TSUNAMI EARLY WARNING SYSTEM BASED ON TOHOKU MODEL FOR TSUNAMI PREDICTION
The early availability of earthquake information and Tsunami prediction is very important to Tsunami warning authority. As Tsunamis occurred in Indonesia are local Tsunamis, a short processing time to predict Tsunami characteristics is very important for making decision to issue a warning and still...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/9654 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The early availability of earthquake information and Tsunami prediction is very important to Tsunami warning authority. As Tsunamis occurred in Indonesia are local Tsunamis, a short processing time to predict Tsunami characteristics is very important for making decision to issue a warning and still have enough time to evacuate. Indonesia has not have an integrated warning system yet which can process earthquake data, predict the Tsunami, and publish the warning in time. This Thesis proposes an early warning system that has short processing time to predict Tsunami arrival time based on Tohoku model from University of Japan. <br />
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The Early Tsunami Warning System receives earthquake information from PGN System’s Data Feeder. The system is able to determine the presence or absence of a Tsunami in order to issue or cancel a Tsunami warning. If there is a possibility of the presence of Tsunami, it is able to rapidly predict the arrival time of Tsunami using the model. Earthquake information and Tsunami prediction dissemination from this system is provided through web-based platform to ease early warning authority to interact with the system. Client-Server system is used to help the early warning authority to control the system from a single platform. The system can interact with other supporting early warning system to disseminate Tsunami alarm to all related entities. <br />
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Referring to the functional specifications, the prototype of the Tsunami Early Warning System fulfils the requirements to be able to read earthquake data and corrected data, to check the type of the earthquake, and to automatically publish the result on the web. Test result shows the prototype needs only less than two minutes to predict the Tsunami arrival time at observed locations. The fulfilment of the user requirements in the prototype makes further development of the system to be used in the real user environment. <br />
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