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

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).

Introduction 

Tsunamis in recent decades have been regarded as one of the deadliest disasters in Indonesia, which has been hit by many tsunami events that killed more than 100,000 individuals (Sieh 2005; Papadopoulos et al. 2006), but to date there is no comprehensive understanding of the characteristics of tsunamis (KURITA et al. 2007). Every tsunami event results in new phenomena and new understandings of tsunamis. For example, the 2004 Indian Ocean tsunami shocked most disaster researchers concerning the potential disaster from a giant tsunami in the eastern basin of the Indian Ocean. The last two tsunami events, namely the 2018 Palu tsunami and the 2018 Mount Anak Krakatau tsunami (Indonesia), also created many theories on the impacts of tsunamis along coastal areas, and the way to understand the characteristics of tsunamis (Giachetti et al. 2012; Heidarzadeh et al. 2019a; Heidarzadeh et al. 2019b; Paris et al. 2020). The 2018 Palu tsunami occurred inside a long bay and it was caused by submarine landslide (Pakoksung et al. 2019). Extremely short arrival times left the coastal communities around the bay with a limited time window to evacuate (Syamsidik et al. 2020). This tsunami caused more than 400 deaths, as well as other cascading events around the same time of this event. Therefore, our understanding toward the characteristics of tsunami around a bay should be strengthened and developed further. A bay is often regarded as a safe location from impacts of extreme waves or weather, but this is not always the case, and this fact can lead to a mistaken understanding of a bay’s function in protecting areas within it from tsunamis. Therefore, researching the potential impacts of tsunamis in a bay area is essential. Further, assessing the bay community’s tsunami awareness would provide a more comprehensive way to increase the area’s readiness for the disaster. Ambon City is situated inside the Ambon Bay Area, similarly to the condition of Palu Bay, despite the geographical context, to the knowledge of the present authors there has been no research reporting on the impacts of any tsunami within the Ambon Bay Area. Further, it is noteworthy that Eastern parts of Indonesia receive less attention despite its tectonic complexities and multiple tsunami events in the past (Løvholt et al. 2012; Pranantyo dan Cummins 2020). This might be parallel to the economic growth and development whereby the geographical and cultural differences Page 3/23 divide eastern and western Indonesia. In the last century, there were a number of tsunamis around the Maluku islands of eastern Indonesian. Among the ways to strengthen the awareness of a coastal city to tsunamis, there is the provision of information related to tsunami estimated arrival times and the area of tsunami inundation (Muhari et al. 2012; Takagi et al. 2019; Jihad et al. 2021; Jihad et al. 2023). The connection between the number of casualties and tsunami arrival time could have an inverse correlation, as was found in the case of Sendai plain during the 2011 Great East Japan Earthquake and Tsunami (GEJET) (Latcharote et al. 2018). Tsunami arrival times within a bay area could be significantly influenced by the hydrodynamic condition of the tsunami in the bay, as in the case of the Palu 2018 tsunami (Husrin et al. 2020). By knowing tsunami arrival times, disaster managers and city planners could then set out a plan for tsunami evacuation in the city. It can be a good basis for determining evacuation routes, safe points, and also for designing tsunami evacuation buildings. Estimated tsunami arrival time (ETA) can be based on the cresttrough of the leading locked waves can present good results, as in the case of Hunga Tonga-Hunga Ha’apai 2022 tsunami (Ren et al. 2023) in the western South Pacific Ocean. The tsunami arrival times could also be connected to a community’s readiness in order to determine if the hazards information could be utilized by the readiness of the community at risk (Paton et al. 2008). They could also be aligned to the willingness of the community to respond to any incoming hazards with their provided capacities and facilities existing in the community. Therefore, coupling the ETA and the community readiness is essential to assess if both sides of the tsunami disaster could be connected properly. However, both sides of the tsunami information i.e. ETA and community’s readiness for Ambon Bay Area are not yet available. This study is aimed at coupling both ETA and tsunami readiness information for the Ambon Bay Area to increase tsunami awareness at this location. We employed a deterministic model of tsunami hazards based on a series of tsunamis that occurred in the past and struck the Ambon Bay Area. This article is expected to fill the gaps on tsunami research for eastern Indonesia and to promote ways to perceive tsunami readiness for a bay area.