· web viewthe makran coast is extremely vulnerable to tsunamis and earthquakes due to the...

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Journal of Cement and Concrete Research (JCCR)Volume 6, Issue 7, Jul 2015, pp. 44-52, Article ID: JCCR_06_07_006Available online at http://www.iaeme.com/JCCR/issues.asp?JType=JCCR&VType=6&IType=7ISSN Print: 0976-6308 and ISSN Online: 0976-6316© IAEME Publication_____________________________________________________________________

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Cite this Article: Omran, Z. A. and Jaber, W. S. Analysis the Deficit of Dissolved Oxygen in Al_Hilla River According to Wastes Disposal and Velocity of Stream. Journal of Cement and Concrete Research , 6(7), 2015, pp. 44-52. http://www.iaeme.com/JCCR/issues.asp?JType=JCCR&VType=6&IType=7

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Table 1 Reactive dyes used with their reactive systems and Colour Index numbers

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 Earthquake2 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

Volcanica Rastogi and Jaiswal (2006) [41]b Ambraseys and Melville (1982)___________________________________________________________________________

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[3] Bootorabi, F., Haapasalo, J., Smith, E., Haapasalo, H. and Parkkila, S. Carbonic Anhydrase VII—A Potential Prognostic Marker in Gliomas. Health, 3, 2011, pp. 6-12.

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Journal of Cement and Concrete Research (JCCR)Volume 6, Issue 7, Jul 2015, pp. 80-92, Article ID: JCCR_06_07_010Available online at http://www.iaeme.com/JCCR/issues.asp?JTypeJCCR&VType=6&IType=7ISSN 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. PatelCivil Engineering Department, K. D. Polytechnic, Patan - 384265, Gujarat, India

M. B. DholakiaL. D. College of Engineering, Ahmedabad - 380015, Gujarat, India

A. P. SinghInstitute of Seismological Research, Gandhinagar - 382 009, Gujarat, India

V.D. PatelCivil Engineering Department, Government Engineering, Patan, Gujarat, India

ABSTRACTThe 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


Article Title

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. Journal of Cement and Concrete Research, 6(7), 2015, pp. 80-92. http://www.iaeme.com/JCCR/issues.asp?JTypeJCCR&VType=6&IType=7

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1. INTRODUCTIONTsunami 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


Author Name

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 Earthquake2 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

Volcanica 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


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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


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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 ofEarthquake

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.


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Figure 2 Results of the tsunami generation and propagation modeling


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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.


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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


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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 [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.


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5. ACKNOWLEDGEMENTSThe 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.

REFERENCES

[1] Ambraseys, N. N., Melville, C. P. A History of Persian Earthquakes. Britain: Cambridge University Press, 1982, pp. 219.

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