Importance of Tsunami Advance Warning System - Case Study Example

TSUNAMI: CASE STUDY PROBLEM BACKGROUND Among all natural disasters, the tsunami is one of the most dangerous, in terms of its threat to human life. Throughout history, there have been devastating tsunamis that resulted in the loss of both large numbers of people and of property. In Lisbon, in 1755, tens of thousands were killed in the tele-tsunami waves, in which waves of between 6 and 7 meters were the result of the Great Lisbon Earthquake (Ramasamy et al, 2006). Another destructive tsunami, generated by a moderate earthquake, hit the Sanriku region of Japan, in 1896, resulted in unusual tsunami waves that reached 30 meters high and killed 27,122 people (Kanamori, 1972). Also, Tsunami early (2010) stated that an earthquake of 7.9RM hit the island of Mindanao in the Philippines creating a disastrous tsunami that left 5,000 dead, 2,200 missing, 9,500 injured, and a total of 93,500 people homeless. In 2004, in the Indian Ocean region, an earthquake of 9.0RM hit the region, producing a series of deadly tsunami waves that killed around 230,000 people (see Figure 1). The tsunami resulted in largest catastrophe, making causalities over an area ranging from Indonesia - next to the earthquake occurrence - Thailand and the northwestern coast of Malaysia, to thousands of kilometers away in Bangladesh, India, Sri Lanka, the Maldives, and even to Somalia, Kenya, and Tanzania in eastern Africa (McKinney, et al 2007, p.147). The large number of tsunami victims in the Indian Ocean region was due in part to the absence of a tsunami warning system. The lack of such a system related to the fact that no major tsunami events had taken place in this region since the 1883 tsunami waves that resulted from the eruption of the volcano on Krakatau Island. The waves of this tsunami were over 40 meters and killed 36,000 people (Ramasamy et al, (2006). From the critical perspective, tsunami as a natural phenomenon represents a significant risk problem for regions and populations located along ocean coastal regions. Taking into consideration such tsunami disasters as the Sumatra-Andaman in 2004, it is evident that there is a pressing need for an effective of early tsunami warning system, which not only notifies about tsunami occurrence but also forecasts its potential dynamics and assesses its risk. Figure 1. Epicenter of the the Sumatra-Andaman earthquake and tsunami directions, December 26, 2004 TSUNAMI: CHARACTERISTICS AND CLASSIFICATION Tsunami disastrous events prompted people to think about the nature of these waves, to describe and analyze their dynamics in order to avoid the loss of lives and propriety. A tsunami became known as a quick displacement of a body of water, either in a sea or a lake, causing a series of waves on a large scale. The origin of the word tsunami came from the Japanese: tsu meaning harbor and name, meaning wave (OLoughlin & Lander, 2003; Ramasamy et al, 2006). Tsunami events are not usually classified as a natural disaster since there are a lot of small tsunamis that produce a small amount of damage. However, large tsunamis that end up with a loss of lives and properties are considered to be natural disasters. The main reason for the damage of a tsunami is the huge mass of water in the wave front that continues to rise quickly and hit the coast with great force. Figure 2 illustrates that a wind-generated wave usually has a period of five to twenty seconds and a wavelength of about 300 to 660 feet (100 to 200 meters) with a speed of 10-20 mph and a height of about 10 feet (3 meters) (PDC, 2002). In contrast, the time period that the tsunami wave takes to pass the same point of the first wave ranges from minutes to hours with a wavelength that reaches several hundred kilometers (see Figure 3). The heights and the speed of a tsunami wave vary from the open seas to the shore. A tsunami wave travels on the oceans at speeds of 500 – 1000 km/h with wave height of less than a meter, which makes it unnoticeable to people on ships (see Figure 3). As the tsunami wave approaches the coast where the shallow water exists, the speed of the wave begins to decrease to 60-150 km/h where the wave accumulates, with compression causing a wave of 30 meters or more (see Figure 4). This wave hits the coast with the same accumulative energy causing damage to the coastal areas (Ramasamy et al, 2006; Keller and Blodgett, 2006). There are several factors that affect tsunami classification, based on their causes. Earthquakes are the most common source of tsunami occurrence, especially those of subduction zones where the oceanic plate goes under the continental plate causing stress, which is then released producing an earthquake. A tele-tsunami is a tsunami that is caused by a major earthquake and travels more than 1000 km from the tsunamigenic origin to the affected areas (OLoughlin & Lander, 2003). This type of tsunamis is common on the US west coast and Hawaii. Another type of tsunami also caused by earthquakes and classified based on distance — is the near-field or local tsunami. This type of tsunami has a distance of less than 1000 km from the tsunami source to the affected area (OLoughlin & Lander, 2003). A third type of tsunami, sometimes combined with an earthquake, is the landslide tsunami. This type of tsunami can occur, causing additional destruction, when the wreckage resulting from an earthquake falls either into the sea or on the ocean floor, if the earthquake is submarine. Additionally, tectonic plates play a part in generating tsunamis; tectonic tsunamis occur when the oceanic plates move up or down. Volcanoes are also considered to be another cause for tsunamis through caldera collapse (OLoughlin & Lander, 2003). Figure 2. Characteristic of a regular wind-generated wave Figure 3. Characteristic of tsunami in deep ocean Figure 4. Characteristic when tsunami is approaching shore TSUNAMI ANALYSIS: ROLE OF SCIENCE, INFORMATION TECHNOLOGY AND ENGINEERING To understand that various types of tsunamis occur as a result of different causes is not enough. There are other considerations, such as the phases of a tsunami, which must also be understood in order to prepare effective mitigation and warming systems. Most tsunami damages that occur to the coastal areas are due to the proximity of the tsunami source where the tsunami travels less than 30 minutes to hit these areas (Ramasamy et al, 2006). There are three main phases that the tsunami goes through, beginning with generation and proceeding through the propagation and inundation, or flooding, stages. Generation is the stage at which the movement of the sea floor occurs due to the released energy from various sources as discussed before, causing tsunami waves. Propagation can be described as the gravity waves movement of a tsunami through the water body, from the ocean floor to the sea surface (Ramasamy et al, 2006). Inundation is the stage at which seawater flows onto the shore causing damage to property and loss of lives. In this process, the inland water movement measures as runup, the maximum water height above the sea level, and the distance of the inundation inland (Ramasamy et al, 2006). Tsunamis usually occur because of the plate subduction that results in water displacement (OLoughlin & Lander, 2003). From the scientific perspective, computational modeling has been conducted for man years by the geological and oceanographic specialists as serving an integral role in tsunami science. Since most tsunamis are generated by sea floor displacements from large undersea earthquakes, the displacement of the sea floor after an earthquake can be modeled by the elastodynamic system (Anderson, 1991; Erdik and Durukal, 2003). This is a system of hyperbolic partial differential equations (PDEs). The displacement of the sea level corresponding to this displacement of the sea floor and the subsequent wave motion can be described by the shallow water equations, which are also a system of hyperbolic PDEs (Erdik and Durukal, 2003). The elastodynamic system is linear with variable coefficients while the shallow water equations form a nonlinear system (Anderson, 1991; Erdik and Durukal, 2003). From information technology and engineering perspective, the prediction, monitoring and mitigation of tsunami disasters can be and is enhanced with remote sensing technology and Geographic Information Systems (GIS). Remote sensing is the science and art of data gathering from a distance. It observes the earth surface features through the analysis of data acquired by a variety of devices without actually touching or contacting features of interest (Lillesand et al., 2004). By the last decade, satellite systems and various sensors had been designed specifically to collect remotely sensed data of the entire earth. The basic concept of remotely sensed data depends upon observation electromagnetic radiation of the energy reflected or emitted from the feature of interest (Campbell, 2002). Geographic Information System (GIS) is a computer-based system designed to analyze spatial or geographical referenced data, which can deal with any type of information about the earth’s features (Campbell, 2002; Lillesand et al., 2004). Many studies have illustrated the efficacy of remotely sensed data utilisation as a powerful tool to spot land use/ land cover change, land use/ land cover mapping, urban planning, vegetation mapping, and hazard mapping (Saha et al., 2005; Sun et al., 2005). The advantages of remotely sensed data and GIS were showed by Nirupama (2002); it can be effectively used for quickly assessing the severity and impact of damage due to a natural disaster such as tsunami, planning escape routes, locating shelters for victims during the disaster, rapidly identifying hardest-hit disaster areas in order to provide evacuation and warning, and monitoring reconstruction and rehabilitation after the disaster. There are several methods used for mitigating property damage and loss of life that a tsunami might cause, particularly if the tsunami if of the tele-tsunami type. In the case of a local tsunami, where the tsunamigenic source is not far away from the seashore, the mitigation warning system might not be that effective due to the time needed for the evacuation process. Torrence and Grattan (2002) state that with any strong earthquake, roaring sounds that resemble gunfire, along with an unusual reduction of the sea level - below the normal low water mark - are the warning signs of a tsunami. Actions that are needed to reduce tsunami damage include installing hydrostatic pressure sensors in the sea floor, employing artificial satellites to improve tsunami warning systems, and, using the zoning technique to estimate the tsunami risk (OLoughlin & Lander, 2003). Ramasamy et al (2006) stated that the mangrove forests on the coastal areas played a crucial role in reducing the effect of the 2004 tsunami that hit South Asia. In the study carried out by Ramasamy and colleagues (2006), the mangroves were attributed with absorbing the tsunamis power and reducing the speed of tsunami waves. As a result, no lives were lost nor property damage sustained in T.S Pettai, India. As mangroves can absorb the impact of the tsunami waves, specifically engineered buildings can play the same role, but with specific conditions such as the location and the foundation of the building in addition to the tsunami magnitude. Zobel et al (2007) stated that the building with two (or more) stories have potentially better survivability, subject to sufficient robustness on the first (ground) floor. In addition, for the building to survive the high pressure of the tsunami wave, the first floor and its base should be designed to resist the tsunami risk. REFERENCES Anderson, J. G. 1991. Strong motion seismology. Review of Geophysics, 29(2):700-720 Campbell, J. B. 2002. Introduction to Remote Sensing, 3rd edition. New York: The Guilford Press. Erdik, M. & E. Durukal. 2003. Simulation modeling on strong ground motion. In: Earthquake engineering handbook. CRC press LLC. Kanamori, H. 1972. Mechanism of tsunami earthquakes. North Holland Publishing Company, Amsterdam. Keller, E. A., & Blodgett, R. H. 2006. Natural hazards: earths processes as hazards, disasters, and catastrophes. Pearson/Prentice Hall, Inc. Lillesand, T. M., Kiefer, R. W., and Chipman, J. W. 2004. Remote Sensing and Image Interpretation. 5th edition. New York: John Wiley & Sons Inc. McKinney, M., Schoch, R., Yonavjak L. 2007. Environmental science: systems and solutions, Jones & Bartlett Learning O’Loughlin, K. F., & Lander, J. F. 2003. Caribbean tsunamis: A 500-year history from 1498-1998. Advances in natural and technological hazards research, v. 20. Dordrecht: Kluwer Academic. Pacific Disaster Center (PDC). 2002. Retrieved Oct 14, 2010 from < http://www.pdc.org/iweb/tsunami.jsp?subg=1> Ramasamy, S., Kumanan, C. K., Sivakumar, B. R., & Singh, B. (2006). Geomatics in Tsunami.New Delhi: New India Publication Agency. Saha, A. K., Arora, M. K., Csaplovics, E., and Gupta, R. P. 2005. Land Cover Classification using IRS LISS III Image and DEM in a Rugged Terrain: A Case Study in Himalayas. Geocarto International 20(2): 33-40. Sun, W., Kelly, M., and Gong, P. 2005. Separation of Dead Tree Crowns from the Oak Woodland Forest Mosaic by Integrating Spatial Information. Geocarto International, 20(2):15-20. Tsunami early warning system. (2010). Tsunamis in history. Retrived Oct 14, 2010 from Torrence, R., & Grattan, J. 2002. Natural disasters and cultural change. One world archaeology, 45. London: Routledge. Zobel, R. Tandayya, P. & Duerrast, H. 2007. Affordable Strategies for the Reduction of Future Tsunami Effects on LocalPopulations in Phuket, Krabi and Phang Nga, Southern Thailand. 2007. Proceedings of the First Asia International Conference on Modelling & Simulation (AMS). Retrieved Oct 14, 2010 from IEEE Xplore. Read More