For rapid forecast of tsunami inundation during a tsunamigenic event, we constructed pre-computed tsunami inundation database for Chimbote, which is one of the most populated cities in the north-central Peru and considered as a tsunami-prone area. The database consists of tsunami waveforms and modelled tsunami inundation areas based on a total of 165 fault model scenarios starting from 8.0 to 9.0 with an increment of 0.1 on moment magnitude scale (Mw). Following the methodology by Gusman et al. (2014) we evaluated the reliability of NearTIF algorithm using two hypothetical thrust earthquake scenarios: Mw 9.0 (worst-case event), Mw 8.5 (high probability of occurrence), and a finite fault model of the 1996 tsunami earthquake (Mw 7.6) offshore Chimbote. The linear tsunami propagation and nonlinear inundation were simulated with the JAGURS code implemented in a high-performance computer at Earthquake Information Center, Earthquake Research Institute, The University of Tokyo. This study demonstrated that NearTIF algorithm worked well even for tsunami earthquake scenario because it used a time shifting procedure for the best-fit fault model scenario searching. Finally, we evaluated the lead time with NearTIF algorithm for purpose of tsunami warning in Chimbote. Comparison of computation time indicated that NearTIF only needed less than 20 seconds while direct numerical forward modeling required 27-45 minutes. We thus demonstrated that NearTIF was a suitable algorithm for developing a future tsunami inundation forecasting system in Chimbote and would give useful contribution to improve and strengthen the Peruvian Tsunami Warning Center in terms of obtaining in short time a forecast of tsunami inundation maps for analysis of evacuation and reduction of loss of life.
Keywords: Real-time tsunami inundation forecast, Chimbote Peru