*Corresponding author: Department of Civil Engineering, Engineering Faculty, Jember University, 62121, Indonesia E-mail address: [email protected] (Retno Utami Agung Wiyono)
doi: https://doi.org/10.21776/ub.pengairan.2023.014.02.5
Vol. 14 No. 02 (2023)
Jurnal Teknik Pengairan: Journal of Water Resources Engineering
Journal homepage: https://jurnalpengairan.ub.ac.id/index.php/jtp
Original research article
Tsunami – Tides Interaction of the South Coast of Jember Using Delft3D- Flow
Norma Aulia Narulita
a, Retno Utami Agung Wiyono
a*, Gusfan Halik
a, Munawir Pratama
baDepartment of Civil Engineering, Engineering Faculty, Jember University, 62121, Indonesia
bSchool of Engineering, The University of Edinburgh, EH9 3FB, United Kingdom
A R T I C L E I N F O A B S T R A C T
Keywords:
Tsunami;
Tides;
Jember
The tsunami of June 3, 1994, which originated from a shift in the Indo-Australia plate, resulted in hundreds of casualties and material damage on the south coast of Jember. This study aims to understand the tidal impact of a tsunami in terms of arrival time and wave height. Several simulations of the interaction of tidal waves with tsunami waves were carried out through numerical modeling using Delft3D with modified wave characteristics from the Banyuwangi tsunami on June 3, 1994, as well as using bathymetry data from BATNAS and BIG tide data. The results of the analysis show that tidal waves can be a factor affecting the height of the tsunami waves. The increase in the amplitude of the tsunami waves was considered very local from the three observation points. This is shown at the observation locations of Puger Beach and Watu Ulo Beach, where the maximum wave amplitude occurs when the tsunami occurs independently of 7.102 m and 5.56 m, while at the Tanjung Pelindu observation location, the highest amplitude occurs when the tsunami meets the tides during low tide phase, which is 3.68 m. This research is expected to provide a basic understanding of the dynamic impact of the tidal wave when a tsunami occurs.
1. Introduction
The southern coast of Jember is faced with the potential for a tsunami disaster due to an underwater subduction zone or the long Indo-Australian trough, or what is commonly called the megathrust zone. The difference in the position of the earth’s plates can trigger movement between plates, produce megathrust earthquakes, and generate powerful tsunami waves.
The south coast of Jember was one of the areas affected by the 1994 Banyuwangi tsunami that occurred on June 3, 1994.
The tsunami was triggered by a shift in the Indo-Australian plate located approximately 200 km from the south coast of Java. This disaster resulted in no less than 250 fatalities, six missing persons, and damage to thousands of houses and hundreds of fishing. A study reported that the height of the tsunami waves that reached Puger Beach, Tanjung Pelindu, and Watu Ulo Beach were 4.88 - 5.85 m, 3.2 m, and 6.5 - 7.5 m, respectively [1].
Another study analyzed the interaction between the September 2015 Chilli tsunami with tidal or ebb waves [2]. The results show a systematic relationship between the attenuation rate of the tsunami and the tidal phase on the wave-locked slopes on the tidal-modified river water level.
The friction of the tsunami waves is relatively small, with tidal currents that are linear with the tsunami component. The observed slope of the base river determines the friction coefficient. In addition, linear superimposition of tides and tsunamis can occur in the high seas because they have very small amplitude compared to the depth of the water [3].
Another research explained the probability distribution of maximum tsunami wave heights as the effects of tides [4]. The tsunami was superimposed on the predicted tides for the open coast at Seaside, Oregon. This location has a mixed semidiurnal type of tide like on most other US west coasts. The probability density function for the tides is combined with the tsunami heights from various locations and magnitudes to determine the distribution of the total wave heights. It was concluded that the total wave height is the result of the linear sum of the tides with the time series of the tsunami and will continue to decrease exponentially in amplitude in multiples of two days at observation locations throughout the Pacific.
Particularly at river mouths, tsunami behavior is greatly influenced by the specific bathymetry of each location and also the characteristics of the tidal waves [5]. The speed and acceleration of tsunamis in the estuary area are considered very significant and can cause losses, which are greatly
144 influenced by sea tides. This has been proven by [6] in terms of modulating the tsunami amplitude during the full tidal cycle. The “orphan tsunami” in the Pacific Northwest of the United States in 1700 was a large tsunami in the Cascadia subduction zone area. As a future mitigation effort, this study found that tsunami waves that entered through a narrow river mouth would be damped and spread their energy. The amplitude of the tsunami transforms into a small and long- period wave that flows 173 km from the ocean [6].
The relationship between river width and tsunami height can be explained in Green’s Law. His study explained that the distance for a tsunami to reach the upstream is greatly influenced by tides, not only the geographical conditions of the estuary (the width and depth of the estuary) [7]. The bigger the entrance to the river, the easier it is for a tsunami to enter.
Likewise, the simulation results of tidal and tsunami interactions for the Hudson River Estuary (HRE) in most of the tidal phases for three different tsunami magnitudes cause an increase in inundation (0.2 - 0.8 m for different locations) in the HRE [8].
In a study, two tsunami waves were disturbed by combined tidal waves in a linear superposition [9]. As a result, the arrival time of the combined tsunami waves is 10 minutes earlier than the linear superposition model. This can result in a sudden surge or a long, narrow shock wave down the coast.
Therefore, the liner superposition model is considered safer in generating tsunami wave heights.
Another study managed three models with the same seismic scenario with constant tide levels, six composite models (the tide model and tsunami model were run independently, then the results were superimposed linearly), six models (complete) non-linear interactions (the tsunami model is run until it reaches balance then given disturbances from tidal waves) [10]. As a result, the composite and complete models are equally sensitive to tidal conditions where the local depth of the canal also influences tsunamis. The amplitude and arrival time of the tsunami waves using the complete model turned out to be very dependent on the direction of the tidal currents and less sensitive to the height and speed of the tides.
Several previous studies for the south coast of Jember still focused on modeling tsunamis and tides separately and did not provide an understanding of the impact of the interaction between the two. In modeling involving megathrust tsunami waves on the Jember Coast, a study [11] uses three different scenarios in terms of the earthquake magnitude used: the first uses the characteristics of the 1994 Banyuwangi earthquake, the second uses the characteristics of the 2006 Pangandaran earthquake, and the third uses a combination scenarios one and two. The simulations show that in the three scenarios, the tsunami heights were between 11 – 22 m, with a time of arrival of 40 minutes and water returning to normal at 150 minutes.
Another study [12] made a tsunami model (independently) on the Jember Coast, with the scenario magnitude of the 1994 Banyuwangi earthquake (7.8 Mw) and the megathrust earthquake (9.1 Mw).
The current study intends to show the impact of the interaction of tsunami waves and tides through three scenarios involving tsunamis and sea tides. The tsunamis that are modeled independently will be compared with the
tsunamis that are affected by each tide and ebb so that the influence of the tidal or low tide values on the amplitude height and arrival time of each model scenario will be known.
This research is expected to provide a basic understanding of the dynamic impact of tidal waves when a tsunami occurs.
2. Method
The research area includes three observation points:
Pelindu Beach (113.3° E; -8.311° S), Puger Beach (113.46° E; - 8.386° S), and Watu Ulo Beach (113.56° E; -8.431 °S) Jember Regency (Figure 1(a)). The constructed domain model includes the south coast of Jember and the Indo-Australian fault as the location of the earthquake source (Figure 1(b)).
The movement of tectonic plates causes faults. The influence of vertical and horizontal forces causes this. This results in permanent shear displacement between blocks of soil masses. This shift can be in the vertical, horizontal direction, or a combination. Generally, faults have characteristics such as length, depth, and width. The length of the fault itself can reach hundreds of meters, while the fault ranges from 20-30 km, and the width of the fault can reach tens of meters [13]. Faults are boundaries between the earth’s plates that protrude into the ground. Fault instability causes movement between two tectonic plates. There are three fault movement mechanisms: up fault, down the fault, and shear fault. According to [14], the fault plane parameters consist of a strike, dip, and rake. A Strike (ϕ) is formed by a fault plane with a north direction. Measured from north to east clockwise to the fault plane. Dip (δ) is the angle calculated from the plane of the fault in the horizontal direction and is measured in the vertical plane perpendicular to the direction of the fault. Rake (λ) is the angle formed from the slip direction and the fault plane. The rake is positive on an up fault; it is called a Thrust Fault, and if it is negative on a down fault, it is called a Normal Fault. To describe the fault plane that causes earthquakes and determine the type of plate movement, one needs strike and dip parameters and a rake [15]. In BMKG earthquake and tsunami event records [16], no larger earthquake resulted in a tsunami in the observation area (Jember’s south coast and its surroundings) for the period before 1994.
The research phase starts with data collection activities.
The data includes parameter data for the 1994 Banyuwangi earthquake, BIG tidal data, and bathymetry data (BATNAS).
Modeling begins using the Delft Dashboard to construct grids of the simulation domain, determine physical parameters, create boundary conditions with tidal data input, and determine observation locations. Delft3D-Flow was utilized to carry out the process of running the model and visualizing the output on the quickplot menu.
The modeling scenarios are divided into 4. Scenario 1, is an independent tsunami modeling using the parameters of the 1994 Banyuwangi earthquake from the USGS with modification of slip for calibration purpose to reach the observation report Maramai and Tinti [1]. Before proceeding to Scenarios 3 and 4, the tsunami model for Scenario 1 has been validated using MAPE to assess whether the tsunami height resulting from the simulation can be used in Scenarios 3 and 4. Scenario 2 is an independent model for tidal waves.
145
Figure 1. Research location on the Delft Dashboard (a) observation location of P. Puger, Tj. Pelindu, and P. Watu Ulo (b) The model domain stretches from the south coast of Jember to the Indo-Australian fault.
Scenario 3 combines the tsunami and high tide on one model, while Scenario 4 is a combination of the tsunami and low tide phase. The independent model scenario for tsunami and tidal waves is intended to determine the stability of the tsunami and tidal waves in advance.
2.1. Research Materials
For bathymetric data, BATNAS data was used. It has a spatial resolution of 6 arc seconds (about 180 meters) using MSL (Mean Sea Level) and EGM2008 data. This resolution is considered detailed compared to global bathymetry data. This bathymetry data has advantages in coastal areas and shallow waters because it uses surveys from the Center for Marine and Coastal Environment (PKLP, BIG). Generally, national bathymetry data is made from inversion of gravity anomaly data obtained from allometric data processing, coupled with sounding data from BIG, NGDC, BODC, BPPT, LIPI, P3GL, and other institutions using single or multibeam.
One of the main data needed is tidal data. Tidal prediction is obtained from the Indonesian Geospatial Information Agency. The tides around the Puger Beach area, according to [17], [18], are dominated by the influence of the tides, which can experience ebb and flow phases, each of which can be up to two times a day and have almost the same height or are commonly called semidiurnal tides, this occurs due to the gravitational pull of the moon with M2 of 61 cm. The earthquake parameters used are the 1994 Banyuwangi earthquake parameters from the USGS. The initial condition used multi-faults with five segments, as shown in Table 1 for the first scenario. Of these parameters, a calibration is performed by changing the depth and slip parameters so that the simulated tsunami water level can approach the results of observations made by [1].
2.2. Research methods
Delft3Flow is a multidimensional hydrodynamic simulation program developed by Deltares which is used to simulate tsunamis, tides, and interaction between both cases.
This model can be used for two-dimensional and three- dimensional calculations. However, because the horizontal length and time scales are significantly larger than the vertical scales, two-dimensional horizontal calculations are considered in this study. The momentum equations for the x and y directions are given in Equations 1 and 2, while the 2D (vertically integrated) continuity is given in Equation 3
Deltares (2021) as follows:
𝜕𝑢
𝜕𝑡
+
𝑢√𝐺𝜉𝜉
𝜕𝑢
𝜕𝜉
+
𝑣√𝐺𝜂𝜂
𝜕𝑢
𝜕𝜂
+
𝜔𝑑 + 𝜁
𝜕𝑢
𝜕𝜎
−
𝑣2√𝐺𝜉𝜉√𝐺𝜂𝜂
𝜕√𝐺𝜂𝜂
𝜕𝜉
+
𝑢𝑣
√𝐺𝜉𝜉√𝐺𝜂𝜂
𝜕√𝐺𝜉𝜉
𝜕𝜉
− 𝑓𝑣 = −
1𝜌0√𝐺𝜉𝜉
𝑃𝜉 + 𝐹𝜉 +
1 (𝑑+𝜁)2
𝜕
𝜕𝜎
(𝑣𝑣
𝜕𝑢𝜕𝜎
) + 𝑀𝜉
(1)𝜕𝑢
𝜕𝑡
+
𝑢√𝐺𝜉𝜉
𝜕𝑢
𝜕𝜉
+
𝑣√𝐺𝜂𝜂
𝜕𝑢
𝜕𝜂
+
𝜔𝑑 + 𝜁
𝜕𝑢
𝜕𝜎
+
𝑢𝑣√𝐺𝜉𝜉√𝐺𝜂𝜂
𝜕√𝐺𝜂𝜂
𝜕𝜉
−
𝑢2
√𝐺𝜉𝜉√𝐺𝜂𝜂
𝜕√𝐺𝜉𝜉
𝜕
− 𝑓𝑢 = −
𝜌0√𝐺1𝑃 + 𝐹 +
1 (𝑑+𝜁)2
𝜕
𝜕𝜎
(𝑣𝑣
𝜕𝑢𝜕𝜎
) + 𝑀
(2)𝜕𝜁
𝜕𝑡
+
1√𝐺𝜉𝜉√𝐺𝜂𝜂
𝜕((𝑑+𝜁)𝑈√𝐺𝜂𝜂)
𝜕𝜉
+
1
√𝐺𝜉𝜉√𝐺𝜂𝜂
𝜕((𝑑+𝜁)𝑉√𝐺𝜉𝜉)
𝜕𝜂
= (𝑑 + 𝜁)𝑄
(3) Where U and V are defined as the average depth velocity, that is :𝑈 =
1𝑑+𝜁
∫ 𝑢 𝑑𝑧 =
𝑑𝜁∫ 𝑢 𝑑𝜎
−10(4)
𝑉 =
1𝑑+𝜁
∫ 𝑣 𝑑𝑧 =
𝑑𝜁∫ 𝑣 𝑑𝜎
−10 (5) and Q is the contribution to the unit area due to water removal or withdrawal, precipitation, and evaporation. 𝑃𝜉 and P represents the pressure gradients, 𝑣𝑣 is the vertical vortex viscosity coefficient (m2/s), 𝐹𝜉 and F represents the horizontal imbalance of the Reynolds pressure (m/s2), 𝑀𝜉 and M represents external source contribution or momentum pool (external forces by hydraulic structures, water release or withdrawal, wave pressure, etc.) (m/s2). 𝑓 is the Coriolis parameter (inertial frequency) (1/s), 𝑢 is the flow velocity in the x or y direction (m/s), 𝑣 fluid velocity in x or y direction (m/s). 𝜔 speed in the direction in the coordinate system (m/s), ζ is the water level with t time and d as depth (m), √𝐺𝜂𝜂 = 𝑅 and √𝐺𝜉𝜉 = 𝑅 𝑐𝑜𝑠 𝜙, ϕ is the latitude, R is the radius of the earth (6378.137 km, WGS 84), 𝜉 and 𝜂 are the horizontal coordinates of the curve, qin dan qout local waterlogging per unit volume respectively, P is rainwater, E non-localized puddle due to evaporation, In this research, the initial process is to create a tsunami model independently without tides (here in after referred to as Scenario 1 model).146
Table 1. Tsunami scenarios Scenario 1
Independent tsunami model using the
characteristics of the 1994 Banyuwangi earthquake
Earthquake parameters for tsunami model Epicenter Location
MW Width (Km)
Depth (Km)
Dip (Deg)
Slip/Rake (Deg)
Slip Long (°) Lat (°) (m)
113,14° -10,547 7,8 22.2 11,5 83 91 15
Source: USGS
The initial condition model uses multi-fault, consisting of 5 segments with 144.6 km fault length.
Fault Model
Scenario 2
Consists of a high tides phase independent model (2a) and a low tide phase independent model (2b)
The difference between the two tidal phases used is that one starts with a high amplitude or during the high tide phase (Scenario 2a), and the other starts with a low amplitude or during the low tide phase (Scenario 2b).
Scenario 3
Merging scenario 1 with a high tides phase
independent model from Scenario 2a
When the independent tsunami model (Scenario 1) and the independent tide model in Scenario 2a are considered to have met the requirements, then Scenario 3, an interaction between the tsunami and tide models for high phase tides, is carried out.
Scenario 4
Merging scenario 1 with a low tides phase
independent model from Scenario 2b
When the independent tsunami model (Scenario 1) and the independent tide model in Scenario 2a are considered to have met the requirements, then Scenario 4, which is an interaction between the tsunami and tide models for low-phase tides, is carried out.
The Delft Dashboard is for grid settings, data input, and parameter settings and determines observation locations. The grid in the research domain is made with a size of 275 m x 275 m. The earthquake parameters are set in the fault area using the tsunami toolbox. The model calculation was performed using Delft3D-Flow, and modeling results were visualized through the quickplot Delft3D toolbox. Even the grid is relativity large for tsunami modeling, but after the validation process is carried out using MAPE (Mean Absolute Percentage Error), this model gets a minimum error value.
Simulation results from Delft3D were validated using MAPE (Mean Absolute Percentage Error) [18] with the following equation:
𝑀𝐴𝑃𝐸 = ∑ |𝑦𝑖− ŷi
yi | 𝑥 100%
𝑛𝑡=1 (6) With n = amount of data, y = actual yield value, ŷi = value of simulation results
(Validation error percentage of tsunami wave height should not be more than 0.1 or <10%).
The tsunami event in scenario 1 occurs within the first hour. This corresponds to the range of high and low tide phases in the first hour, as shown in the high and low tide curves in Table 1.
3. Results and Discussion
In this section, results from a simulation of Scenario 1 (independent tsunami model), Scenario 2 (independent tide model), Scenario 3 (tsunami and high tide model), and Scenario 4 (tsunami and low tide model) are discussed in term of wave height and arrival time to the observation points.
3.1. Scenario 1
Results from the simulation of Scenario 1 are shown below.
Figure 2 shows the results of Scenario 1 (independent simulation of tsunami). It can be seen that the tsunami waves started to touch the shoreline in 30 - 50th minutes, while the water level elevation and wave arrival time in each study area can be seen in Table 2 and Figure 3.
147
a) b) c)
Figure 2. Spatial surface elevation of Scenario 1 after. a) 30 minutes, b) 40 minutes, c) 50 minutes
Table 1. Altitude and arrival time results for Scenario 1 Observation location Water level elevation
(m)
Arrival time (minutes)
Watu Ulo Beach 7.107 39
Puger Beach 5.580 40
Tanjung Pelindu 3.443 48
Figure 3. Water Level from Scenario 1 (independent tsunami model)
Table 2. Validation of Scenario 1 results for tsunami height values [1] using MAPE No. Observation location
Tsunami wave elevation (m) simulation results
Tsunami wave elevation
(m) (Maramai & Tinti) MAPE Time (min.)
1 Watu Ulo 7.10706 7.5 5.2% 39
2 Puger 5.57951 5.85 4.6% 40
3 Tanjung Pelindu 3.44322 3.2 7.6% 48
Average MAPE 5.8%
148 Results of Scenario 1 (the independent tsunami model) show that at Watu Ulo Beach, the tsunami reached a height of 7.1 m. The waves reached the shoreline after 39 minutes. Watu Ulo Beach is geographically located at the easternmost compared to the other two observation locations. This could be a factor that affects the arrival time of waves at Watu Ulo Beach to be earlier. Meanwhile, at Puger Beach and Tanjung Pelindu, the wave heights reached 5.57 m and 3.34 m, and the arrival time was 40 and 48 minutes, respectively.
After obtaining the wave height values in Scenario 1, the height values are validated using the tsunami heights observed by [1]. The validation calculation method uses MAPE (Mean Absolute Percentage Error), which is a further value from the MAE (Mean Absolute Error) value by determining the resulting percentage value.
In evaluating the results of the validation using MAPE, there are four categories in the MAPE percentage assessment, that is <10% is considered “Very good”, 10-20% is considered
“Good”, 20-50% is considered “Reasonable”, and > 50% is assessed “Inaccurate or Failed”.
The MAPE values for the tsunami wave height in Table 2 are calculated using Equation 7. The percentage of error values from all observation locations was then calculated on average, and a MAPE value of 5.8% was obtained. Because the value is
<10%, according to the validation provisions in this study, the tsunami wave height value in this study is considered very good and acceptable.
3.2. Scenario 2
Scenario 2 is a tidal simulation that is divided into two, that is high tide with initial high tide phase (Scenario 2a) to be combined with Scenario 1 to become Scenario 3, and high tide simulation with initial high tide phase (Scenario 2b) to be combined with Scenario 1 to become Scenario model 4.
3.3. Scenario 3 dan 4
Scenario 3 is a composite model between tsunami and high tide, while Scenario 4 is a composite model between tsunami and low tide. The tsunami model from Scenario 1 was simulated simultaneously with high tide, which was defined in the boundary of the model domain. The high tide initiated Scenario 3, while the low tide initiated Scenario 4.
In Scenario 3, the waves produced a shock wave at 10 minutes, then break at 20 minutes towards the south coast of Jember. After 30 minutes (Figure4(a)), the waves approach the coast until they almost touch Nusa Barong Island.
After 40 minutes, the waves touched the beach (Figure4(b)). The waves arrived at Watu Ulo Beach, Puger Beach, and Tanjung Pelindu in the 39th minute. The wave height peaked in Tanjung Pelindu, with a wave height of 3.67 m after 57 minutes. After hitting the beach, the waves broke and spread around the beach and were reflected to the sea.
In Scenario 4, the tsunami waves that interact with the tidal waves with the initial low tide also significantly impact one of the location points, Tanjung Pelindu. In Figure 5(a), the waves that came first hit the beaches with the easternmost location.
Therefore, Watu Ulo Beach was the first to be hit by a wave, which was at 39 minutes. Meanwhile, the second location was
Puger Beach, with a wave arrival time of 40 minutes.
Figure 6 shows that Watu Ulo Beach has the highest amplitude in Scenario 1 (independent tsunami), with a maximum wave height of 7.1 m at 39 minutes. Meanwhile, second place is in Scenario 4, when the tsunami interacts with the tides with the ebb phase at low tide 0.14 m, with a wave height of 5.32 m in the 39th minute. The third sequence occurs in Scenario 3 when the tsunami interacts with the low phase (Scenario 4), which is 4.68 m in the 39th minute.
Watu Ulo Beach has variations in beach depth with two dominant depths, namely 1-12 m (1363 m far) and 78-100 m (1766 m far) depth. These two depth variations with a considerable distance make Watu Ulo the observation location with the smallest slope compared to the other two locations.
This condition may cause the highest tsunami run up (7.10 m) in Watu Ulo Beach compared to the other two observation locations. This result is supported by a study [8] explaining that complex bathymetry and large tidal currents can significantly increase surface elevation and inundation compared to static simulations.
Figure 7 shows that at Puger Beach, the highest amplitude value is obtained from Scenario 1 (standalone tsunami) at 40 minutes with a maximum wave height of 5.56 m. The second highest amplitude is in Scenario 4, when the tsunami interacts with the ebb phase at an ebb elevation of 0.11 m with a maximum amplitude of 3,233 m in the 40th minute. The third highest is obtained in Scenario 3 when the tsunami interacts with the high tide phase, which is 3.13 m in the 40th minute.
Puger Beach has a diversity of bathymetry with depth variations of 1-12 m (330 m), 12-34 m (655 m), and predominately depths of 34-56 m (3,323 m). The slope of Puger Beach is considered to be lower than that of Tanjung Pelindu, resulting in a higher tsunami run-up value (5.56 m) than Tanjung Pelindu’s (3.67 m). At Tanjung Pelindu, as shown in Figure 8, the maximum amplitude is obtained from Scenario 3 when the tsunami interacts with the high tide phase with a tide value of 0.25 m, with a wave height of 3.67 m at the 57th minute. The second order maximum elevation occurs in Scenario 1 when the tsunami occurs independently, that is 3.38 m in the 48th minute. The lowest elevation at Tanjung Pelindu occurs in Scenario 4 when the tsunami interacts with the tidal phase, which is 2.97 m in the 57th minute. Pelindu Beach obtains the maximum amplitude in Scenario 3 when the tsunami waves meet the tide, while at Watu Ulo Beach and Puger Beach, the maximum amplitude is obtained in Scenario 1 when the tsunami waves occur independently. This is stated by [19], who states that a location’s geometry and bathymetry conditions also play a role in determining wave height and current when the tsunami interacts with tidal currents.
From a bathymetric review, Tanjung Pelindu has the most consistent and steepest variation in depth compared to the others. With varying depths of 1-12 m (675 m), 12-34 m (692 m), 34-56 m (840 m), 56-78 m (770 m), and 78-100 m (791 m).
This consistency of steep depth greatly impacts the bottom friction coefficient, thereby increasing the attenuation rate of the tsunami waves. As a result, the waves that reached Tanjung Pelindu were the lowest among all three locations (3.67 m).
149
a) b) c)
Figure 4. Spatial distribution of wave propagation in Scenario 3 a) after 30 minutes, b) after 40 minutes, and c) after 50 minutes.
a) b) c)
Figure 5. Spatial distribution of wave propagation in Scenario 3 a) after 30 minutes, b) after 40 minutes, and c) after 50 minutes.
Figure 6. Comparison of the water level in Scenario 1, 2, 3, and 4 in Watu Ulo Beach
Figure 7. Comparison of the water level in Scenario 1, 2, 3, and 4 in Puger Beach
150
Figure 8. Comparison of water level in Scenarios 1, 2, 3 and 4 at Tanjung Pelindu Beach
a) b) c)
d) e) f)
Figure 9. Spatial distribution of waves at 3 observation locations at Watu Ulo Beach (figures a & b), Puger Beach (figures c & d), Tanjung Pelindu (figures e & f)
151
Table 4. Tsunami Simulation Results
Obs Point Scenario 1 Scenario 3 Scenario 4
minutes meters minutes meters minutes meters
Watu Ulo 39 7.1020 39 4.68786 39 5.32961
Puger 40 5.56016 40 3.13137 40 3.23394
Tj. Pelindu 48 3.3874 57 3.67682 57 2.97368
The results of modeling the tsunami and tides carried out simultaneously differ from modeling the tsunamis and tides independently and are carried out with a linear superposition of wave heights. In addition, tsunami waves are considered to be highly dependent on bathymetry and coastline configuration. Using a 2D numerical model with high resolution and carrying out tsunami and tide interactions simultaneously, the uncertainty of the impact of a tsunami at observation sites with strong tides and tsunamis can be reduced [19]. The research results do not become a general rule on the impact of the tsunami-tidal interaction. The two ports in San Diego Bay react differently to the same tsunami and tide. Likewise, Pillar Point Harbor and Crescent City Harbor show the influence of each port’s physical characteristics, such as bathymetry and existing infrastructure, as well as the strength of the tsunami and tidal signals [20].
Simulation Results in Observation Points
A summary of all scenarios in three observation locations is shown in Table 4, while discussions are presented after figures of time series from every observation point.
Each observation location has a different wave height and arrival time. Figure 9(a) is an overview of the observation locations for Watu Ulo Beach and Puger Beach, with the tsunami wave peak occurring at the 39th minute and Tanjung Pelindu at the 57th minute. The wave height is quite affected by the influence of the tides, even though the impact is still local [10]. In addition, considerable influence is also obtained from earthquake parameters such as earthquake magnitude, strike, dip, and slip. For several research locations, the bathymetry characteristics and coastal morphology also affect the height and impact of the tsunami waves. The observation site at Watu Ulo Beach has a bathymetric pattern that tends to be gentle and shallow waters with a depth of less than 1 m, while Tanjung Pelindu has a steep bathymetry pattern and deep water (depth of more than 24 m).
4. Conclusion
From the analysis of the three scenarios, the two observation locations experienced the maximum height of the wave amplitude when the tsunami occurred individually or in Scenario 1. The two locations, Watu Ulo Beach and Puger Beach, each got the highest elevation of 7.1 m in the 39th minute and 5.56 m in the 40th minute. Meanwhile, Tanjung Pelindu Beach experiences a maximum wave height when the tsunami interacts with the tidal phase in Scenario 3, with the highest elevation of 3.68 m in the 57th minute. In several tsunami incidents, the tidal waves are considered to have an impact on increasing the amplitude of the tsunami waves during high
tide so that they can accumulate wave heights that reach the coast.
From the results of this study, it can be concluded that the impact of the interaction of tsunami waves with tidal waves is very local, where each observation location gets a different influence from the interaction of the two tidal phases. The three observation locations have very varied beach slopes and depths that affect the difference in water surface elevation in each location.
More comprehensive research is needed on the factors that can affect the height of the tsunami waves that reach the coast, such as the accuracy of bathymetric data, the use of a smaller grid, the influence of coastal morphology, and the influence of tides.
Hopefully, the results of this study can be useful as a comparison of similar research in terms of tsunami modeling when interacting with tidal waves because the prediction of tsunami wave height at high and low tide can be used as a benchmark in preparing tsunami disaster mitigation measures in an area.
Acknowledgments
Authors express gratitude to DELTARES as the Delft3D software developer for providing an open license in this modeling and the Indonesian Geospatial Information Agency (BIG) for free national bathymetric and tidal data.
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