RAPID TSUNAMI INUNDATION MODELLING FORECAST USING PRE-COMPUTED EARTHQUAKE SCENARIOS AND OCEAN BOTTOM PRESSURE GAUGE (OBPG) DATA CASE STUDY: YOGJAKARTA INTERNATIONAL AIRPORT (YIA) - Weniza
Currently most of the tsunami warning systems in the world including Indonesia only provide information on the estimated tsunami height, arrival time along the coast and level of tsunami threat. This information may not be sufficient for the coastal community and emergency respon agency in evacuation area. For this reason, studies on the development of tsunami inundation forecasting models in the tsunami warning system has been conducted using various methods and approaches. We propose a method for developing Near-Field Tsunami Inundation Forecasting (NearTIF). We combine the inversion method with the original NearTIF to obtain a more accurate tsunami source, utilizing Ocean Bottom Pressure Gauge (OBPG) data. We use Mw8.5 hypothetical earthquake located in the Java megathrust to assess the optimum time window of OBPG data for inversion with a smoothing factor. The 15-minute time series data obtained a goodfit fault slip distribution, indicated by high correlation and low Root Mean Square Error (RMSE), which means the bias of the prediction model is also low. Additionally, Green’s function based on tsunami waveform predictions is the substitute for the low-resolution forward modeling part of the original NearTIF to acquire inundation forecasts in less computational time. The 330 pre-computed tsunami scenario, using a non-linear numerical model, is employed for matching and shifting between observed and pre-computed waveform in the 15 virtual observation point along the Kulon Progo coast, the area of interest, using five hypothetical sources varying from Mw8.5 to Mw8.9. The Aida number (K) implies that the developed NearTIF gives accuracy in the acceptable range (0.6<K<1.4) in less than 2 minutes after the tsunami recorded in the OBPG. In the future the technique presented in this paper could provide near real-time tsunami inundation forecast in Indonesia Tsunami Early Warning System (InaTEWS).