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International Journal of Civil Engineering and Technology (IJCIET) Volume 6, Issue 7, July (2015), pp. 78-90, Article ID: Article ID: 20320150607010
Available online at
http://www.iaeme.com/currentissue.asp?JType=IJCIET&VType=6&IType=7
ISSN Print: 0976 – 6308 and ISSN Online: 0976 – 6316
© IAEME Publication
___________________________________________________________________
TSUNAMI EMERGENCY RESPONSE
SYSTEM USING GEO-INFORMATION
TECHNOLOGY ALONG THE WESTERN
COAST OF INDIA
V. M. Patel
Civil Engineering Department, K.D. Polytechnic, Patan – 384265, Gujarat, India
M. B. Dholakia
L.D. College of Engineering, Ahmedabad-380015, Gujarat, India
A. P. Singh
Institute of Seismological Research, Gandhinagar- 382 009, Gujarat, India
V.D. Patel
Civil Engineering Department, Government Engineering, Patan, Gujarat, India
ABSTRACT
The Makran coast is extremely vulnerable to tsunamis and earthquakes
due to the presence of three very active tectonic plates namely, the Arabian,
Eurasian and Indian plates. On 28 November 1945 at 21:56 UTC, a massive
Makran earthquake generated a destructive tsunami in the Northern Arabian
Sea and the Indian Ocean. The tsunami was responsible for loss of life and
great destruction along the coasts of Pakistan, Iran, India and Oman. In this
paper tsunami early response system created using classification of tsunami
susceptibility along the western coast of India. Based on the coastal
topographical features of selected part of the western India, we have prepared
regions susceptible to flooding in case of a mega-tsunami. Geo-information
techniques have proven their usefulness for the purposes of early warning and
emergency response. These techniques enable us to generate extensive geo-
information to make informed decisions in response to natural disasters that
lead to better protection of citizens, reduce damage to property, improve the
monitoring of these disasters, and facilitate estimates of the damages and
losses resulting from them. The classification of tsunami risk zone (susceptible
zone) is based on elevation vulnerability by Sinaga et al. (2011). We overlaid
satellite image on the tsunami risk map, and identified the region to be
particularly at risk in study area. In our study satellite images integrated with
GIS/CAD, can give information for assessment, analysis and monitoring of
Tsunami Emergency Response System Using Geo-Information Technology Along The
Western Coast Of India
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natural disaster. We expect that the tsunami risk map presented here will
supportive to tsunami early response system along the western coast of India.
Keywords: Tsunami, GIS, Tsunami Risk Zone, Western Coast of India
Cite this Article: V. M. Patel, M. B. Dholakia, A. P. Singh and V.D. Patel,
Tsunami Emergency Response System Using Geo-Information Technology
Along the western Coast of India. International Journal of Civil Engineering
and Technology, 6(7), 2015, pp. 78-90.
http://www.iaeme.com/currentissue.asp?JType=IJCIET&VType=6&IType=7
________________________________________________________________
1. INTRODUCTION
Tsunami is a phenomenon of gravity waves produced in consequence of movement of
the ocean floor. The giant tsunami in the Indian Ocean on 26 December 2004,
claiming more than 225,000 lives (Titov et al. 2005; Geist et al. 2006; Okal &
Synolakis 2008, Singh et al. 2012), has emphasized the urgent need for tsunami
emergency response systems for various vulnerable coastlines around the world,
especially for those neighbouring the Indian Ocean. The second deadliest tsunami
prior to 2004 in South Asia occurred on 28 November 1945 (Heck 1947; Dominey-
Howes et al. 2007; Heidarzadeh et al. 2007; Jaiswal et al. 2009; Hoffmann et al.
2013). It originated off the southern coast of Pakistan and was destructive in the
Northern Arabian Sea and caused fatalities as far away as Mumbai (Berninghausen
1966; Quittmeyer & Jacob 1979; Ambraseys & Melville 1982; Heidarzadeh et al.
2008; Jaiswal et al. 2009). More than 4000 people were killed by both the earthquake
and the tsunami (Ambraseys & Melville 1982). Several researchers have different
estimates about the location of the earthquake epicentre. Heck (1947) reported the
epicentre at 25.00º N and 61.50º E. According to Pendse (1948), the epicentre was at
24.20º N and 62.60º E, about 120 km away from Pasni. Ambraseys and Melville
(1982) reported the epicenter at 25.02º N and 63.47º E. By recalculating the seismic
parameters of the 1945 earthquake, Byrne et al. (1992) suggested that the epicentre
was at 25.15º N and 63.48º E, which is used in the present study. The earthquake
mainly affected the region between Karachi and the Persian border. In Karachi,
ground motions lasted approximately 30 sec, stopping the clock in the Karachi
Municipality Building and interrupting the communication cable link between
Karachi and Muscat (Oman). According to Pendse (1948), the tsunami that was
generated reached a height of 12-15 m in Pasni and Ormara on the Makran coast and
caused great damage to the entire coastal region of Pakistan. However, several
researchers have estimated the tsunami height of about 5-7 m near Pasni (Page et al.
1979; Ambraseys & Melville 1982; Heidarzadeh et al. 2008b). The tsunami wave was
observed at 8:15 am on Salsette Island, i.e. Mumbai, and reached a height of 2 m
(Jaiswal et al. 2009; Newspaper archives, Mumbai).
V. M. Patel, M. B. Dholakia, A. P. Singh and V.D. Patel
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Table 1 Historical tsunami that affected the western coast of India
NO Year Longitude °E) Latitude °N) Moment
Magnitude
Tsunami Source of Loss
of Life /Location
1 326BC 67.30 24.00 Earthquake
2 1008 60.00a
25.00a
? Earthquake 1000*
52.3b
27.7b
3 1524 Gulf of Cambay Earthquake
4 1819 Rann of Kutch 7.8 Earthquake >2000*
5 1883
Krakatau Krakatau Volcanic
6 1845 Rann of Kutch 7.0 Earthquake
7 1945 63.00 24.50 8.1 Earthquake 4000*
8 2007 101.36 -4.43 8.4 Earthquake
9 2013 62.26 25.18 7.7 Earthquake
Volcanic
a Rastogi and Jaiswal (2006)
b Ambraseys and Melville (1982)
*Both by earthquake and tsunami: Ambraseys and Melville, 1982; Bilham, 1999;
Byrne et al., 1992; Dominey-Howes et al., 2006; Heck, 1947; Merewether, 1852;
Murty and Rafiq, 1991; Murty and Bapat, 1999; Okal et al. 2006; Paras-Carayannis,
2006; Pendse, 1946; Rastogi and Jaiswal, 2006; Quittmeyer and Jacob,1979; Walton,
1864; National Oceanic and Atmospheric Administration (NOAA); United States
Geological Survey (USGS);Jaiswal et al. 2011; Jaiswal et al. 2008
1.1 Importance of Geo-Information Technology for Tsunami Risk Visualization
The tsunami risk visualization created by Geo-Information technologies of
Geographic Information Systems (GIS), Remote Sensing (RS) and Computer Aided
Design (CAD) are powerful tools for conveying information to decision-making
process in natural disaster risk assessment and management. Visualization is the
graphical presentation of information, with the goal of improving the viewer
understands of the information contents. Comprehension of 3D visualized models is
easier and effective than 2D models. 3D visualization models are important tools to
simulate disaster from different angle that help users to comprehend the situation
more detailed and help decision makers for appropriate rescue operations. 3D
visualizations are tools for rescue operations during disasters, e.g., cyclone, tsunami,
earthquake, flooding and fire, etc. 3D visualization has a big potential for being an
effective tool for visual risk communication at each phase of the decision-making
process in disaster management (Kolbe et al. 2005; Marincioni, 2007; Zlatanova,
2008). 3D visualisations have the potential to be an even more effective
communication tool (Zlatanova et al. 2002; Kolbe et al. 2005). Previous studies have
shown that the presentation of hazard, vulnerability, coping capacity and risk in the
form of digital maps has a higher impact than traditional analogue information
representations (Martin and Higgs, 1997). Graphical representation significantly
reduces the amount of cognition effort, and improves the efficiency of the decision
Tsunami Emergency Response System Using Geo-Information Technology Along The
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making process (Christie, 1994), therefore disaster managers increasingly use digital
maps. Better disaster management strategies can be designed by visualization.
The advances in GIS/CAD and RS supported visualization have a potential to
improve the efficiency of disaster management operations by being used as a risk
communication tool. 3D models particularly the city and building models are created
by CAD software and scanned into computer from real world objects. In this study,
classification of tsunami risk zones and tsunami risk 3D visualization created in
GIS/RS and CAD environments. We except that the results presented here will be
supportive to the tsunami emergency response system and useful in planning the
protection measures due to tsunami.
1.2 Emergency Response System along Coast of Gujarat
Gujarat state has the longest coastline in India, and has massive capital and
infrastructure investments in its coastal regions (Singh et al., 2008). With rapid
developmental activities along the coastline of Gujarat, there is a need for preparing
tsunami risk 3D visualizations database using geo-information technology. The coast
of Gujarat is prone to many disasters in past (Singh et al., 2008). Some of the most
devastating disasters that have struck the state in the last few decades include: the
Morbi floods of 1978; the Kandla (port) cyclone of 1998; the killer earthquake in
Kutch, January 26th 2001; and the flash floods in south Gujarat in 2005 and in Surat
in 2006. Also in the past the coast of Gujarat was affected by tsunami (Jaiswal et al.,
2009; Singh et al., 2012, Patel et al., 2014). Visualization is the graphical presentation
of information, with the goal of improving the viewer understands of the information
contents. Comprehension of 3D visualized models is easier and effective than 2D
models. 3D visualization models are important tools to simulate disaster from
different angle that help users to comprehend the situation more detailed and help
decision makers for appropriate rescue operations. 3D visualizations are tools for
rescue operations during disasters, e.g., cyclone, tsunami, earthquake, flooding and
fire, etc (Patel et al., 2013).
2. DATA USED AND TSUNAMI MODELING
In the present study tsunami forecast stations were selected for output of tsunami
simulation along the coast of India, Pakistan, Oman and Iran. Most of the tsunami
forecast stations were selected in such a way that sea depth is less than 10.0m to better
examine tsunami effect (Onat and Yalciner, 2012). The location of tsunami forecast
points along the west coast of India including Pakistan, Iran and Oman are shown in
Fig. 1. Bathymetry and elevation data are the principal datasets required for the model
to capture the generation, propagation and inundation of the tsunami wave from the
source to the land. The bathymetry database taken from General Bathymetric Chart of
the Oceans (GEBCO) 30 sec is used for tsunami modeling and the topography data
taken from SRTM 90 m resolution is used for preparation of the inundation map. The
bounding coordinates selected are 55° - 76° E longitudes and 10° – 30° N latitudes.
The rupture parameters are taken from Byrne et al. (1992), which was used to model
the source of the 1945 earthquake in this study (Table 2). The initial wave amplitude
(elevation and depression) for the source is computed using Okada’s (1985) method.
The water elevation in the source is about 3 m, and the depression is about 1 m.
V. M. Patel, M. B. Dholakia, A. P. Singh and V.D. Patel
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Figure 1 Location of tsunami forecast points along the west coast of India, Pakistan, Iran and
Oman
Furthermore, tsunami simulation basically aims to calculate the tsunami heights and
its arrival times in space and time. The tsunami is assumed as a shallow water wave,
where wavelength is much larger than the depth of the sea floor. The governing
equations in tsunami numerical modeling are non-linear forms of shallow water
equations with a friction term. The formulas are solved in Cartesian coordinate system
(Imamura et.al, 2006).
Table 2 The rupture parameter of 1945 Makran earthquake provided by Byrne et al.
(1992)
Epicenter of
Earthquake
Fault
length
Fault
width
Strike
angle
Rake
angle
Dip
angle
Slip
magnitude
Focal
depth
Latitude Longitude (km) (km) ° ° ° (m) (km)
25.15° N 63.48° E 200 100 246 90 7 7 15
3. RESULTS AND DISCUSSION
Tsunami snapshots show that the 1945 Makran event affected all the neighboring
countries including Iran, Oman, Pakistan, and India (Fig. 2). The results of initial
tsunami generation based on the fault parameters given by Byrne et al. (1992) are
shown in Fig. 2(a). Tsunami snapshots (Fig. 2(b), 2(c), 2(d), 2(e) and 2(f)) show the
estimated wave propagation at t= 30, 60, 90, 120 and 150 minutes after the
tsunamigenic earthquake, respectively. Along the southern coast of Pakistan, the
tsunami wave reaches Pasni in about 5 to 15 minutes, Ormara in about 60 minutes,
and Karachi in about 110 minutes. While along the southern coast of Iran, the tsunami
wave reaches Chabahar in about 30 to 35 minutes and Jask in about 70 to 75 minutes.
After the earthquake, the tsunami wave reaches the coast of Oman namely at Muscat
in about 40 minutes, Sur in about 30 to 40 minutes, Masirah in about 60 to 70
minutes, Sohar in about 80 minutes, and Duqm in about 130 minutes. Furthermore,
the tsunami wave reaches the western coast of India along the Gulf of Kachchh in
about 240 minutes, Okha in about 185 minutes, Dwarka in about 150 minutes,
Porbandar in about 155 minutes, Mumbai in about 300 minutes, and Goa in about 215
minutes. It is also observed that the distance from epicentre to Mumbai is less than
Tsunami Emergency Response System Using Geo-Information Technology Along The
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Goa, but the arrival time of the first tsunami wave at the Mumbai is more than Goa. It
could be due to the fact that Mumbai offshore is shallower that Goa and also due to
the directivity of tsunami wave propagation. It is well known that most of the
tsunami’s energy travels perpendicular to the strike of the fault which is due to
directivity (Ben-Menahem and Rosenman 1972; Singh et al., 2012, Patel et al., 2014).
Due to this effect, most of the tsunami energy propagates in the direction. The
tsunami travel time map is shown in Fig. 3.
Figure 2 Results of the tsunami generation and propagation modeling
V. M. Patel, M. B. Dholakia, A. P. Singh and V.D. Patel
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Figure 3 Tsunami travel time contour map
Fig. 4 shows the maximum calculated tsunami run-ups along western coast of
India for a tsunami simulation of 360 minutes. The simulated results show that the
maximum tsunami height is about 5-6 m near the southern coast of Pakistan, which is
corroborated with the previous researchers in the same region (Page et al.,1979;
Ambraseys and Melville,1982; Heidarzadeh et al., 2008). The maximum calculated
tsunami run-ups were about 0.7-1.1m along coast of Oman, 0.7-1.35m along the
western coast of India, 0.5-2.3m along the southern coast of Iran and 1.2-5.8m along
the southern coast of Pakistan, respectively. The tsunami run-up along the southern
coast of Pakistan is far larger than that along the other coasts and may be due to
directivity of the tsunami.
It is believed that the digital topographical data is very important in detecting
tsunami prone area. The SRTM data are used to provide digital elevation information.
Based on the processed SRTM data in GIS/CAD, all low-lying coastal areas
potentially at risk of tsunami flooding have been identified. The classification of
tsunami risk zone is based on elevation vulnerability followed by Sinaga et al. (2011).
However, for high resolution mapping of tsunami risk zone along the coastal region,
very high resolution topographical data and satellite images are needed. In this study,
we developed the methodology for creation of 3D infrastructure located in tsunami
risk zones using easily available and low cost Google earth images and SRTM data in
AutoCAD Map 3D software. The coastal area of Okha Okha potentially affected at
different tsunami flooding scenarios shown in Fig. 5. The 3D tsunami risk model of
Okha at different viewing angles is presented in Fig. 6 (a)-(c). A red, blue or green
colour scheme was used to indicate the respective susceptibility to tsunami risk as
shown in Fig. 6 It shows structures that are classified as very high risk, high risk and
medium risk based on tsunami run-up height.
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Figure 4 Maximum calculated tsunami run-ups along western coast of India
Figure 5 Coastal area of Okha potentially affected at different sea level rise scenarios
V. M. Patel, M. B. Dholakia, A. P. Singh and V.D. Patel
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Figure 6 Visualization of 3D tsunami risk model of Okha with different viewing angles
4. CONCLUSION
Early warning technologies have greatly benefited from recent advances in geo-
information technologies and an improved knowledge on natural hazards and the
underlying science. Natural disaster management is a complex and critical activity
that can more effectively with the support of geo-information technologies and spatial
decision support systems. The 1945 Makran tsunamigenic earthquake is modeled
using rupture parameters suggested by Byrne et al. (1992). In most cases, the coastal
regions which are far from the source have smaller tsunami height and longer tsunami
travel times compared with the coastal regions near the source that have higher
tsunami heights and shorter tsunami travel times. As a part of a tsunami emergency
response system the 3D coastal maps should be produced for countries in the vicinity
of the MSZ, namely, Pakistan, India, Iran and Oman. The lessons learnt from the Dec
2004 tsunami could be used for future planning. Ports, jetties, estuarine areas, river
deltas and population in and around the coast of Pakistan, India, Iran and Oman could
be protected with proper methods of mitigation and disaster management. In the
future scientists/researchers need to focus on 3D visualization and animation of
tsunami risk. The study was performed to show the advantages of 3D GIS/CAD
models and satellite images in tsunami risk assessment of the Okha coast, Gujarat.
The main aim of the 3D Okha model is to visualize each building’s tsunami risk level
which improves decision maker’s understanding of the disaster level. Merging of
SRTM elevation data with satellite images is suitable for tsunami risk zone
classification. Combining the advanced computer aided modeling, GIS based
modeling, marine parameter measurements by ocean bottom seismometers and
satellite, installations of tide gauges and tsunami detection systems and also using
conventional and traditional knowledge, it is possible to develop a suitable tsunami
disaster management plan.
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5. ACKNOWLEDGEMENTS
The authors thank Profs Andrey Zaytsev, Ahmet Yalciner, Anton Chernov, Efim
Pelinovsky and Andrey Kurkin for providing NAMI-DANCE software and for their
valuable assistance in tsunami numerical modelling of this study. Profs. Nobuo Shuto,
Costas Synolakis, Emile Okal, Fumihiko Imamura are acknowledged for invaluable
endless collaboration. The VMP is grateful to Dr. B. K. Rastogi, Director General,
Institute of Seismological Research (ISR) for permission to use of ISR library and
other resource materials. APS is thankful to Director General, ISR, for permission and
encouragement to conduct such studies for the benefit of science and society.
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