A PROTOTYPE OF WEB-APPLICATION FORTSUNAMI DATABASEALONG SOUTHERN JAVA ISLAND COASTLINE
Ariska Rudyanto∗
MEE07170

Supervisor: Yohei HASEGAWA∗∗
Yosuke IGARASHI∗∗
Yushiro FUJII∗∗∗
ABSTRACT

Development of tsunami database system along coastline area of southern Sumatra, Java and Bali
islands was presented in this study. This was performed in three stages, there are: (1) applying
tsunami numerical simulation; (2) constructing a database; and (3) retrieving tsunami heights andarrival times from the database for assembling tsunami warning message. First stage was conductedby employing TUNAMI-N2 and TTT software for 1 real case and 28 artificial cases (with 4 depths of
0, 20, 40 and 60 km; and 3 different magnitudes of 7.0, 7.5, and 8.0), to obtain tsunami heights andarrival times on 56 coastal points. The results of tsunami heights at the coasts were consideredapplying Green’s law at 50 m sea depth of forecast points. Then, a web application system using
Apache web server, MySQL relational database and PHP programming language, were used toperform the second and third stages. The tsunami database which was successfully constructed in thisstudy consists of 338 tables, and is divided into 3 parts: coastal point table, hypocenter table andsimulation data table. Relation between the tables in the database based on the primary key from eachtable is a ‘one to many’ type. The system retrieves tsunami heights and arrival times from thedatabase and assembles warning messages. For retrieving methods, simple and interpolation
techniques, are used. Lastly, it was found that the web application was effective for developing
tsunami warning system.

Keywords: Tsunami database, Numerical simulation, Web application.
INTRODUCTION
The occurrence of the Great Sumatra earthquake followed by a devastating tsunami which struck the
Indian Ocean region killing more than 230,000 peoples, has renewed Indonesian awareness of theimportance of tsunami countermeasures. In order to protect people from tsunami disaster, theIndonesian government launched a project of the Indonesian Tsunami Early Warning System(InaTEWS). The primary task of InaTEWS is to issue reliable tsunami warnings with minimum falsealarm. In order to support it, the development of a pre-calculated tsunami is very significant inissuance of the tsunami warning. According to it, the main objective of this study is to construct amodel of tsunami database. Secondary objective is to study the procedure of interpolation techniques
using retrieving methods from the database and its application in study area considering the occurrenceof tsunami in the future.

∗

Meteorological and Geophysical Agency (BMG), Indonesia∗∗

Japan Meteorological Agency (JMA), Japan∗∗∗

International Institute of Seismologi and Earthquake Engineering (IISEE), Building Research Institute (BRI),Japan

THEORY AND METHODOLOGY
Tsunami Numerical Simulation
The main purpose of tsunami simulation is to calculate the tsunami heights and its arrival times.
Tsunami are commonly referred as long waves, therefore, they are usually modeled mathematicallyusing a depth-averaged approximation of the Navier-Stokes equations referred as “shallow-water wave
theory”. In this study I use the shallow water theory with Coriolis effect and bottom friction omitted,
which are described by Satake (1995). This theory will be solved numerically by applying the leapfrog staggered finite difference method (Satake, 2002). I used the TUNAMI-N2 numerical simulation
software which was developed by Disaster Control Research Center of Tohoku University, Japan(Imamura, 2006) to obtain tsunami heights at the target points (forecast and coastal points). In thisstudy, the dimension of computation area was set as 901 grid points and 601 grid points for longitude
and latitude direction, respectively. This computation area covered study area from 5.0oS-15.0oS and
102.0oE-117.0oE. The time step of 0.5 s is set to satisfy the stability (CFL) condition. The total
calculation time was set to three hours for the completion of the simulation at all the coastal points. To
obtain tsunami arrival times I used Tsunami Travel Times (TTT) software which was originallydeveloped by Dr. Paul Wessel from Geoware (http://www.geoware-online.com). In this study I firstestimate tsunami heights at forecast points by tsunami simulation, then estimate tsunami heights atcoastal point by applying the Green’s law to them.
Bathymetry Data
In this study, I use bathymetry data from the General Bathymetric Chart of the Oceans (GEBCO) withresolution of 1 arc minute that is almost equal to 1850 m. The study area is shown in Figure 1 withsource points (SP), forecast points (FP) and coastal points (CP).

Figure 1. Bathymetry data of study area.
Red dots show the source points (30 points)
and green dots show forecast points (56points) and red triangles show coastal points(56 points). Star shows epicenter of the2006 Pangandaran tsunami. Each small
colored rectangle (light blue, blue, magenta,
yellow, red, orange and green) shows thearea indicating coastal block area.

Source Points
The source point is defined as a center of the fault that could generate tsunami. In this study, a realcase source point and artificial ones are used. For the real case, I use the 2006 Pangandaran tsunami(9.222oS, 107.320oE, Mw = 7.7 at 8:19:28 UTC according to USGS). According to the Global CMT
solution, the focal mechanism of main shock of earthquake shows strike = 289o, dip angle = 10o andslip angle = 95o. According to Fujii and Satake (2006), the source area is divided into 10 subfaults thatcover the aftershock area with the depth of 3 km in the shallow part and 11.7 km in the deep part. All
the subfaults have same parameters of focal mechanism with the mainshock.
For the artificial cases, I select 28 source points in the Indian Ocean in front of Java island. For
each source point, I use single segment which has the same assumption for fault parameter with strikeof 285o. For dip and slip angle, I considered the severest case for tsunami generation and set them to
45o and 90o, respectively. By using these data, I set the depths into 4 scenarios (0, 20, 40 and 60 km)
and magnitude into 3 scenarios (7, 7.5 and 8). Then, tsunami simulations were carried out for 337
cases in total including 336 artificial cases and 1 real case.
RESULT OF TSUNAMI SIMULATION
Based on the tsunami simulation results of 336 artificial cases and 1 real case using TUNAMI-N2
software, I will discuss several cases for the sample analysis.
Comparison of tsunami waveforms atcoastal area obtained from the simulation between
the real case and the nearest artificial source points
shows that the tsunami heights of the real casemostly equal to the artificial ones, and arrival times
are mostly earlier especially on the central Java
coasts. These phenomena appear to be due to thedifference of tsunami source area between two cases.
Tsunami source area of the real case mostly extends
to south-eastern part from the epicenter (mainshock) of the real case closely to the central Java
coasts like shown in Figure 2. Figure 2 also shows
the subsided area of initial sea level displacement of
the real case is huge in north-eastern direction, while
the subsided area of point I is small for the same
direction. This explanation is clarifying why the firstarrivals of tsunami for the real case in the central
Java coasts mostly subsided while the artificial one
is uplifted. Even with those differences inwaveforms between the real case and the artificial
Figure 2. Comparison of fault deformation case, there seems no fatal discrepancy in tsunami
areas between the artificial case of source heights, but more investigation is needed for arrival
point I (top) and the real case of the 2006 times. That indicates validity to use simple
rectangular fault model for the artificial cases
Pangandaran tsunami (bottom).
instead of using realistic but complicated fault
model to obtain tsunami heights.
Tsunami Height at CP from different FP

Figure 3 shows the comparison of thetsunami heights at coastal points which wereobtained by applying Green’s Law to thetsunami heights at different depth of forecast
points. Based on this graph, we can find thatthe tsunami heights obtained at coastal point
by applying Green’s law are almost the sameor do not vary significantly among different
bathymetry depths of forecast point. Therefore,
considering the complexity of coastal
bathymetry along the study area, I decided to Figure 3. Comparison of tsunami heights at coastal
use the sea depth of 50 m for forecast points in points obtained by applying Green’s law to thethe tsunami simulations.
heights at the forecast points with different depths(source point C with depth of 0 km and magnitudeof 8.0).
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Height (m)4Figure 4 shows the comparison of tsunami heights from the source point R. From this figure
we can see that the application of the Green’s law gives relatively higher tsunami heights at coasts thanthose directly obtained from tsunami simulation. But these results are relatively more stable than the
results obtained directly from tsunami simulation. This may be because of not so accurate sea depth
data of GEBCO near coasts and choose grid of 1 arc minute, since the complexity of bathymetry of theshallow coastal area could considerably affect the tsunami simulation. Although this result needs
further investigation, it gives us good judgement for application of Green’s law in the tsunami warning
scope.

Figure 4. Comparison of tsunami heights obtained directly from simulation and by applying
Green’s law to heights at FPs for source point R with the same depth and magnitude.

TSUNAMI DATABASE AND WARNING INFORMATION
For establishment of reliable and robust tsunami database, the selection of the database and systems
will be important. In this study I adopted a system for developing web application to construct tsunami
database and applied retrieve method to it. In this study I used Apache 2.2.8 for web server and
MySQL5.0.51 for relational database. PHP 5.2.5 was used in this study as middleware scripting
language to connect the server and the database.
Construction of DatabaseIn this study, the tsunami database which I
constructed consisted of 3 main parts: 1 coastal
point table (fp table), 1 hypocenter table (hyptable) and 336 simulation data tables. I also
constructed
severaltemporarytablesconsidering their applications to retrieve fromthe database. The architecture and relationshipbetween tables of this database are shown in
Figure 5. SQL commands were used to maketable structure and to insert the tsunami
simulation results into the tables.
Figure 5. Architecture of tsunami database.

Retrieving from Database
The next important step to perform database method is to explore how quickly and precisely retrieve
tsunami heights and arrival times from the database. In this study I used 2 methods namely simple andinterpolation method. These methods are performed by a combination of PHP scripting language and
SQL syntax commands. PHP scripting language chooses the most appropriate data from databasewhich match the real earthquake. This combination also makes earthquake and tsunami information
message.
Simple method seeks simulation data whose epicenter is located in the nearest horizontal
distance to the real earthquake. As for magnitude and depth, this method uses the closest element for
outputs. For arrival times, considering the tsunami warning, this method will seek the arrival times
from the nearest element to the hypocenter.
To apply the interpolation method, firstly the four cases surrounding the epicenter of the realearthquake will be searched in the database. Each case has 2 different magnitudes and 2 different
depths. Totally there exist 16 cases used for the interpolation. In order to obtain tsunami heights for theactual hypocenter, the linear method will be used in horizontal interpolation for 4 cases surrounding
the hypocenter. I performed logarithm method to obtain coefficients for magnitude and depth
interpolations following the JMA’s rules. For estimation of arrival times of tsunami at coastal area, themethod will seek the earliest case among the data which were used for the interpolation.
Tsunami Warning Information
Based on JMA (2007), in this study the tsunami
warning messages are divided into 3 stages of
warning. The first warning message consists of data
about the recent earthquake that occurred and theearliest arrival time and the highest tsunami height ateach estimated coastal block which will be affected.
Besides this the information in the warning also
includes criteria of warning for each coastal blockand name list of the coastal area affected withincoastal blocks. The second warning message clarifies
the details of arrival time and tsunami height at eachcoastal area within coastal block which were affected.
The third warning message is about cancellation oftsunami warning information or downgrading or
upgrading on the coastal blocks warning criteria. In
this study, tsunami warning message was developedby utilizing PHP scripting language integrated withthe application of retrieving method in the web
application framework. The flowchart of web
application used in this study is shown in Figure 6.

Figure 6. Flowchart of web application.
CONCLUSIONSIn this study, a prototype of tsunami database developed and retrieving methods were used for web
application. The source points in the study area are combinations of 1 real case (The 2006
Pangandaran tsunami) and 28 artificial cases with 4 different depths and 3 different magnitudes

(totally 337 cases). I considered tectonics setting of study area and the severest case of tsunami
occurrence for initial conditions for numerical tsunami simulation.
The tsunami simulation was conducted by using TUNAMI-N2 numerical simulation softwarefrom DCRC and TTT software from Geoware. From these simulations I obtained the tsunami heights
and estimated arrival times at target points along the study area which consist of 56 forecast and 56
coastal points. I investigated the exact location of forecast points in the offshore area for applying
Green’s law, and I decided to locate the forecast points in the 50 m depth of bathymetry in the ocean infront of coastal points.
Tsunami simulation result shows that comparison of tsunami waveforms between the real caseand the artificial case closest to it had a strong similarity in tsunami heights, but had differences inarrival times due to the differences of fault deformation area for the two cases. Also I foundconsistency between the tsunami heights at the coast obtained by applying the Green’s law and thoseobtained directly from tsunami simulation. These results show that the setting of artificial cases is
acceptable for constructing tsunami database.
Then, the results of tsunami simulation were stored in the database by utilizing web
application system. This system consists of Apache 2.2.8 for web server, MySQL 5.0.51 for relational
database and PHP 5.2.5 for middleware scripting language. The tsunami database which was
successfully constructed in this study consists of 337 tables, and is divided into 3 parts: coastal point
table, hypocenter table and simulation data table. Relation between tables in the database based on the
primary key from each table has type of ‘one to many’. Here, I also succeeded in applying theretrieving method to search the data from the database. The methods I used are simple andinterpolation. These methods are easy to apply, but are not so precise due to the lack of bathymetry
data I used. So, the accuracy of tsunami heights and arrival times should be increased by using finerbathymetry data. The next stage in this study was to assemble tsunami warning message. The design oftsunami warning message also must be simple and apprehensible by people. Although, I couldn’t
finish to completing all the tsunami warning message perfectly like the format I designed, this study
verified the ability of web application system for developing tsunami warning system. However, there
are still needs for further research and improvement to increase utilizing the web application intsunami warning system.
ACKNOWLEDGEMENT
I wish to express my great appreciation to Dr. B. Shibazaki as Tsunami Course Leader for his guidance,
discussions and suggestions during my study in Japan.
REFERENCES
Fujii, Y., and. Satake K., 2006, Source of the July 2006 West Java tsunami estimated from tide gauge
records, Geophysical Research Letter, 33, L24317, doi:10.1029/2006GL028049.
Imamura, F., Yalciner, A.C., Ozyurt, G., 2006 Revision, Tsunami Modeling Manual, DCRC (Disaster
Control Research Center), Tohuku University.
JMA (Japan Meteorological Agency), 2007 Edition, Draft of Manual on Operation Systems for
Tsunami Warning Service.
Satake, K., 1995, Linear and nonlinear computations of the 1992 Nicaragua earthquake tsunami, Pureand Appl. Geophys., 144, 455-470.
Satake, K., 2002, International Handbook of Earthquake & Engineering Seismology: Tsunamis,
Academic Press, 437-451.