DEVELOPMENT OF A COMPREHENSIVE DISASTERSCENARIO SIMULATOR THAT CONSIDERS THE TIMEFRAME OF THE DISASTER

Noriyuki Kuwasawa1, Toshitaka Katada2 and Masanobu Kanai3
Abstract: In order to execute effective disaster mitigation measures it is necessary to examine various
problems such as; damage assumption, warning transmission strategy, and evacuation plan, etc. The purposeof this study is to develop a Comprehensive Disaster Scenario Simulator that expresses a regional situation
during a disaster in order to manage these problems. This simulator expresses resident's activities during
normal circumstances and their behavior during a disaster. The simulator also expresses the extent of damage,and number of casualties during the time of occurrence of the disaster. Therefore, the use of this simulator canbe twofold; i. as a strategic tool for examining effective disaster prevention measures. ii. due to its visualpresentation and easy-to-use interface, this simulator can be used as a risk communication tool to inform
about the various characteristics of the disaster and the appropriate actions that should be taken to reduce theimpact of disasters.
Keywords: Disaster prevention measure, Damage Assessment, Risk Communication, Scenario Simulator

1. INTRODUCTION
Recently, in 2004 disasters such as Typhoon No.23
which occurred in October resulted in extensive damage
from storm centering in Kinki and Shikoku, and the
Niigata-Chuetsu Earthquake in Japan claimed more than 50
lives. In addition, the Sumatra earthquake that occurred inIndonesia in 2004 killed more than 200,000 people inneighboring countries due to the occurrence of a tsunami.
Lately, disasters that exceed current estimated scale havebeen occurring frequently.
In our country that is vulnerable to a number of hazards,
it is important to implement effective measures for
reducing the impact of hazards on the society. However,municipalities that actually accomplish disaster mitigation
measures are being pressed to maintain several disasterprevention facilities such as; embankments, warningfacilities, evacuation roads, shelter facilities, as well as, toestimate damage assumptions of disaster scenario anddisaster prevention plans etc. On the other hand, it isnecessary to carry out disaster educational activities inorder to improve the resident’s disaster prevention
consideration. In that regard, measures that should be

examined for regional disaster prevention are numerous
and are constrained by limited budget and time.
In this study, we recognized the usefulness of thesimulation technology in aiding with disaster prevention
problems, and therefore we developed the simulation
model to express local conditions based on various
scenario assumptions including the generation time of thedisaster. The simulation model expresses the disasterprogression and resident’s activity during normal
circumstances and evacuation behavior during a disaster,and estimates impact based on these factors. Therefore, this
scenario simulator can predict extent of damage by
considering the activity being carried out by the residents
in the target city area. Moreover, this simulation model was
implemented by using the Object-Oriented Programming
Language (OOPL), and a system that considers the type ofactivity being undertaken was developed.
This paper discusses details of the simulation model that
expresses disaster behavior and resident’s activity and how
the simulation system utilizes this information. Moreover,effectiveness of this simulator as a disaster prevention
strategy and a risk communication tool was shown byshowing the execution process of damage scenario
assumptions using this simulator.

1) Member of JSCE, Dr. Eng., Researcher, Institute of Social Technology(Frontier Building 2F, 1-12-16, Kataoka-cho, Takasaki, Gunma, 370-0862, Japan, E-mail: kuwasawa@ce.gunma-u.ac.jp)
2) Member of JSCE, Dr. Eng., Professor, Department of Civil and Environmental Engineering, Gunma University3) Member of JSCE, Dr. Eng., Assistant Professor, Department of Civil and Environmental Engineering, Gunma University

2. UTILITY OF SCENARIO SIMULATOR IN
DISASTER MEASURES(1) Problems Identified in Disaster Measuresa) Problems Concerning Damage Assumption
It is important to grasp damage scale and generation
patterns of the disaster that occurred in order to implement
effective disaster measures. For instance, the special
investigation committee for Tonankai-Nankai earthquake ispart of the Central Disaster Management Council which is
a committee responsible for planning disaster prevention
measures for the Tonankai-Nankai earthquake, and it has
detailed information of seismic intensities for various
places, the circumstances of a tsunami, and the likely levelof damage that is possible1). Moreover, some municipalities
have predicted possible damage levels for various disasters
such as flood, tsunami, and nuclear plants etc2).
It is important to predict human casualties by scenario
simulations in order to reduce human suffering due to adisaster, and to examine appropriate responses. It isbelieved that the scale and pattern of human suffering due
to a disaster is greatly dependent on the resident’s location,
the activity being undertaken at the occurrence of thedisaster and the characteristics of the disaster. Therefore, itis prudent to examine scenarios that consider residents
action such as residents activity when the disaster occurs,
their evacuation behavior in addition to predicting thecharacteristic of the disaster phenomenon in order to planadequate disaster prevention measures suitable for thetarget region. Many municipalities have analyzed disasterphenomenon in detail, but residents’ action has not been
examined sufficiently. Moreover, the examination ofresidents only consisted of estimating total population in
the area from statistical records, and doesn’t consider therange of activities being carried out by individuals at
generation time of the disaster.
b) Measures Requested for Disaster Education
An attempt to improve awareness of disasters throughthe distribution of hazard maps and by conducting disasterprevention lecture meetings is encouraged for disastereducation. However, many tsunami and flood
investigations have revealed that recently evacuation rateof resident is declining3),4). Therefore, even if effective
evacuation plans are designed, problems can still arise fromthe residents’ perspective.
The main reason why residents tend not to evacuate is
because they often fail to recognize their level ofvulnerability during a disaster, and as such they do notthink it is necessary to evacuate. It is believed that these

problems tend to occur because resident perception of thedisaster is inaccurate due to lack of knowledge of thedisaster because of a lack of experience, incorrectknowledge based on past disaster experience and legend,and psychology characteristic under non-daily situation5).
Therefore, there is a need for an effective disastereducation program to solve these problems.
(2) Utility of Comprehensive Scenario Simulator
There are some researchers6),7),8) that have focused on
aspects/issues such as resident’s evacuation behavior andwarning transmission in terms of the predicted disaster
scenario. Generally, however, many of these researchers
did not examine a series of events seen during a disastersuch as hazard characteristics, warning transmission, andresident’s evacuation behavior, etc. Certainly, there is aneed to examine separately the issue of improving
efficiency in resident’s evacuation and warningtransmission. However, there are many limitations that canbe highlighted for the first time by analyzing therelationship between disaster phenomenon and social
circumstances that vary with differences in time series. For
example, would there be an increase in damage due to thedelay of warning and evacuation behavior? The impact of
this relationship is far more important than an individual
event being compared by total damage scale. In addition, it
is important not only to consider resident’s behavior during
the disaster but also their daily activities in order toestimate potential damage especially since some hazards
tend to occur during unexpected times with little or no
warning such as the occurrence of an earthquake. In lightof the above, we believe that a scenario simulator that is
capable of expressing two or more events such as a city’s
daily activities and disaster phenomena is much more
useful for disaster management planning purposes.
Moreover, we believe that the simulator is effective in
helping residents to recognize that disaster phenomena arecapable of changing greatly from scenario to scenario andthat damage can be kept to a minimum if adequate response
action is employed. A scenario simulator that expresses
various situations during a disaster can be considered as adynamic hazard map. The dynamic hazard map can express
various results such as; disaster phenomenon that
progresses with passage of time and scale of damage due todifferences in social response which can be displayed
visually and plainly. From this viewpoint, thecomprehensive disaster scenario simulator is useful as arisk communication tool that plainly explains the disasterrisk and disaster measures, and can effectively inform
about an appropriate response action during a disaster.

3. OUTLINE OF SIMULATION MODEL
This chapter outlines the simulation model which is thecore of this simulator.
(1) Features and Development Policy of the Model
This model is capable of illustrating damage related to
the generation time of the disaster, the resident’s activity
during normal circumstances and during a disasteroccurrence etc. Moreover, the model was developed basedon the following policies in consideration of generality andextendibility:
・ To express residents ’ action based on individual
attributes such as; age, sex, disability, etc. The
simulator expresses residents as individual units.
・ This simulator does not express time by using theelapsed time method but rather using normal time of
day to express daily activities and disaster scenario.
・ The results of previous calculation by other programs
are used for expressing the changes in the progressionof the disaster (tsunami and flood) in order to improve
efficiency.
・ The function is to reproduce population characteristics
from statistical information so that resident informationin the model correspond with existing population data
for the area.
・ GIS data is used to express geographical space such as
altitude, road, building etc of the target area.
・ Census9) and housing map data, etc, which is available
on a nationwide scale was used for regions where
various data is not available.
(2) Flow of Model
This section discusses the outline of each processaccording to the flow of the simulation model depicted inFig. 1. Part: c), d), e), f). The flow is expressed by
improving the Comprehensive Tsunami Scenario
Simulator10) that the authors had previously developed.
a) Expression of Population
Initially, families and residents in the target region are
expressed by using census information about the resident
population, such as; sex, age, family structure, worker,
student etc, so that the population information in the model
replicate the existing resident population in the area. To put
it more concretely, residents were first grouped using theattributes of sex and age. Secondly, families werereproduced based on: family size, type (alone, a couple,
couple and children etc.), and the average number of eachfamily type that exists in order to reproduce the type offamily structure that exists in the target area. Residents
were then allocated into family using attributes of; familya) Expression of Population- Family: House, Family type structure)- Residents: Age, Sex, Occupation (Worker / Student), Office / Schoolb) Expression of Activities in Normal Circumstances- Distribution of population that it was considered the time of day.
c) Expression of Disaster- Change in the extent of the impactd) Expression of Warning Transmission- Loudspeaker, Patrol car, Mass media- Oral and telephone communication> Reception situation of warninge) Expression of Evacuation Behavior- Decision making - Evacuation behavior> Evacuation arrival, Resident’s distributionf) Expression of Damage- Human casualties - Building damage> Number of casualties, Number of collapsed buildings

Fig. 1 Outline of Simulation Modeltype, average age of the head of the household etc. The
program was then used to extract each family’s house at
random from the housing map; however, the selection ofcommercial buildings was not done on a random basis.
Thirdly, resident’s occupation i.e. worker, student, andother was obtained from statistical information. In addition,
residents’ place of work or learning was identified as being
located at home, inside the region, or outside the region
based on statistical information. In addition, statisticalinformation was used to express residents (workers andstudents) who commute to the area from outside the region
from.
b) Expression of Activities in Normal Circumstances
A city activity during normal circumstances can be
expressed by the daily activities of individuals in that
region. Traffic movement is dependent upon resident’s
occupation which is chiefly influenced by the daily
activities of residents. This model expresses resident’s
traffic behavior by five types of traffic: commuter, student,
business, private, and through traffic.
First of all, the commuter traffic shows how employedindividuals’ shuttle from home and work. The commuter
traffic refers to information on the location of the office i.e.
whether it is inside or outside the region. Using the housing
map, the program randomly selects commercial buildings
for workers who are employed in the city. The floor spaceof each commercial building was used to indicate thenumber of employees, since there is a relationship between

number of employees and size of floor space. Moreover,for persons who commute to the suburbs, edge points on
the road network were treated as temporary offices, and an
office was selected at random from these points. Because
generation timing of the commuter traffic is controlled, thedistribution time of commuting to work and the total
working hours can be arbitrarily set in this model.
The student traffic shows how students shuttle fromhome and school. For elementary and junior high school
students who attend school in the city, the school isselected by age and school district. On the other hand, forhigh school students, the school is selected at random in theregion. Moreover, generation timing of student traffic is
controlled according to parameters that relate to
distribution timing of commuting to and from school.
The business traffic refers to personnel trips that involvecommuting from the office to another building and back to
the office or home in the target region. The private trafficrefers to travel by which residents other than workers andstudents shuttle from home and other buildings. To control
this traffic, this model uses parameters that decide a traffic
generation probability according to; time of day, durationin destination, and travel frequency of each resident during
the day and the floor space of buildings is used as anindicator of the number of visitors.
Finally, through traffic refers to the commuting ofresidents from other areas that pass through the target
region. This model developed traffic generation
probabilities based on time and the ratio of people that
visits building in the target region as a parameter forthrough traffic.
This model has many traffic parameters but many ofthese parameters were obtained from the person trip survey.
c) Expression of Disaster
This process expresses change in the extent of the impact
of disaster and development due to the progress of time.
Currently, an inundation situation due to tsunami and flood
occurrence can be considered in this model. An inundation
analysis is not calculated by this simulation model but it iscalculated beforehand by another program, because aninundation analysis requires a long time to computeinundation information and up to several days to determine
the range and accuracy of the data. Inundation analysis is
not influenced by external factors such as warning timing
or evacuation behavior etc.
d) Expression of Warning Transmission
The warning transmission module models both official(“broadcast”) and informal (“contagion”) processes. The
informal network (person-to-person oral communications)is the primary method of warning transmission, since
official warnings (processed by government authorities andtransmitted by loudspeakers, route alert vehicles, radio, andTV) are relatively slow in responding to disasters.
The simulation model for information dissemination thatwas previously developed by Katada et. al8),11),12) is used toexpress warning transmission. This model can calculate
warning transmission situation for example, warning
reception timing for each resident etc. by setting up
parameters for each warning facility.
e) Expression of Evacuation Behavior
Resident’s evacuation behavior consists of two parts; i.
expression of decision making related to evacuation, and ii.
expression of action to when evacuee moves to shelter. For
this model, every elapsed time can be set as a parameterthat controls evacuation timing. Moreover, this model canset destination and speed for each individual. Evacuee’s
arrival and resident’s distribution for each elapsed time isexpressed in this process.
f) Expression of Damage
This process expresses the situation of human casualties
and housing damage due to the condition of the hazard andresident’s evacuation status. In other words, residents andbuildings that have received damage are extracted from therange of inundation and distribution of residents andbuildings, in order to calculate the extent of damage which
is determined by the fluid power of the inundation. This
process output is total casualty and occurrence timing ofeach casualty, location of casualty and damaged buildings.
4. DEVELOPMENT OF SIMULATION SYSTEM
This simulator is expected to be used as a disastermanagement tool by the disaster manager officials, andsecondly as a risk communication tool by residents.
Therefore, an interface to execute the simulation for theuser and to clearly display the calculation result is
indispensable. This chapter discusses the method of
implementing this simulation model and the details of thesimulation system.
(1) Implementation
This paragraph describes the framework and theimplementing method of the simulation model that
expresses space and time.
a) Expression of SpaceThis simulator considers three basic elements that
express object region; the first element is a geographicalfeature that expresses elevation, river and coast etc., thesecond element expresses buildings such as houses,shelters, and the third element expresses road networks
used when undertaking daily activities and evacuation.
Additionally, this simulator expresses spatial features bybuilding elements that express warning transmission
facilities, such as loudspeakers, patrol cars, evacuation
facilities, disasters such as tsunami and flood, anddetermining the condition of the hazard.
In this simulator, elements are modeled using points,
lines, and polygons to represent the actual shapes. Eachfigure has coordinate values based on a geographic
coordinate system, and can calculate the location of eachelement in space and the real distance between elements. In
addition, this simulator can execute a spatial retrieval bylocation attributes like in GIS. Hence, this simulator canrequest household data that exists in the audible area ofloudspeakers from a distance between two points, locate
the nearest shelter by network path finding algorithm, andestimate casualties from the inundation region anddistribution of evacuees.
b) Expression of Time
This simulator expresses events such as “resident
realization that an earthquake has occurred” and “resident
receipt of warnings from a patrol car”. This exchange of
information is called a ‘message’ which takes place
between elements. For instance, when an earthquake occurs,
the earthquake element sends a message to resident’s
elements to indicate the occurrence of an earthquake. A
patrol car extracts the surrounding resident element by
spatial retrieval, and a message is sent to indicate awarning transmission. Moreover, this simulator can specify
generation time of each event such as, “depart home at
7:30am for school”. Residents’ element expresses asituation in which the resident element travels on road anda message with time lag is sent to oneself.
Such a mechanism has been achieved by manipulating
the system that controls communication messages based ontime between elements. This system arranges the order oftransmitting the message by using Priority Queue. In
addition, this system transmits the ‘message’ to an element
according to the elapsed time of the simulation. The
simulator explains the process by which each element
functions through the use of such a mechanism according
to passage of time.
c) Implementation in Program Language
We used object-oriented programming language inbuilding the simulator. In addition, we identified
abstraction classes that contain a common function to allelements, for example, the function that a message was sent
and received etc. Then we derived the abstraction class

CommonRoad

Mass media

SpatialTsunamiEarthquake

Location

Elevation

Building

Shelter

Loudspeaker

Movement

Resident

WorkerPatrol Car

Student

Abstract Class
Element Class

Fig. 2 Hierarchical Structure of Simulation Classes
InterfaceGUI
Program

CUI
ProgramScenario
Setting

Rendering
ProgramSimulation
ProgramHazardDB

Data Flow

Fig. 3 Configure of Simulation Systemwith functions of element group, and are describing classthat finally expresses each element (Fig. 2).
In each element class expression of action (i.e. go toschool, warning transmission, evacuation) according to theelement’s role in each event is triggered by the receipt of amessage. The entire simulation model is shown as
operating as an element generating the events of each other.
However, we calculated beforehand some elements that
represented a disaster phenomena such as a tsunami andflood, because it takes a very long time to calculate, and it
is unaffected by other elements. Therefore, only theinterface of the database, which results from the calculation,is implemented for these element classes.
(2) Development of Systema) System Components
Fig. 3 shows the configuration of this simulator. This
simulator is composed of three programs; simulation,
rendering, and interface program.
Firstly, the simulation program is a mounting part of thesimulation model explained in foregone paragraphs. To
make the simulation program correspond to two or moreinterfaces, the simulation program was separated from theinterface. This program reads the condition from theconfiguration file, and calculates the simulation. Moreover,the program expresses the progress of the disaster andrefers to the database that accumulates inundation analysis

Tool Bar

Main Map

Layer and Legend List

Information

Index Map

Menu Bar

Update Interval

Event Message

Time Line

Fig. 4 Screenshot of Simulation System
when executing the simulation. Secondly, the rendering
program displays the calculation results of the simulation
program that is, the resident’s distribution, disasterbehavior, and hazard impact on the base map. Finally, we
created two types of programs; Graphical User Interface(GUI) and Character-based User Interface (CUI) as theinterface program. The GUI program visually displays theresults of the calculation of the simulation program byusing the rendering program. Moreover, this programprovides an interface to edit the scenario configuration file,and can visually control the scenario. On the other hand,
the CUI program can control the scenario by using thecommand line interface. Using the CUI program two or
more scenarios can be calculated at once. It is necessary to
execute many scenarios that change various parameters inorder to discover the best option. By calculating two or
more scenarios at once it helps to ensure efficiency andrapid results.
b) Interface
Fig. 4 shows the main window of this simulator. In theupper part of the screen, there is a menu bar and a toolbar
to operate each function of this simulator such as; scenario
setting and to begin the simulation. The function to operate
the main map screen is similar to general GIS software andcan be accessed from the toolbar such as to: change map

scale and change display area. In addition, from the toolbar
it is also possible to start and stop the simulation.
Next, there is an index map located in the upper left
hand corner of the screen that shows the extent of theregion and the area of the main map on the screen. The left
hand side of the screenshot simulation system contains
both the layer list and the legend. The layer list contains thelist of layers which are displayed on the main map, and thelegend contains the various symbols used on the map.
Using the layer list we can choose to display or not todisplay various layers and to change symbols on the map.
The Time Line and event message are located at the bottomof the main map. The Time Line displays the icons thatshow the occurrence time of the disaster and thetransmission of evacuation order etc. By dragging this icon
the generation timing of events can be changed, therefore
confirming the relationship that exists between elapsed
time and occurrence of other events. Also, when executing
the simulation model, the simulation time is displayed
below the time line. On the lower left side of the screenshot
is the controller which is used to confirm the simulation
time by numeric characters, and to set update intervals forthe main map.
Finally, the progress of the results of the simulation suchas; warning transmission, evacuation and extent of impact

is displayed on the right side of the screen as textual
information. Using tab control, this part can be switchedand can be changed to interface to visually set the scenario.

Shelter
Loudspeaker
Patrol Car RouteRoad
Height5. APPLYING THE SIMULATOR TO OWASE CITYThis chapter discusses the Input and Output data and theapplication of the simulator in a tsunami prone area.
(1) Applied Region
Owase City is a mid-sized coastal community in Japan,(population 23,000; area 193 km2) along the Pacificcoastline (Fig. 5). Approximately 90% of the area is steep,
mountainous terrain, with 80% of the population residingin the vicinity of Owase’s port. Due to the rugged nature of
the coastline the occurrence of a tsunami locally is
amplified therefore resulting in the community being
affected by several tsunami events in the past. For example,
the 1944 Tounankai and the 1946 Nankai tsunamis wereboth generated along the Nankai Trough Seismogenic Zone,
approximately 150 km offshore from Owase. On the other
hand, if a similar event were to occur in the future, such asa 7m-high tsunami this could possibly hit the city within 20
minutes of the occurrence of the earthquake.
(2) Input Data
Table 1 shows input data made for Owase City, and Fig.
5 shows the location of various facilities. The data
concerning building, road and elevation was created byprocessing and referring to the digital housing map and thelaser profiler data. Then, warning and evacuation facilities
were made utilizing the information etc. obtained from
Owase city office. Within the region, areas above 30 meters
sea level or higher were designated as an evacuation site
because residents are expected to evacuate to public
shelters and other areas that are on high ground. Moreover,
we prepared the tsunami inundation data using four
patterns that changed with the presence of breakwater andearthquake scale (Table 2). This data consists of
information on the wave height and the flow velocity of thetsunami every ten seconds with an accuracy of 12.5 meter
mesh. Finally, the population was reproduced using thefunction of this simulator from the statistical information
obtained from the Census data. Because the target region is
not the complete area for Owase city, other statistics suchas worker and student population were required forcomparison between the total population of Owase Cityand the population of the target region.
(3) Scenario Setting
For the scenario setting, we set three possible times forthe generation of an earthquake (i.e. 4:00am, 8:00am andSea, River

Breakwater

0

0.5

1

2

km

Fig. 5 Owase City
Table 1 Input Data
Category
Spatial Info.

Warningtransmission
facility
Evacuation
facility
HazardItem
Building
Road
Elevation
Loudspeaker
Patrol Car

3

Shelter

24

Height103
4patterns
7,974
18,5202,203

TsunamiPopulation*

Amount12,922176 km
6m mesh42

Household
Resident
Inflow Pop.

Reference
Digital housing map
Laser Profiler
Owase disasterprevention plan13)
Owase disasterprevention plan
Elevation
Central disastermanagement council14)
H12 Census9),
Owase disasterprevention plan

*Presumption result with this simulator.

Table 2 Scenario Patterns of Tsunami Hazard
No.

Type of earthquake

Breakwater

1

Tonankai-Nankai earthquake

With

2

Tonankai-Nankai earthquake

Without3

Sumatra earthquake class*

With

4

Sumatra earthquake class*Without*To assume the tsunami due to Sumatra earthquake in December 2004, fault
displacement of Tonankai-nankai earthquake was increased by factor of 1.5.

noon/midday). At 4:00am many residents are at home. At
8:00am many residents are commuting and at noon many
residents are not at home. The transmission scenario for an
evacuation order has two patterns; evacuation orders aretransmitted three minutes or ten minutes after anearthquake occurrence. Finally, for the evacuation scenario,
we have four patterns; 5 and 10 minutes after an evacuation
order is received, and 5 and 10 minutes after the earthquake
has occurred. Table 3 shows the above-mentioned scenario
patterns, and a common condition is shown in Table 4. In
this application, only damages resulting from the impact of
the tsunami are considered, damages due to the earthquake
are not considered. A Monte-Carlo simulation of 20 trials

Evacuation
TimingType:

20

Scenario patterns
4:00am, 8:00am, noon
Four pattern shown as Table 2
Three minutes after the earthquake,
Ten minutes after the earthquake
Five minutes after an order is received,
Ten minutes after an order is received,
Five minutes after the earthquake has occurred,
Ten minutes after the earthquake has occurred

Population (thousand)

Item
Earthquake
TimingTsunamiEvacuation
OrdersWorkerStudent

Free

TravelTotal

Stay-at-home

18

100
90

8

80

6

70

4

60

2

50

0

4:00am

8:00am40

noon

Stay-at-home percentage(%)

Table 3 Scenario Patterns

Fig. 6 Population and Stay-at-home Percentage

Table 4 Common Condition
Resident

Loudspeaker

Patrol Car

Item
Telephonecommunication
Evacuation speed
Shelter
Audible area,
ratingTransmission
timingAudible area,
ratingSpeed
Start timing

Mass media

Audience rating
Transmission
timingCondition
Not available
80 meter/minute
Nearest shelter
250 meter, 30 %Immediately after
official announcement
100 meter, 40 %20 kilometer/hour
Immediately after
official announcement
60 %Five minutes after
official announcement

was conducted and average values were compiled.
(4) Results of Simulationa) Transition of Population
First of all, we determined resident’s activity during theoccurrence time of each earthquake. Fig. 6 shows the
population and the percentage of the population that stays
at-home at each time, and Fig. 7 shows the distribution of
population at each time. From these figures it can beconcluded that at 4:00am, the stay at home-percentage isalmost 100 % with just a few workers existing. At 8:00am
there is an increase in worker and student population,
however, about 80 % stay at home. At 8:00am
approximately 1,000 people (workers and students) aretraveling. At noon there are about 9,000 workers, 2,500
students, and 600 free activity people (neither going towork or school). At this time, the stay at home-percentage
is approximately 45 %, in other words more than half of thestay at home resident has gone out. The distribution of the
population at noon shows that many residents are
distributed in the urban area which infers that theconcentration region of the population compared withnighttime has changed. Moreover, the population has
increased from approximately 18,500 to 20,000 people

Home

WorkerStudent

Business Trip

Free Trip

ThroughFig. 7 Distribution of Populationfrom 4:00am to noon. Therefore, the inflow of population
to this region during the daytime is more than a thousand
during the nighttime.
b) Result of Warning Transmission and Evacuation
We examined reception rate/time of evacuation order andevacuation circumstances of each scenario. The result foreach time is summarized in Table 5. In this case, we
assumed that all residents who received the evacuation
order evacuated so as to ascertain the effect of information
timing and evacuation timing on residents.
Fist of all, a remarkable trend is not observed from theorders reception rate which shows the ratio of residents
who received the evacuation order. However, orders

Time
Order Reception Rate (%)
Order Reception Time (min.)Evacuation Time (min.)

4am
97.6
3.4
4.5

8am
97.0
4.0
4.7

noon
97.2
4.6
4.8

Table 6 Evacuation Completion Time
Evacuation Time (min.)
Order Timing(after earthquake)

TimeEvacuation Start
Timing (min.)
4am
8am
noon

-

3 min.

After
Earthquake
510
9.5 14.5
9.7 14.7
9.8 14.8

10 min.

After Order is Received
5
14.0
14.8
16.1

10
19.0
19.8
21.1

5
21.0
21.9
23.1

10
26.0
26.8
28.1

Table 7 Number of Casualties
Number of casualties-

Evacuation Start
Timing (min.)After
Earthquake
5
10

Time

Order Timing(after earthquake)

4am
8am
noon

3 min.

10 min.

After Order is Received
5

10

5

10

0

40

85

305

530

1,440

4

174

309

552

867

1,651

0

393

645

967

1,292

1,935

reception time which indicates the average time that willpass before residents receive the evacuation order has
slowed when approaching noon and the distribution of
population during the daytime tends to require more time totransmit information. Also, evacuation time tends toslowdown when approaching noon and it can be assumed
that this is due to the fact that distance from the shelter
during the daytime is greater than at other times. Table 6
shows the evacuation completion time which was
calculated in consideration of the above-mentioned factors
and each scenario condition. The time indicated in the table
is the elapsed time from the occurrence of the earthquake.
According to the table, ten minutes are required tocomplete evacuation safely when evacuation begins fiveminutes after the earthquake. On the other hand, 26 to 28
minutes are required to safely complete evacuation whenboth evacuation order transmission and evacuation aredelayed.
c) Result of Human Impact
Finally, we will discuss the impact on humans for eachscenario. Table 7 shows the total casualty for the tsunamithat resulted from the Tonankai-Nankai earthquake inrelation to the presence of breakwater. According to thetable, when an evacuation order is announced three minutes
after the earthquake, and residents evacuate five minutes

Number of casualties (thousand)Table 5 Result of Warning Transmission and Evacuation

3.0
2.5
2.0
1.5

Time
noon
8am
4am

(Common scenario)
Warning Timing:
3 min. after the earthquake
Evacuation Timing:
5 min. after order is received

1.0
0.5
0.0

With
breakwaterWithout
breakwaterWith
breakwaterWithout
breakwater

Tonankai-Nankai earthquake
Sumatra class earthquake
Tsunami Scenario PatternFig. 8 Casualty Toll of Each Tsunami Scenario
after they receive the information, there is a difference ofseven times or more in the total number of casualties that
occurs when compared with the generation time of theearthquake for 4:00am and noon. It is believed that changes
in the distribution of the population in the inundation
region and changes in the evacuation completion time
influences these results. Furthermore, when evacuation
begins ten minutes after information reception, casualty
tolls for an earthquake which occurred at 4:00am are 305
people. Therefore, the number of casualties increases byapproximately 200 people when resident’s evacuation
behavior is delayed by five minutes. On the other hand,when the evacuation order is announced ten minutes
following an earthquake occurrence which was generated
at noon, the number of casualties is about 20 times the
scenario simulated for an earthquake occurrence at 4:00am,
evacuation order time announced 3 minutes following theearthquake and evacuation commencing 5 minutes after thewarning was received. On the other hand, the casualty tollranges from 0 to a few people in the scenario whereresidents take evacuation in five minutes following anearthquake. This result suggests that damage can besuppressed to a minimum if evacuation is undertaken
promptly.
Fig. 8 shows changes in the casualty toll of each tsunami
scenario. In this simulation, we assumed that theevacuation order is announced three minutes after theearthquake, and evacuation begins five minutes after orderis received. The result shows that the casualty toll of theSumatra Class Tsunami is four times that of the tsunami
from Tonankai-Nankai earthquake. Moreover, the numberof casualties decreases to 70 percent due to the presence ofa breakwater in the case of the Tonankai-Nankai
earthquake tsunami confirming the importance of the
breakwater. However, in the case of the Sumatra class
earthquake tsunami the presence of the breakwater had the
opposite result.

inundation area to the southern part because the breakwater
is located in the northern part of the coast (Fig. 5) and assuch it will deflect the tsunami waves to the southern part
resulting in the possibility of increased damages.
6. APPLICATION AS A DISASTER EDUCATION
TOOL

Fig. 9 Distribution of Casualties
Fig. 9 shows the distribution of total number ofcasualties for each tsunami scenario at noon. In this figure,many of the casualties occurred around the vicinity of thecoast on the north side of the Tonankai-Nankai earthquake
tsunami that had breakwater. On the other hand, in the caseof the Sumatra class tsunami, casualties are distributed
over the entire coast, and casualties are generated even in
the vicinity of the railway especially on the north side of
the river (Fig. 9 iii A). In order to examine the extent of
human impact due to the presence or absence of breakwater,
the images labeled iii and iv are compared. In image iii,
due to the presence of a breakwater, casualties have been
generated within a wide range around both the central andthe southern river (Fig. 9 iii B, C). When we assumed theSumatra Class Tsunami, the breakwater will expand theThis simulator displays a regional disaster situation
which was calculated using the simulation model whichdisplayed the results in animation format. Fig. 10 shows
the snapshots of the animation made using this simulator.
This animation shows resident’s distribution immediately
following the earthquake (Fig. 10 A), scene (B); shows therelay of warning transmission information to the residents
from the warning transmittal facilities, scenes (C, D & E),shows residents who have received the information
evacuating from the tsunami and going to shelters. Scene(D, E & F) shows the generation and raid of the tsunami
and the creation of casualties. At the upper right side of thescreen, the numbers indicate the total number of casualties.
Such animation is useful for its visual confirmation of
the results of the scenario simulated. In addition, it iseffective as a tool to be used in disaster education toeducate a general resident who doesn’t have technicalknowledge on the subject matter. For example, residents
are better able to grasp various concepts, such as changes
in the inundation region and depth of the water with thepassage of time, which cannot be obtained from a static
hazard map. Moreover, because the content of the scenario
expressed can be easily modified, residents can better
understand the various phenomena of the disaster and how
to effectively respond during a disaster. For example, thesafe area in the disaster struck area can change quickly
only because the scale of the disaster changes a little, andthe damage scale can change greatly depending on theadministrators and the resident’s response.
Authors have used this simulator to educate the Owase
City residents about disaster prevention. For example, themodel has been made available over the Internet so that
residents can view it freely (Fig. 11). Moreover, thissimulator has been used as a risk communication tool
during a tsunami lecture meeting held on May 6, 2004.
Two earthquakes had occurred in Owase City on
September 5, 2004, and an evacuation order was officiallyannounced after the second earthquake. The evacuation rateof residents living near the coast exceeded 70 percent
according to a follow-up investigation conducted.
Therefore, it can be said that many residents have properFig. 10 Snapshots of Animation
result from an individual or society perspective.
In the future, we will aim to further improve theaccuracy of the simulation model and extend its
applications to other natural hazards such as; floods,
earthquake, typhoons etc. Moreover, we will further
advance the system function such as its interface,animation etc. in order to make it more user friendly whenbeing used as a disaster strategy or risk communication
tool.
Fig. 11 OWASE Dynamic Tsunami Hazard Map15)
image of the potential threat posed by a tsunami.
7. CONCLUSION
It is necessary to take various measures into
consideration in order to plan an effective disasterprevention strategy. In this study, the scenario simulator
that expressed social circumstances during normal
circumstances and during a disaster was developed as a
strategy tool for disaster prevention measures. Due to its
visual presentation, this simulator can be used as a risk
communication tool that can effectively teach theappropriate response action needed during a disaster. Since
this simulator expresses the status of progress of thedisaster phenomenon and society based on usual activities
during normal circumstances, this simulator can be applied
to various situations to indicate problems that are likely to

Acknowledgments: The authors would like to express
their gratitude to the Owase city office that extended theirkind assistance to us and to the Japan Weather Association
who performed the tsunami calculations for this model.
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