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Abd Rahman et al.:
Quasi
-
Continuous Tidal Datum for Peninsular Malaysia u
sing Tide Gauge
…
Quasi-Continuous Tidal Datum for Peninsular
Malaysia using Tide Gauge, Satellite Altimetry,
and Tide Model Driver (TMD) Data
Mohd Faizuddin Abd Rahman
Geospatial Imaging and Information Research Group (Gi2RG), Faculty of Built Environment and
Surveying, Universiti Teknologi Malaysia, Malaysia
mfaizuddin4@live.utm.my (corresponding author)
Ami Hassan Md Din
Geospatial Imaging and Information Research Group (Gi2RG), Faculty of Built Environment and
Surveying, Universiti Teknologi Malaysia, Malaysia
amihassan@utm.my
Mohd Razali Mahmud
Geospatial Imaging and Information Research Group (Gi2RG), Faculty of Built Environment and
Surveying, Universiti Teknologi Malaysia, Malaysia
razalimahmud@utm.my
Mohammad Hanif Hamden
Geospatial Imaging and Information Research Group (Gi2RG), Faculty of Built Environment and
Surveying, Universiti Teknologi Malaysia, Malaysia
mohammad.hanif@utm.my
Received: 25 December 2023 | Revised: 12 February 2024, 11 March 2024, and 6 April 2024 | Accepted: 8 April 2024
Licensed under a CC-B Y 4.0 license | Copyright (c) by the authors | DOI: https://doi.org/10.48084/etasr.6810
ABSTRACT
Conventionally, information from the tide gauge stations was used to establish the localized tidal datum.
However, limitations in coverage, due to the sparse station distribution along the coast, have caused
insufficient tidal datum information in some areas. Therefore, this study aims to develop the Peninsular
Malaysia Quasi-Continuous Tidal Datum (PMQCTD) by in tegrating tide gauges, satellite altimetry, and
Tide Model Driver (TMD) data. The research methodology includes data acquisition from 12 Departments
of Survey and Mapping Malaysia (DSMMs) tide gauge stations along the coast of Peninsular Malaysia,
satellite altimetry data of TOPEX, Jason-1, Jason-2, and GEOSAT Follow-On (GFO) from Radar
Altimeter Database System (RADS), and the global hydrodynamic model from TMD. The tide gauge,
satellite altimetry, and TMD data encompass 23 years of tidal observation data from 1993 to 2015. For the
derivation of the tidal datum, tide gauge, and satellite altimetry data were analyzed following a harmonic
analysis approach in the Unified Tidal Analysis and Prediction (UTide) software. Meanwhile, for the TMD
data, the tidal datum was determined based on the tidal prediction from the 11 extracted major tidal
constituents. For compatibility in data integration, the derived Lowest and Highest Astronomical Tide
(LAT and HAT) from tide gauge, satellite altimetry, and TMD data were referenced to the Mean Sea Level
(MSL), denoted as LAT
MSL
and HAT
MSL
, respectively. Next, the LAT
MSL
and HAT
MSL
were interpolated
employing Inverse Distance Weighting (IDW) to develop the PMQCTD (LAT
MSL
and HAT
MSL
) with the
ArcGIS software. The statistical assessment indicated that the established PMQCTD (LAT
MSL
and
HAT
MSL
) has a better agreement with the DSMM tide gauges with a Root Mean Square Error (RMSE) of
± 0.228 m for LAT
MSL
and ± 0.159 m for HAT
MSL
In conclusion, the establishment of PMQCTD (LAT
MSL
and HAT
MSL
) has led to the a vailability of the tidal datum at any location along the coast of Peninsular
Malaysia.
Keywords-tide gauge station; satellite altimeter; tide model driver; tidal datum; IDW integration
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I. INTRODUCTION
Traditionally, data from the tide gauge stations have been
exploited to establish a localised tidal datum, such as the
Lowest Astronomical Tide (LAT), Mean Sea Level (MSL), and
Highest Astronomical Tide (HAT) along the coast [1, 2].
Currently, there are 19 continuously operating tide gauges in
Malaysia by the Department of Survey and Mapping Malaysia
(DSMM) [3, 4]. Accordingly, Malaysia has a maritime area of
55,629
and 329,960
of land area [5]. Hence, relying
solely on 19 tide gauge stations to monitor the variation of sea
level along the 55,629
of Malaysia’s coast is insufficient
as there are areas without any tidal datum information [4, 6].
The satellite altimeter has been evolving since 1975.
Currently, there are a total of 13 satellite missions that have
been operating from 1985 to 2022, such as TOPEX/Poseidon,
Jason-1, Jason-2, Jason-3, GEOSAT Follow On (GFO), ERS-1,
ERS-2, ENVISAT-1, Cryosat-2, SARAL, and Sentinel-3A and
Sentinel-6 [7, 8]. Accordingly, a satellite altimeter has three
long-term scientific objectives, which are observing the
circulation of the oceans, monitoring the volume of the polar
ice plate, and observing the variation in the sea level. Hence,
due to their vast coverage for data acquisition, satellite
altimeters have been considered as an additional approach to
monitoring the regional sea levels [9, 10].
Nowadays, with the advancement of the Global Navigation
Satellite S ystem (GNSS) for real-time positioning and satellite
altimeter for bathymetry derivation, there is a significant
improvement in the hydrographic surveying technique [3, 7].
Such an advancement leads to the development of a continuous
tidal datum along the coast by integrating the tide gauge and
satellite altimetry data for bathymetry determination, as well as
GNSS for p ositioning, in which all the derivation of the tidal
datum will refer to a similar local reference surface, such as the
MSL, or the global reference surface, for example, the World
Geodetic System 1984 (WGS84) ellipsoid [1, 10, 11].
In relation to the development of a continuous tidal datum
using geodetic-based approaches, many countries have begun
to develop their continuous tidal datum for their respective
region, e.g. France in 2005 [12, 13], UK and Ireland in 2009
[14], Canada in 2010 [15, 16], Netherlands and Belgium in
2018 [17], the Kingdom of Saudi Arabia in 2019 [18], and
Malaysia [7].
However, despite the previous model for continuous tidal
datum yielding an acceptable result in terms of vertical and
horizontal accuracy, there are still several limitations that can
be further improved in the future. In this study, two significant
issues were addressed. The first issue regards the utilization of
an insufficient number of tide gauge stations that are sparsely
distributed along the coast. Since the characteristic of the tide is
site-specific, approximately within a 10 km radius around the
coast, the determination of the tidal datum for the area situated
further from the tide gauge is inaccurate. Moreover, only
depending on the extrapolation of the tidal datum using a
limited number of tide gauges is still insufficient to produce an
accurate tidal datum, due to the propagation of errors during the
extrapolation process from a limited and sparsely distributed
known point, which will continue to increase according to the
travelling distances for datum transfer. The second issue
concerns the most suitable approach of integrating the derived
tidal datum from multiple sources, which is achieved either by
employing a hydrodynamic model, an empirical model, an
assimilation model, or spatial interpolation. The derived tidal
datum from the tide gauge refers to the zero-tide gauge. On the
other hand, the derived tidal datum from satellite altimetry
refers to the TOPEX ellipsoid for the TOPEX class satellite
mission or the WGS84 ellipsoid for the ERS-class satellite
mission. Hence, to develop a consistent and near-seamless tidal
datum, the derived tidal datum for all tidal data sources must be
referenced to a similar reference surface. This can be
accomplished by either referring the derived tidal datum (LAT
and HAT) to a global reference surface, such as the WGS84 or
GRS80 ellipsoid, or a local reference surface, like the MSL.
Thus, based on all the previous and current issues involving the
approach in establishing a continuous tidal datum based on the
tide gauge and satellite altimetry, this study aims to develop the
Peninsular Malaysia Quasi-Continuous Tidal Datum
(PMQCTD) using tide gauge, satellite altimetry, and TMD
data. Its integration aims to establish a quasi-continuous tidal
datum surface along the coast of Peninsular Malaysia,
especially at locations without any tidal datum information,
because they are located far from the DSMM tide gauge
stations, and satellite altimeter track. In addition, the
establishment of the PMQCTD improves the most current
continuous tidal datum (MyVSEP), which only utilizes tide
gauge and satellite altimetry data.
II. RESEARCH METHODOLOGY
This study is divided into 3 phases. Phase 1 highlights the
literature review, the identification of the study area, and the
data acquisition stages. Phase 2 focuses on the derivation of the
tidal datum from the tide gauge, satellite altimetry, and TMD
data. Phase 3 focuses on the integration of the tide gauge,
satellite altimetry, and TMD data to develop the PMQCTD
(
and
) using Inverse Distance Weighting
(IDW) interpolation [19]. Conclusions were drawn based on
the results of the findings.
A. Study Area
The study area is the east and west coast of Peninsular
Malaysia, ranging between (1° N < Latitude < 7° N) and (99° E
< Longitude < 105° E). The proposed locations for data
acquisition applying the ArcGIS software are illustrated in
Figure 1.
B. Data Acquisition
The data acquired for this study came from three source
types, i.e. tide gauge data from DSMM, satellite altimetry data
from TOPEX, Jason-1, Jason-2, and GFO from RADS, and
tidal datum prediction using TMD.
1) Tide Gauge Data from 12 Tide Gauge Stations of DSMM
The DSMM tide gauge station data implemented in this
study were obtained from the University of Hawaii Sea Level
Centre (UHSLC) [20]. The tide gauge data of 12 stations in
Peninsular Malaysia were considered over a duration of 23
years, from 1993 to 2015. According to [8, 21-22], the
minimum period of tidal observation for a stable tidal datum
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sing Tide Gauge
…
determination is 18.6 years, which represents the time spent by
the moon to make a complete revolution around the Earth.
Therefore, since this study uses 23 years of tidal observation
data for tide gauge, satellite altimetry, and TMD, it complies
with the aforementioned requirement. The details are portrayed
in Figure 2.
Fig. 1. Study area.
Fig. 2. The 12 DSMM tide gauge stations used i n this study.
However, the distance between each DSMM tide gauge
station as depicted in Figure 3 ranges from 42.690 km to
176.26 km. Such distances do not fulfil the requirement of a 10
km radius [23] for the establishment of an acceptable and
reliable tidal datum (LAT, MSL, and HAT).
2) Satellite Altimetry Data from RADS
The satellite altimeter deployed in this study consists of
non-sun synchronous satellite missions, which are the TOPEX
class (TOPEX, Jason-1, Jason-2) and the GFO mission. The
satellite altimetry data in this study were extracted from the
Radar Altimeter Database System (RADS) [24]. The non-sun
synchronous satellite mission was chosen in this study due to
its compatibility with harmonic analysis. For this study, since it
shares a similar orbit, the TOPEX class satellite mission
(TOPEX, Jason-1, and Jason-2) was combined to create a
single time series data encompassing 23 years of tidal
observation from 1993 to 2015 [8, 9]. Equivalently to the tide
gauge data, the combination of the TOPEX class mission also
complies with the requirement of 18.6 years of tidal
observation for a stable tidal datum determination. On the other
hand, due to its different orbit from the TOPEX class satellite
mission, the GFO satellite mission cannot be combined with
the TOPEX class mission [7-9]. However, owing to its
compatibility with harmonic analysis, the GFO mission was
also utilized as an additional satellite altimetry data to ensure
denser data coverage for the tidal datum determination. The
satellite altimeter track for the TOPEX class and GFO satellite
mission illustrated using ArcGIS is shown in Figure 3.
Fig. 3. Satellite altimetry points (492 points) for TOPEX class (315 km
satellite altimeter track) and GFO (220 km satellite altimeter track) for the
Peninsular Malaysia regio n considered in this study.
315 km
220 km
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…
Unfortunately, the width of the satellite altimeter track for
the TOPEX class mission is 315 km, whereas for the GFO
mission, it is 220 km. Such a distance does not comply with the
requirement of a 10 km radius for the establishment of an
acceptable and reliable tidal datum (LAT, MSL, and HAT)
[23].
3) Tide Model Driver (TMD) Data
TMD is a MATLAB package developed by Earth and
Space Research (ESR) and Oregon State University (OSU) to
access the tidal constituents for high-latitude tidal analysis and
prediction [25]. The tidal constituent was deployed in making
predictions of tidal height and currents based on the
hydrodynamic model [26]. It consists of two significant
functions. The first one is a Graphical User Interface (GUI) for
browsing tide fields, selecting study areas, and determining a
specific coordinate and duration of time for tidal predictions of
a specific variable. Secondly, it comprises a set of
programming codes for accessing tide fields [25, 26]. It has
been generally used to model the tides engaging the resolution
medium (1/40 × 1/40) [25, 26]. Accordingly, TMD has been
utilized to derive the tidal datum (LAT, MSL, and HAT) within
the same period of observation data with tide gauge and
satellite altimetry data, which is from 1993 to 2015 (23 years).
Figure 4 displays the coordinates of the 377 points and their
locations, respectively, imported into the ArcGIS working layer
to be integrated with the tide gauge and satellite altimetry data.
For this study, TMD was introduced as a complementary tidal
data source, rather than just relying on the tide gauge and
satellite altimetry data. TMD is capable of predicting the
specific point within 0 to 100 km from the coastline, by a set
distance of 10 km radius for each point, allowing it to comply
with the 10 km radius as stated in [23].
Fig. 4. 377 p oints wit hin 0 to 20 km from the coastal line to be predicted
using TMD.
Hence, with the addition of TMD, along with its integration
with the tide gauge and satellite altimetry data, a reliable tidal
datum along the coast of Peninsular Malaysia can be
established in comparison with [3].
III. DATA PROCESSING AND ANALYSIS
A. Derivation of Tidal Datum for Tide Gauge Data
The tide gauge data (1993 to 2015) from 12 DSMM tide
gauge stations were processed deploying harmonic analysis,
which uses Unified Tidal Analysis and Prediction Software
(UTide) in MATLAB based on 11 major tidal constituents
(
,
,
,
,
,
,
,
,
,
[8-9, 27].
The 11 tidal constituents are tabulated in Table I. The derived
tidal datum (LAT, MSL, and HAT) was then integrated with
the satellite altimetry and TMD data.
TABLE I. 11 MAJOR TIDAL CONSTITUENTS
Tide
Category
Tidal
constituents Phenomenon
Semi-Diurnal
Lunar principle
Solar principle
Large lunar ecliptic
Lunar solar semi-diurnal
Diurnal
Luni solar diurnal
Principle lunar diurnal
Principle solar diurnal
Large lunar ecliptic
Shallow
Water
Twice the angular velocit y
due to the
influence of the moon in shallow water
and
interactions in shallow water
Shallow water quarter diurnal constituent
B. Derivation of Tidal Datum from Satellite Altimetry Data
The TOPEX class mission is truncated to create a time
series of 23 years of tidal data for a stable determination of the
tidal datum. Similarly, the satellite altimetry data for TOPEX
class and GFO satellite missions, were processed using UTide.
The amplitude and phase of 11 tidal constituents,
,
,
,
,
,
,
,
,
, and
were estimated based
on the SSH time series from the TOPEX class and GFO
satellite missions using harmonic analysis. The derived tidal
datum (LAT, MSL, and HAT) with a total of 492 points for
satellite altimetry data as illustrated in Figure 4 was
interpolated following the IDW interpolation technique.
C. Derivation of Tidal Datum from Tidal Prediction using
TMD
The TMD was used to derive the tidal datum for 377
locations within 0 to 20 km from the coast of Peninsular
Malaysia. The derivation of the tidal datum through TMD was
also based on 11 tidal constituents utilizing the Indian Ocean
1/12º hydrodynamic model [28]. The derived tidal datum
(LAT, MSL, and HAT) with a total of 377 points for TMD data
as observed in Figure 5 was then interpolated adopting the
IDW interpolation technique.
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D. Integrating Tide Gauge, Satellite Altimetry, and Tide
Model Driver (TMD) Data using IDW Interpolation
There are two approaches for integrating the tidal datum
from the tide gauge, satellite altimetry and TMD data, either by
using the reference ellipsoid or the offset of MSL. For this
study, the integration of three datasets was performed on the
basis of the offset, using the MSL as a reference surface,
denoted as
and
. The determination of
and
for the tide gauge, satellite altimetry, and TMD-
derived tidal datum were based on (1) and (2),
(1)
MSL (2)
Accordingly, the location of 12 DSMM tide gauge stations
is portrayed in Figure 2. On the other hand, the satellite
altimetry data for TOPEX, Jason-1, and Jason-2 for Phase (A
and B), as well as GFO (Phase A), are illustrated in Figure 3.
The 377 points of tidal prediction using TMD are depicted in
Figure 4. The integration of all datasets (with a total of 881
points) is illustrated in Figure 5. The integration of the derived
tidal datum from the tide gauge, satellite altimetry data, and
TMD was conducted in ArcGIS. The tide-gauge, satellite
altimetry, and TMD-derived tidal datum (
and
)
in point-based were further interpolated using IDW to establish
the PMQCTD (
and
) along the coast of
Peninsular Malaysia.
Fig. 5. Integration of 12 DSMM tide gauges, 492 satellite altimetry points,
and 377 TMD data in ArcGIS.
Consequently, the reliability of the PMQCTD (
and
) still needs to be assessed. Therefore, in this study, the
PMQCTD (
and
) was statistically evaluated in
terms of their standard deviation (STD) and Root Mean Square
Error (RMSE) by comparing the PMQCTD (
and
) established from the combination of the tide gauge
and satellite altimetry data with the PMQCTD (
and
) established from the combination of tide gauge,
satellite altimetry, and TMD data. The statistical assessment
was based on the offset of PMQCTD (
and
)
with the offset from the DSMM tide gauge (
and
). In addition, the comparison of the two combinations
was conducted to identify the rate of improvement of the
PMQCTD (
and
) with the addition of TMD
data.
IV. RESULTS AND DISCUSSION
A. Derivation of Tidal Datum for Tide Gauge Stations
The derived tidal datum of LAT, MSL, and HAT with
respect to zero tide gauge for the 12 DSMM tide gauge stations
along the coast of Peninsular Malaysia is tabulated in Table II.
The result is based on the duration of tide gauge data from
1993 to 2015 (23 years). Accordingly, the tidal datum has been
determined using harmonic analysis focusing on 11 tidal
constituents (
,
,
,
,
,
,
,
,
,
employing UTide. The derived tidal datum, LAT,
and HAT were referenced to MSL, denoted as (
and
) according to (1) and (2).
TABLE II. TIDE-GAUGE-DERIVED TIDAL DATUM
Tide gauge
stations
LAT
(m)
MSL
(m)
HAT
(m)
!
(m)
"
!
(m)
Cendering 0.819 2.137 3.500 -1.318 1.363
Geting 1.644 2.310 3.246 -0.666 0.936
Tanjung
Gelang 1.042 2.835 4.661 -1.793 1.826
Tioman 0.988 2.781 4.399 -1.793 1.618
Sedili 1.108 2.392 3.691 -1.284 1.299
Langkawi
0.440
2.240
3.957
-
1.800
1.717
Penang
1.037
2.679
4.106
-
1.642
1.427
Lumut 0.724 2.204 3.563 -1.480 1.359
Port Klang 0.640 3.509 6.457 -2.869 2.948
Tanjung
Keling 1.645 2.845 4.186 -1.200 1.341
Kukup 2.401 4.024 5.991 -1.623 1.967
Johor Bahru 0.794 2.879 4.508 -2.085 1.629
B. The IDW Interpolation of Tidal Datum (#$%
&'(
and
)$%
&'(
) for Satellite Altimetry Data
The derived tidal datum (
and
) from the
satellite altimetry data (TOPEX class and GFO) with a total of
492 points was interpolated following the IDW interpolation
technique using ArcGIS. The result of the interpolation is
illustrated in Figure 6.
C. The IDW Interpolation of Tidal Datum (#$%
&'(
and
)$%
&'(
) for TMD Data
The derived tidal datum (
and
) from TMD
with a total of 377 points was interpolated via the IDW
interpolation technique using ArcGIS. The result of the
interpolation is detected in Figure 7.
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Continuous Tidal Datum for Peninsular Malaysia u
sing Tide Gauge
…
(a)
(b)
Fig. 6. (a) and (b) for satellite altimetry data using IDW
interpolation in ArcGIS.
D. Integration of Tide Gauge, Satellite Altimetry, and TMD
Data to Develop the PMQCTD *#$%
+,-
and )$%
+,-
)
Once the tidal datum from tide gauge stations, satellite
altimetry, and TMD has been determined and referenced to a
similar reference surface, the tidal datum (
and
) can finally be integrated employing the IDW
interpolation in ArcGIS. Hence, the quasi-continuous tidal
datum,
and
, for Peninsular Malaysia was
established. However, the accuracy of the PMQCTD *
and
) must be statistically assessed in terms of its STD
and RMSE with the DSMM tide gauge (in-situ).
The assessment was made between the PMQCTD *
and
) established from tide-gauge and satellite-
altimetry-derived tidal datum and the PMQCTD *
and
) established from tide-gauge, satellite-altimetry, and
TMD-derived tidal datum. The reliability of both approaches
was reviewed implementing 9 DSMM tide gauge stations as in-
situ data. Such assessments were conducted to show the rate of
improvement by deploying TMD, as additional tidal data. The
PMQCTD (
) based on the integration of
tide gauge, satellite altimetry, and TMD-derived tidal datum is
exhibited in Figure 8.
(a)
(b)
Fig. 7. (a) and (b) for TMD data using IDW interpolation
in ArcGIS.
E. Statistical Assessment of the PMQCTD (#$%
+,-
and
)$%
+,-
) with DSMM Tide Gauge Stations
The reliability of the PMQCTD (
) was
statistically assessed based on the offset of
and
in terms of their STD and RMSE. The statistical
assessment of both approaches (using TMD and without using
TMD) of PMQCTD (
) was conducted to
determine which combination demonstrates a better agreement
with the 9 DSMM tide gauge stations (excluding Johor Bahru,
Tanjung Keling, and Kukup due to poor coverage of satellite
altimetry data). The PMQCTD (
and
) with the
smallest RMSE and STD in comparison with the DSMM
coastal tide gauges signify the best approach for establishing
the PMQCTD (
and
). The statistical analysis
for PMQCTD (
and
) with the 9 DSMM tide
gauge stations is presented in Tables III and IV, respectively.
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…
(a)
(b)
Fig. 8. PMQCTD (a) and (b) from t he combination of
tide-gauge, satellite-alti metry, and TMD-derived tid al datum in ArcGIS.
TABLE III. STATISTICAL ASSESSMENT OF PMQCTD
() WITH D SMM TIDE GAUGE STATIONS
Tide gauge
station
In-Situ
(m)
PMQCTD
(
./)
from TG
and SALT
(m)
PMQCTD
(
./)
from TG
and SALT -
In Situ (m)
PMQCTD
(
./)
from TG,
SALT, and
TMD (m)
PMQCTD
(
./)
from TG,
SALT &
TMD - In
Situ (m)
Cendering -1.318 -0.978 0.340 -1.219 0.099
Geting -0.666 -0.610 0.056 -0.415 0.251
Lumut -1.480 -1.230 0.250 -1.527 -0.047
Penang -1.642 -1.003 0.639 -1.194 0.448
Langkawi -1.800 -1.970 -0.170 -1.52 6 0.274
Port Klang
-
2.869
-
1.821
1.048
-
2.476
0.393
Tioman
-
1.793
-
1.337
0.456
-
1.563
0.230
Tanjung
Gelang -1.793 -1.030 0.763 -1.629 0.164
Tanjung
Sedili -1.284 -1.185 0.099 -1.463 -0.179
STD 0.334 STD 0.175
RMSE ± 0.410 RMSE ± 0.228
TABLE IV. STATISTICAL ASSESSMENT OF PMQCTD
() WITH DSMM TIDE GAUGE STATIONS
Tide Gauge
In-
Situ
(m)
PMQCTD
(
"
./)
from TG
and SALT
(m)
PMQCTD
(
"
./)
from TG
and SALT -
In Situ (m)
PMQCTD
(
"
./)
from TG,
SALT, and
TMD (m)
PMQCTD
(
"
./)
from TG,
SALT, and
TMD - In
Situ
(m)
Cendering 1.363 1.154 -0.209 1.315 -0.048
Geting
0.963
0.534
-
0.429
0.730
-
0.233
Lumut 1.359 1.062 -0.297 1.360 0.001
Penang 1.427 1.073 -0.354 1.199 -0.228
Langkawi 1.717 1.309 -0.408 1.511 -0.206
Port Klang 2.948 1.958 -0.990 2.465 -0.483
Tioman 1.618 1.357 -0.261 1.513 -0.105
Tanjung
Gelang 1.826 1.388 -0.438 1.742 -0.084
Tanjung
Sedili 1.299 0.973 -0.326 1.133 -0.166
STD 0.272 STD 0.079
RMSE ± 0.368 RMSE ± 0.159
For the statistical assessment of the PMQCTD (
,
the result has indicated a better STD of 0.175 m and RMSE of
± 0.228 m for the PMQCTD (
established from the
tide-gauge, satellite-altimetry, and TMD-derived tidal datum in
comparison to the PMQCTD (
established from the
tide-gauge and satellite-altimetry-derived tidal datum, which
demonstrates an STD of 0.334 m and RMSE of ±
0.410 m. The
addition of TMD-derived tidal datum with tide gauge and
satellite altimeter has showcased an increase by 44%.
A similar outcome was achieved for PMQCTD (
)
established from tide-gauge, satellite-altimetry, and TMD-
derived tidal datum, which exhibits an STD of 0.079 and
RMSE of ± 0.159 m in comparison to the PMQCTD (
)
established from tide-gauge and satellite-altimetry-derived tidal
datum with an STD of 0.272 m and RMSE of ± 0.368 m,
respectively. Likewise, the addition of TMD-derived tidal
datum with tide gauge and satellite altimeter has manifested an
increase by 57%.
According to [8, 11, 29], such a rate of improvement
emerges from the lack of data coverage in the coastal region
owing to the utilization of low-resolution satellite altimetry
data, in which the contaminated signals due to the presence of
land areas have been removed before the interpolation.
However, with the utilization of the tidal prediction of 377
points within 0 to 20 km from the coastal line from TMD, this
limitation was mitigated. In addition, the employment of the
Indian Ocean hydrodynamic model [25] contributed to this
improvement. According to [7], the period of observation for
the TOPEX and TOPEX-tandem satellite altimetry mission is
approximately from 1993 to 2002. Hence, this study, by
including Jason-1 and Jason-2 (Phase A and B) to create a
time-series of 23 years from the TOPEX class satellite
altimetry mission, along with the additional GFO satellite
mission (from 2000 to 2008) has contributed to the acquisition
of data from a longer period of observation and with a denser
network of tidal observation for a reliable tidal datum
determination. The statistical assessment has indicated that the
rate of improvement for the PMQCTD (
and
)
established from tide-gauge, satellite-altimetry, and TMD-
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Abd Rahman et al.:
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sing Tide Gauge
…
derived tidal datum is 44% and 57%, respectively, in
comparison to the PMQCTD (
and
)
established from tide-gauge and satellite-altimetry-derived tidal
datum.
V. CONCLUSIONS
In conclusion, the establishment of the Peninsular Malaysia
Quasi-Continuous Tidal Datum (PMQCTD) (
and
) from tide-gauge, satellite-altimetry, and TMD-
derived tidal datum has led to the availability of a tidal datum
at any location along the coast of Peninsular Malaysia. Its
establishment has solved the first issues of the determination of
tidal datum from limited and sparsely distributed DSMM tide
gauge stations (with distances from 42.690 km to 176.26 km)
and wide satellite altimeter tracks for TOPEX class (315 km)
and GFO missions (220 km) along the coast of Peninsular
Malaysia. In addition, the utilization of TMD along with the
tide gauge and satellite altimetry data for establishing
(PMQCTD) (
and
) has demonstrated a better
RMSE with an increase of 44% and 57% for
and
, respectively, in comparison to the PMQCTD (
and
) established from tide gauge and satellite altimetry
data only.
Furthermore, regarding the issue involving the integration
of the tidal datum from multiple sources (tide gauge stations,
satellite altimeter, and Tide Model Driver), utilizing the MSL
as a common reference surface and the Inverse Distance
Weighting (IDW) spatial interpolation approach in developing
the PMQCTD (
and
), led to a uniform and
consistent establishment of the tidal datum along the coast of
Peninsular Malaysia for any hydrographic-related application.
ACKNOWLEDGEMENT
This project is funded by the Ministry of Higher Education
under the Fundamental Research Grant Scheme (FRGS)
(FRGS/1/2023/WAB05/UTM/02/1) and Universiti Teknologi
Malaysia for the funding under UTM Encouragement Research
(UTMER) (Q.J130000.3852.31J46).
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