Estimated Tsunami Arrival Times for the Ambon Bay Area, Indonesia: Linking Tsunami Hazards Information to the City’s Evacuation Readiness

Abstract

Abstract The Ambon Bay Area, with the current population of around 350,000 in Ambon City located along the Bay, has a central function from the perspectives of geography and economic activities in Eastern Indonesia, but also the Bay is surrounded by a number of tectonic and non-tectonic tsunami sources, with insufficient information that could be integrated into a city-wide evacuation procedure for Ambon City. This study is aimed at estimating tsunami arrival times based on deterministic tsunami modeling, assessing tsunami evacuation readiness of the communities and inland facilities for city-wide evacuation. Two main methods are applied in this research, first by simulating a numerically deterministic model of a tsunami, and second by assessing the community’s perceptions on their readiness to evacuate should any tsunami happen. Tsunami simulations were performed using the Cornell Multi-Grid Coupled Tsunami Model (COMCOT). Bathymetry data were taken from GEBCO and Admiralty charts published by PUSHIDROSAL (Hydro-Oceanographic Center, Indonesian Navy). The simulations took four historical tsunamis sources, namely from Tanimbar trough (two events), Weber Sea, and from Banda Detachment. The results show that the shortest arrival time was around 37 minutes and it was indicated at the eastern part of the bay. Meanwhile, at some major populated areas around the bay, the shortest arrival times were between 42 and 56 minutes. However, tsunami evacuation routes in the city have not been fully identified. Only one siren tower is available and it is not enough to reach the whole city area, and only around 20% of the research respondents have participated in tsunami evacuation drills. Most of the respondents were obtained for the tsunami awareness information from places of worship. Essentially, concerns are over the absence of emergency traffic management facilities and insufficient tsunami early warning facilities (such as sirens).