TSUNAMI EMERGENCY RESPONSE SYSTEM USING GEO-INFORMATION TECHNOLOGY ALONG THE WESTERN COAST OF INDIA

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 05, May 2019, pp. 418-429, Article ID: IJCIET_10_05_045
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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 natural
disaster. We expect that the tsunami risk map presented here will supportive to tsunami
early response system along the western coast of India.

V. M. Patel, M. B. Dholakia, A. P. Singh and V.D. Patel
Key words: Tsunami, GIS, Tsunami Risk Zone and 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, 10(05),
2019, pp. 418-429
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=05
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)
[9, 32, 47], 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) [8, 12, 14, 18, 22]. 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) [1, 2, 4, 15, 23]. 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), [38] 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) [16]. 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).
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

Tsunami Emergency Response System Using Geo-Information Technology Along the Western
Coast of India
management (Kolbe et al. 2005; Marincioni, 2007; Zlatanova, 2008) [24, 27, 53]. 3D
visualisations have the potential to be an even more effective communication tool (Zlatanova
et al. 2002; Kolbe et al. 2005) [51]. 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 making process (Christie, 1994), therefore disaster managers increasingly use
digital maps. Better disaster management strategies can be designed by visualization.
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) [41]
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 [5, 6, 7, 22, 28, 29, 34, 39, 48]
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) [44]. 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) [36, 37, 45]. 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) [35].
Figure 1 Location of tsunami forecast points along the west coast of India, Pakistan, Iran and Oman
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) [33]. The location of tsunami forecast points along the west coast of India
including Pakistan, Iran and Oman are shown in Figure 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) [31] method. The water
elevation in the source is about 3 m, and the depression is about 1 m.
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) [19, 20, 21, 42].

Coast of India
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 (Figure 2). The results of initial tsunami generation
based on the fault parameters given by Byrne et al. (1992) are shown in Figure 2(a). Tsunami
snapshots (Figures 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 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) [3]. Due to this effect, most of the
tsunami energy propagates in the direction. The tsunami travel time map is shown in Figure 3.

Figure 2 Results of the tsunami generation and propagation modeling
Figure 3 Tsunami travel time contour map
Figure 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;

Coast of India
Heidarzadeh et al., 2008) [17]. The maximum calculated tsunami run-ups were about 0.7–1.1
m along coast of Oman, 0.7–1.35 m along the western coast of India, 0.5–2.3 m 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) [43]. 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 [40]. The coastal area of Okha Okha potentially affected at
different tsunami flooding scenarios shown in Figure 5. The 3D tsunami risk model of Okha at
different viewing angles is presented in Figures 6 (a)-(c). A red, blue or green colour scheme
was used to indicate the respective susceptibility to tsunami risk as shown in Figure 6 It shows
structures that are classified as very high risk, high risk and medium risk based on tsunami run-
up height.
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
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 [13, 30, 46] 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

Coast of India
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.
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, and 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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