A two-stage framework for a large-scale probabilistic tsunami inundation hazard assessment: A study case for the southern coast of Java, Indonesia

Producing a probabilistic tsunami hazard assessment (PTHA) at an inundation level for a large-scale region is computationally demanding. The main reasons are the vast number of scenarios and the high spatial resolution in coastal areas required. Various methodologies have been proposed to overcome these challenges. However, they are limited to local scales or specific sites. In addition, the scarcity of high quality and accuracy of digital elevation model (DEM) that create this task is even more expensive. Here, we applied a two-stage framework to perform a large-scale inundation PTHA and utilised open sources DEM from BATNAS [1] and DeltaDTM [2]. As a pilot study area, we focused on the southern coast of Java Island, Indonesia, covering over 1,000 km length of coastal area. This region has high potential tsunami from the Java megathrust earthquake with high density population at several locations.

At the first stage, we focused on simulating offshore tsunami propagation in a low-resolution configuration model using the JAGURS code [3]. Further, tsunami elevation timeseries at 10 m isobath were extracted and used as boundary conditions for high-resolution inundation modelling at the second stage utilising the SFINCS code [4]. We generated a synthetic earthquake event catalogue by adopting a space-time Epidemic-Type Aftershock Sequence (ETAS) model [5] and coupled it with heterogenous earthquake slip models [6].

This is a proposed modular framework where we could strategically adjust the configuration as needed to suit a range of risk-based applications and the facilities availability. For example, users might apply other hydrodynamic software for the simulations, consider different tsunamigenic sources, and refine the Stage 2 results by incorporating a better quality of DEM without redo the whole processes. Finally, it enables us to progressively develop a national, regional, or even at a global level in parallel processes.  

 

References: [1] BATNAS: https://tanahair.indonesia.go.id/portal-web/; [2] DeltaDTM: https://doi.org/10.4121/21997565; [3] JAGURS: https://github.com/jagurs-admin/jagurs/; [4] SFINCS: https://github.com/Deltares/SFINCS/tree/v2.1.1_Dollerup_release/; [5] Petrillo, G., & Zhuang, J. (2024). Bayesian earthquake forecasting approach based on the Epidemic Type Aftershock Sequence model. Earth, Planets and Space, 76(1), 78; [6] RPTHA to generate random slip models: https://github.com/GeoscienceAustralia/ptha