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 6, Issue 7, Jul 2015, pp. 80-92, Article ID: IJCIET_06_07_010

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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

Tsunami Emergency Response System Using Geo-Information Technology along the

Western Coast of India


natural disaster. We expect that the tsunami risk map presented here will

supportive to tsunami early response system along the western coast of India.

Key words: Tsunami, GIS, Tsunami Risk Zone and Western Coast of India

Cite this Article: Patel, V. M., Dholakia, M. B., Singh, A. P. and Patel, V. D.

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. 80-92.

http://www.iaeme.com/IJCIET/issues.asp?JTypeIJCIET&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) [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

V. M. Patel, M. B. Dholakia, A. P. Singh and V. D. Patel


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) [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].

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; 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.

Tsunami Emergency Response System Using Geo

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Figure 4 Maximum calculated tsunami run

Figure 5 Coastal area of Okha potentially affected at different sea level rise scenarios



ET/index.asp 87 [email protected]

aximum calculated tsunami run-ups along western coast of

Coastal area of Okha potentially affected at different sea level rise scenarios

Information Technology along the

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ups along western coast of India

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 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.




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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