A. Wijesundara et al., Integer. J. Engg. Res. Tech. Vol 1 (5)
ISSN NO. 2348 – 6821
Integrated Journal of Engineering Research and Technology
Content Available at www.ijert.co
IDENTIFICATION OF TSUNAMI RISK AREA USING GEOGRAPHICAL INFORMATION
SYSTEMS & REMOTE SENSING
(A CASE STUDY OF WELIGAMA COASTAL BELT AREA, SRI LANKA)
Anusha Wijesundara*1, Manjula Ranagalage2
1. National Aquatic Resources Research & Development Agency, Sri Lanka.
2. Department of Social Sciences, Rajarata University of Sri Lanka, Sri Lanka.
ABSTRACT
A tsunami is a natural coastal hazard generated in the deep ocean as a
result of an earthquake, volcanic activity, submarine landslide or
Article History:
meteoritic impact. The 26 December 2004 earthquake off the west
coast of Sumatra, Indonesia generated one of the deadliest tsunami in
Received onhistory. It demolished the coastal areas of Indonesia, Sri Lanka, India,
30 Sep 2014
and Thailand, as these Asian counties located shadow zone of this
Accepted ontectonic belt. Over thirty thousand loss their lives and also millions of
2nd Sep 2014
worth extensive property damage because lacking of adequate
knowledge and preparedness for such an infrequent but a powerful
event. As Sri Lanka situated in a shadow zone of the earthquake
Corresponding Author:
generated belt preparedness is very important factor.
Early warning and evacuations based on inundation maps are the
Manjula Ranagalage
most strategic ways to minimize the massive loss of life and damages
Lecturer, Department of
to the property in risk community. The study focused towards
Social Sciences, Rajarata
creation of a Tsunami risk map for Weligama area. The numerical
simulation of tsunami inundation was carried out using Com MIT
University of Sri Lanka,
model with the major input parameters of earthquake source
Sri Lanka
parameters, topography and bathymetry data.
EmailThe December 2004 Sumatra Earthquake source parameters were
manjularanagalage@gmail.com
used for generation, propagation, and coastal amplification of the
tsunami waves and finally the inundation extent and water level was
obtained to prepare large scale action maps on tsunami inundation to
protect the coastal communities.
The GIS tool has been used to incorporate the tsunami inundation depth to prepare the final tsunami risk
map. Reliability of model results was compared with the field data and a high resolution Quick Bird image,
which was taken just after the 26th December 2004 earthquake. The results from this study will be useful
for delineation of evacuation routes long – term planning and implementing activities to reduce impacts of
tsunami in future.
KEYWORDS: Tsunami Inundation Mapping, Natural Disaster Response, Numerical
Simulation.
INTRODUCTION
Tsunami is a series of large waves of
generated by a violent, impulsive undersea
extremely long wavelength and period usually
disturbance or activity near the coast or in the
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A. Wijesundara et al., Integer. J. Engg. Res. Tech. Vol 1 (5)
ISSN NO. 2348 – 6821
ocean (Ramy, 2005). In the deep sea, it is
inundation information allows determining
propagate with high speed and the low wave
level of vulnerably associated with coastal
amplitude. At the same time wave amplitude
belt. Risk assessment process requires the use
is rapidly increasing and converts in to killer
of mathematical models to simulate the
waves and inundates low-lying coastal areas
generation, the propagation across the ocean,
resulting
and eventually, the inundation for historical
mass
destruction.
When
the
tsunami waves reach shore, speed of the
or hypothetical source.
waves decrease according to the topography
1.1 Background of the study
of the sea bed. Tsunami waves are mainly
Tsunamis are a major concern to the Pacific
formed with the sudden displacement of
islands and Asian coastal nations because
seabed due to an underwater earthquake. In
they may occur at any time, with little or no
the deep sea, it propagates with a high speed
warning, and with destructive force. During
and low wave amplitude. When the tsunami
the past decade, more people have died from
waves reach the shore, the speed of the waves
tsunamis than from hurricanes, earthquakes,
decreases according to the topography of the
and floods combined. A tsunami is caused
seabed. At the same time, the wave amplitude
when there is a disturbance deep under the
increases rapidly and converts into killer
ocean such as an earthquake, volcano or a
waves and inundate low-lying coastal areas,
landslide. An underwater earthquake is the
resulting in mass destruction.
most common cause for a tsunami, but not
In order to reduce the impact of tsunamis, it
just any underwater earthquake causes a
is
thorough
tsunami. The earthquake needs to be a large
understanding of the area at risk, its
enough earthquake of around 7.0 magnitudes
population, infrastructure, and pattern of
or bigger.
land use. In order to reduce the impact of
Sri Lanka experienced its worst natural
tsunamis, it is beneficial to have a thorough
disaster on the 26th of December 2004 one of
understanding of the area at risk, its
the hardest hit countries in terms of loss of
population, infrastructure, and pattern of
life,
land use. Early warning and evacuations
estimates stand at more than 31000 lives lost,
based on inundation maps are the most
over 4000 missing and 1 million affected.
strategic ways to minimize massive loss of life
These are staggering numbers for any
and
risk
country, but especially for Sri Lanka when
community & most countries now start to
they are compared in relative terms and the
prepare disaster prevention plans. Therefore
capacity to recover (Herath, 2008). The
it is important to prepare large scale action
reconstruction should take place based on an
maps on tsunami inundation incorporating
assessment of risks and appropriate measures
land use details using a GIS tool. Hazard
to minimize losses from a future similar
assessment
disaster. Although the frequency of Tsunami
beneficial
damages
to
to
have
the
studies
a
property
integrated
in
with
162
infrastructure
and
assets.
Current
A. Wijesundara et al., Integer. J. Engg. Res. Tech. Vol 1 (5)
ISSN NO. 2348 – 6821
in Sri Lanka is very small, should avoid
was badly hit by tsunami waves and is highly
rebuilding the same disaster. To assess risks,
affected to the fisheries sector as there is a
accurate representation of topography when
major fishery harbour called Mirissa located
inundation impacts on people are considered.
close to the bay of Weligama. The tsunami
Therefore it is necessary to step up tsunami
resulted in major, but great damages to the
awareness effects such as tsunami forecasting
Weligama area infrastructure & assets and
methods
lost massive of lives.
and
inundation
maps
at
risk
Under tsunami
communities in Sri Lanka. Properly prepare
inundation mapping along Weligama coast an
against the threat of tsunami inundation, thus
integrated approach is adopted to identify the
saving lives and protecting property. It is
vulnerable areas.
helpful
with
The main objective of this study is to integrate
population density and Land use information
a tsunami simulation model and remote
& Disaster management activities.
sensing data with the available topographic
1.2 Statement of the Problem
data using a GIS tool for Tsunami inundation
Any natural Hazard results to a disaster
mapping and risk mapping to identify the
depending upon its magnitude of the impact.
disaster risk to provide facility for decision
Natural
makers to understand an evacuation planning
for
risk
hazard
analysis
such
process
as
an
undersea
earthquake may cause a Tsunami hazard to
& in public education & awareness activities.
the coastal land region resulting in a disaster,
1.4 Prior Knowledge
damaging property and people. Since such
Inundation maps are depictions of coastal
type of natural hazards cannot be controlled,
areas that identify regions, populations, and
they
and
facilities that are at risk from tsunami attack,
precautionary/safety planning can be done
which could be used by emergency planners
along the coastal regions to safeguard from
for
the damages. The assessment of Tsunami
Inundation maps require an assessment of
impact over the people and property was
local and far-field geologic hazards, and the
important for planning the relief actions.
calculation
Hence the requirement for the Tsunami
2008). Numerical simulations are useful tools
Disaster Mapping to identify the Tsunami
for analyzing tsunami propagation, coastal
affected for planning purpose is the essential
amplification and inundation (Alpar et al,
exercises for managing future.
2006). The numerical simulation of tsunami
1.3 Justification of the Study
inundation was carried out using TUNAMI
can
be
monitored
The tsunami impact study is
disaster
of
response
coastal
and
mitigation.
flooding
(Kumar,
N2 model. The major input parameters for
undertaken
along coastal belt of Weligama area, which is
the
located at latitude 05º 51’ 14.697” N -05º 58’
parameters, topography and bathymetry data.
6.541”N and longitude 80º 34’ 57.477” E to
The December 2004 Sumatra Earthquake
80º 22’ 7.139” E respectively. The study area
source parameters were used for generation,
163
model
were
earthquake
source
A. Wijesundara et al., Integer. J. Engg. Res. Tech. Vol 1 (5)
ISSN NO. 2348 – 6821
propagation, and coastal amplification of the
tsunami waves and finally the inundation
extent and depth were obtained for Galle city
parameter for quantification of level of
(Borah, 2007). The shallow water wave
damage caused by tsunami (Imamura, 2001).
equations are governing equations behind the
These depth ranges were chosen for hazard
model. It uses a nested grid of topographic
analysis because they are approximately
and bathymetric elevations and calculates a
knee-high or less, knee-high to head-high,
wave elevation and velocity at each grid point
and more than head-high (Timothy et al.
at specified time intervals to simulate the
2004).
generation from Sumatra source, propagation
1.4 Study Area
through Ocean and finally inundation at land
The tsunami impact study is undertaken
(Imamura, 1995). To establish a cost effective
along the coastal belt of Weligama area,
method and a quick determination of factors
which is approximately 35 km long including
that influence damage intensity in tsunami
the Weligama bay in the South coast of Sri
prone
the
Lanka (Figure 01). This area was badly hit by
preparatory or causal controlling factors
the 2004 December tsunami waves and is
using remote sensing and GIS methodology
currently involved in large development
(Willige, 2006). Tsunami intensity scale
reconstructions activities.
areas,
one
must
analyze
considers inundation depth as one of the vital
Figure 1: Weligama Coastal Region.
1.5 Data and Materials Used
Digital Data – Land use data, 1:5000 building
Bathymetry Data - Single beam shallow water
layer, Road network
bathymetric data
Demographic Data - Census data (2001) from
GEBCO 30 sec. data
Central Bureau of Statistics, Sri Lanka
Data can be analysed and processed by using the
Topographic data - LIDAR
following softwares:
1:10,000 contours
ArcGIS 9.3,ComMIT Numerical Model, Hypack
Gold 4.3,PDS 2000, CARIS GIS 4.4, Auto CAD
2007, 2008, ERDAS Imagine 9.2, Global Mapper,
Surfer 82.0.
SRTM data
Satellite Images- Quick Bird images (before
and after the 2004 Tsunami event)
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ISSN NO. 2348 – 6821
METHODOLOGY
2.1 Data Preparation
scenario that was relevant to the 2004
The run-up of the tsunami on to land is the
Sumatra earthquake. It uses a three-nested
most undeveloped part of the tsunami model,
grid of bathymetry and topography. A
primarily because of the lack of the two major
combination of high-resolution bathymetric
types of data i.e the high quality field
and topographic data was used for the inner
measurements for testing of the models and
grid, which covers the entire study area while
fine resolution bathymetric & topographic
GEBCO and SRTM data were used for the
data (Titov, 1997). Hence, in this study, all
other two grids. Models calculated the
available local and global bathymetric data,
velocity at each grid point at specified time
topographic data and Lidar data were brought
intervals to simulate the generation from the
into the world geodetic coordinate system
Sumatra source, propagation through the
(WGS 84) and merged together to generate
Ocean
the Digital Terrain Model (DTM). By using
(Imamura et al., 1995).
Krigging method, data was interpolated for
2.3 Inundation Map, Hazard Map and
creation the three nested grids with both
Risk Map Creation
bathymetric and topographic data. Using
The GIS environment has been used to
DTM, all undesirable elevations and depths
incorporate and analyse the maximum wave
were removed and converted into ASCII grid
run-up. According to the results, maximum
format for propagation and the Tsunami
wave run up “NetCDF” raster file used to
numerical
tsunami
prepare the inundation map of the study area.
inundation, maximum wave height, wave
The computed inundation depth is classified
speed, and reflection in the Weligama coastal
into four ranges for quantification of level of
area. (Figure 02)
hazard damages. The physical characteristics
2.2 Tsunami Numerical Modelling
of the coastal area (land use and population)
The ComMIT Numerical model was used for
and the built environment in the area
identifying the tsunami propagation, coastal
considered to determine the vulnerability. A
amplification and inundation. The model was
risk to a natural event is defined as the
developed by Vasli Titov at the NOAA centre
mathematical product between vulnerability
for tsunami research, based on non-linear
and hazard; it refers to the expected loss from
shallow
a given hazard to a given element at risk.
modelling
water
to
equations
study
and
governing
equations. A magnitude of 9.2 on the Rictour
scale and 1200 km length of fault rupture
were used as parameters of the earthquake
165
115
and
finally,
inundation
at
land
A. Wijesundara et al., Integer. J. Engg. Res. Tech. Vol 1 (5)
Topographic Data
LiDAR Data
Contours (from
1:10,000 & 1:50,000
Map Sheet
ISSN NO. 2348 – 6821
Co-ordinate
System
Transformation
Bathymetric Data
Coastline, offshore &
near shore bathy
Nautical charts GEBCO
Data Preparation
Data Merging
Convert to Raster
Data Interpolation
Convert to ASCII
Tsunami Modelling
Out Put
Travel Time
Run-up height &
Inundation
Distance
Model Output (Senario)
ARC GIS
Inundation Map (Digital)
Hazard Map (digital)
Risk Map (Digital)
Vulnerability Map
(Land use, Population
Density)
Disaster Risk
Figure 2. Flow diagram of the methodology.
3.0 RESULTS AND DISCUSSION
The inundation depth is one of the most
distribution along the Weligama coastal belt
important parameters for analysing the level
and the tsunami wave height was estimated at
of damage due to tsunami. Figure 03
3-4 m along the coastline. In this study, the
indicates the computed inundation depth
inundation depth, which is given by the
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ISSN NO. 2348 – 6821
model, was classified into four levels; 0-0.5
Weligama city to find the affected areas due
m, 0.5-1.0 m, 1.0- 2.0 m and greater than 2
to Tsunami.
m, using the Arc GIS tool for identifying
By using the weighted overlay method find
hazard
out the risky areas in three stages like low,
zones.
Figure
04
indicates
the
Tsunami hazard map in the Weligama Bay
moderate and high risk (Figure 05).
area.
According to the results of the tsunami affect
Vulnerability is defined as the potential for
in 2004, it can be realized that the area which
damage while hazard, for a Tsunami event, is
was identified as the risky by the tsunami
defined as the wave height. In order to
modeling, was greatly affected and lost
examine the vulnerability in relation to land
massive of lives and damaged to the property.
use
used.
Hence, Preparation of tsunami inundation
Vulnerability maps recognize sectors within
maps is very important for delineation of
the selected areas that are highly vulnerable
evacuation routes and long term planning in
to a maximum tsunami run-up and flood
vulnerable
event. The inundation map integrates with
provide early warnings to take precautions to
land use based population density map of
protect from any kind of natural hazards.
and
population
density
was
coastal
communities
Figure 3: Inundation Depth Distribution in Weligama Bay Area.
167
169
and
to
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ISSN NO. 2348 – 6821
Figure 4: Tsunami Hazard Map in Weligama Bay Area.
Figure 5: Risk Map.
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A. Wijesundara et al., Integer. J. Engg. Res. Tech. Vol 1 (5)
The results show the high hazard zone
covering a larger area of the Weligama Bay
and the coastline. The Quick Birds Satellite
image clearly shows the damaged areas in the
ISSN NO. 2348 – 6821
Weligma Bay (Figure 06) and overlay analysis
has given a clear representation to evaluate
the results given by the ComMIT numerical
model.
Figure 6: Tsunami Affected area in Weligama Bay.
4.0 CONCLUSION
The Tsunami numerical model was used for
and accuracy of the DTM. Understanding
the
incor-
vulnerability and hazard level, identification
porating high-resolution near-shore bathy-
of possible mitigation measures, of the socio-
metric and topographic data to model the
economic impact caused by the event is very
2004 tsunami event. The results shows that
important to evaluate the level of the risk.
the areas in Weligma Bay are in a high
Tsunami risk assessment is performed in the
tsunami hazard risk area due to its low
study area incorporating tsunami hazard,
elevation and topography. The validation of
population
the model results with field surveyed data on
information. The risk map shows 97.61 % of
the 2004 tsunami event shows an 80 % match
the study area falls in very high risk zone
with the field observations. Accuracy of the
while 1.735 % falls in moderate and the rest
Tsunami hazard prediction depends on the
0.65 % falls in low hazard zone. The
estimation of earthquake source parameters
inundation modeling used for tsunami hazard
tsunami
hazard
assessment,
169
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and
land
use
vulnerability
A. Wijesundara et al., Integer. J. Engg. Res. Tech. Vol 1 (5)
ISSN NO. 2348 – 6821
assessment incorporates high resolution near
economic impact caused by the event is very
shore bathymetry and LIDAR (Light Angle &
important to evaluate the level of the risk.
Detection Ranging) to model the December
Tsunamis are unpredictable events and
2004 tsunami inundation even.
increasing the uncertainty of preventive
The study reveals that integration of remote
action, contribute to a very low social memory
sensing, GIS and demographic data with
on these phenomena that is inversely related
numerical inundation model is quite useful
with a high demand for decision criteria
for tsunami risk assessment studies. GIS tools
based on scientific knowledge. This method is
provide
the
useful for tsunami risk assessment while the
management of the possible disasters. The
local authorities can use it for early warning
results output can be validating with the
and evocation purposes by creating different
ground truth data to identify the reliability of
earthquake
the tsunami numerical model.
The hazard
contribute in reducing tsunami damage and
map
makers
planning mitigation measures in future.
a
scientific
facilitates
to
approach
decision
to
to
scenarios.
The
study
could
understand an evacuation planning & in
ACKNOWLEDGEMENT
public education & awareness activities &
We would like to pay our obligation to
provides indication to demarcate suitable
acknowledge the wisdom and consent of
sites
Understanding
generous people who have helped me to
vulnerability and hazard level, identification
complete the project report successfully.
for
rehabilitation.
of possible mitigation measures, of the socioREFERENCES
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