Numerical Modeling of Tsunamis for Early Warning and Evacuation

Abstract

Its creation was prompted by the 2004 Indian Ocean earthquake and resuhing tsunami, which lel^; some 230,000 people dead or missing. Many analysts claimed that the disaster would have been mitigated if there had been an effective warning system in place, citing the wellestablished Hawaii-based Pacific Tsunami Warning Center, which operates in the Pacific Ocean. People in some areas would have had more than adequate time to seek safety if they were aware of the impending catastrophe. The only way to effectively mitigate the impact of a tsunami is through an early warning system.Other methods such as tsunami walls only work for a percentage of waves, but a warning system is effective for all waves originating outside a minimum distance from the coastline. Based on the above information, great attention was paid towards the Indian Ocean Tsunami Warning System. But the still Indian Tsunami Warning System has only two deep water buoys to detect the tsunami waves and two number of buoys are not enough to issue accurate warning at all. Due to this reasons, in most of the occations tsunami warnings had been issued for Indian Ocean countries including Sri Lanka, mainly based on the magnitude of the earchquake which causes the tsunami. This is a blind issue of warning such as the Sri Lankan experience in 2007 September tsunami. Therefore in order to issue a warning accurately and with confidence, there must be a properly developed thunami warning system. In this project, I'm going to develop such system for Sri Lanka considering the earthquake on Sunda fault, which lies in the Indonesian region. This fault is considered as a most critical fault for Sri Lanka. The selected region of the fault has divided in to several segments which act as tsunami sources. Tsunami modeling software "WinlTDB" is used to model the tsunami under each earthquake case. After runing the model for several magnitudes of earthquake for each source, wave heights and reaching time was measured at selected Six coastal points around the country. A database was created using the observed data for the analysis purpose. 11