Real-time tsunami inundation forecast system: Application of machine learning for matching algorithm

Recently NIED developed a new methodology of real-time tsunami inundation forecast system (Aoi et al., 2015, JpGU) using S-net (Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench). They constructed the Tsunami Scenario Bank (TSB) that contains offshore tsunami pre-calculated waveforms, coastal tsunami heights, flow depth maps, and others. If a tsunami occurs, the system will search tsunami scenarios from the TSB by matching the observed offshore tsunami waveforms and estimate a tsunami inundation. The matching algorithm using in the system is the multi-index method which was developed by Yamamoto et al. (2016, EPS). In this algorithm, the estimated results have variation because the algorithm picks up more than one tsunami scinario.