximately 0.6 m/s compared with spring

tidal currents (not shown here). In this present study, the

simulated results did not well reproduce the existence of

tidal current asymmetry as shown by the observational data

in which flood current is stronger than the ebb current

(Fig. 3). The cause is probably due to the approximation

made in setting the minimum depth of 3 m. In reality,

wetting and drying phenomenon in the BB, especially

during the ebb condition, will lead to the water depth of

\3 m, which enhances bottom friction. Consequently, the

ebb current is weaker than the flood current.

5.2 Temperature and salinity

Because observational data of the TS were not available for

model validation, we only qualitatively present the model

results. In addition, for limiting the presentation, the model

results are presented for spring tide and the EM2 simula-

tion only.

Figures 6 and 7 show temperature and salinity distri-

bution along a vertical transect extending eastward from

the inner part of the bay to about 12.5 km offshore. These

figures indicate that the model well reproduces temporal

Fig. 4 Circulation pattern of near-surface currents (z = -1.5 m) during spring tide for the EM1 simulation: a flood conditions; b highest water

conditions; c ebb conditions; and d lowest water conditions

J Mar Sci Technol (2013) 18:203–212 209

123

Fig. 5 Circulation pattern of near-surface currents (z = -1.5 m) during spring tide for the EM2 simulation: a flood conditions; b highest water

conditions; c ebb conditions; and d lowest water conditions

Fig. 6 Temperature (�C) distribution along a C–D vertical transect during spring tide for the EM2 simulation: a flood conditions; b highest water

conditions; c ebb conditions; and d lowest water conditions

210 J Mar Sci Technol (2013) 18:203–212

123

variations of the TS distribution, dynamics of front, and

stratification associated with spring tidal cycles. During a

flood condition, colder and more saline water intrudes into

the BB (Figs. 6a, 7a), whereas warmer and fresher water

flows out of the bay during the ebb condition (Figs. 6c, 7c).

However, to accurately predict such phenomena in the BB,

relevant sources of freshwater inflows from rivers are

necessarily to be considered.

6 Concluding remarks

A three-dimensional hydrodynamic model of the ECOM

within the framework of a single grid system has been

applied to simulate water level, velocity, salinity, and

temperature in the BB by conducting two types of simu-

lation: the EM1 (specifying elevation at all boundaries) and

the EM2 (implementing a combination of elevation and

velocity at the boundaries). The present study attempts to

as optimally as possible use the limited data for simulating

the hydrodynamic behavior of the bay and its surrounding

area.

The overall agreement between the model and data of

water elevation and velocity is good. For both EM1 and

EM2 simulations, errors in simulated water levels and

currents are less than 5 and 22 %, respectively. Correla-

tions between the data and model exceed 0.95 for water

elevation and they are about 0.75 for currents. In the

present study, although the EM2 simulation does not sig-

nificantly improve the computed results in the BB, it has

been presented that the combination of elevation and

velocity used at the boundaries performs better than the

applying the same type of boundary condition at all

boundaries.

Though the simulated results well reproduce the current

circulation pattern associated with tidal cycles in the bay

and the main characteristic of southward transport of the

ITF in the offshore area, the existence of tidal current

asymmetry cannot be well predicted. In general, temporal

variations of the temperature and salinity distribution,

dynamics of front, and stratification associated with tidal

cycles have also been well reproduced by the model.

However, the current performance of the model in pre-

dicting salinity and temperature has not yet been judged

due to the lack of observational data.

The forcing functions implemented in the current study

are based on a large number of assumptions and approxi-

mations. Nevertheless, the simulated and observed values

of water elevation and currents are generally in agreement.

Therefore, it is hoped that the results of this present study

could be significantly valuable for water quality modelling

and designing proper management plans of water resources

in the Benoa Bay. For further study and to improve the

performance of the present study, it is suggested that

wetting and drying phenomenon be considered, along with

an adequate estimation of the effect of the bottom friction,

freshwater fluxes from rivers, and more appropriate ele-

vation gradients along the boundaries.

Acknowledgments We would like to thank the Hydro-Oceano-

graphic division of the Indonesian Navy (DISHIDROS TNI-AL) for

providing data validation for this work. We also gratefully

acknowledge the Graduate School for International Development and

Fig. 7 Salinity (psu) distribution along a C–D vertical transect during spring tide for the EM2 simulation: a flood conditions; b highest water

conditions; c ebb conditions; and d lowest water conditions

J Mar Sci Technol (2013) 18:203–212 211

123

Cooperation (IDEC) at Hiroshima University, Japan, for making the

writing of this paper accomplished.

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