Automatic tsunami arrival detection algorithm for sea level observation system

Abstract

The automatic tsunami detection algorithm needs to be put in the sea level observation system to give society a quick warning when a tsunami happens. This study designs an automatic tsunami detection algorithm consisting of three sub-algorithm: spike elimination, gap data filling, and tsunami detection. Spike elimination and gap data filling are used to improve the sea level data, which is often disturbed by spikes and gap data due to electronic factors. This algorithm was tested using time-series tide gauge data that contain tsunami waveforms in Indonesia from 2007 to 2019. About 54.52 % of 409 spikes have been eliminated while the gap data were successfully filled. Furthermore, tsunami detection, which uses DART (Deep-ocean Assessment and Reporting of Tsunamis) and TEDA (Tsunami Early Detection Algorithm) methods, can detect 7 of 10 tsunami waveforms. However, there are three undetected tsunamis and one false detection. This algorithm has an average delay of 7.7 minutes in detection time.