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This study reports on recent developments of the Indonesia Tsunami Early Warning System (InaTEWS), specifically the tsunami modeling components used in the system. It is a dual system: firstly, InaTEWS operates a high-resolution scenario database pre-computed with the finite element model TsunAWI; running in parallel, the system also contains a supra real-time modeling component based on the GPU-parallelized linear long-wave model easyWave, capable of dealing with events outside the database coverage. The evolution of the tsunami scenario database over time is covered in the first sections also touching on the involved capacity building efforts. Starting with a coverage of just the Sunda Arc region, the database now includes scenarios for 15 fault zones. The study is augmented by an investigation of warning products used for early warning; the estimated wave height (EWH) and the estimated time of arrival (ETA). These parameters are determined by easyWave and TsunAWI with model specific approaches. Since the numerical setup of the two models is very different, the extent of variations in warning products is investigated for a number of scenarios, where both pure database scenarios and applications to real events are considered. Finally, the performance of the system in past tsunami events is reviewed to point out major system updates. [ABSTRACT FROM AUTHOR]

The various uncertainties in the earthquake-triggered tsunami threat assessment are difficult to quantify and/or integrate into the tsunami early warning process. Uncertainties in the (seismic) input parameters and the lack of knowledge about the earthquake slip distribution contribute most to the total uncertainty in real-time evaluated tsunami assessment. We present a method how to integrate and quantify these uncertainties in the warning process by evaluating a tsunami warning level probability distribution with a Bayesian network (BN) approach. As soon as an earthquake is detected, the seismic source parameter estimates are evaluated and a probabilistic overview on different tsunami warning levels is provided, feasible to support a decision maker at a warning center with important additional data. A BN system has been developed exemplarily for the region Sumatra. In this paper, we describe the method of BN generation by ancestral sampling, we critically analyse the assumptions made and weight the pro and cons of the BN approach. A case study demonstrates the workflow of the BN system in real-time and reveals the promising power of a BN analysis in the framework of early warning. [ABSTRACT FROM AUTHOR]

We present the GITEWS approach to source modeling for the tsunami early warning in Indonesia. Near-field tsunami implies special requirements to both warning time and details of source characterization. To meet these requirements, we employ geophysical and geological information to predefine a maximum number of rupture parameters. We discretize the tsunamigenic Sunda plate interface into an ordered grid of patches (150×25) and employ the concept of Green's functions for forward and inverse rupture modeling. Rupture Generator, a forward modeling tool, additionally employs different scaling laws and slip shape functions to construct physically reasonable source models using basic seismic information only (magnitude and epicenter location). GITEWS runs a library of semi- and fully-synthetic scenarios to be extensively employed by system testing as well as by warning center personnel teaching and training. Near realtime GPS observations are a very valuable complement to the local tsunami warning system. Their inversion provides quick (within a few minutes on an event) estimation of the earthquake magnitude, rupture position and, in case of sufficient station coverage, details of slip distribution. [ABSTRACT FROM AUTHOR]

A new tsunami forecasting method for near-field tsunami warning is presented. This method is applied in the German-Indonesian Tsunami Early Warning System, as part of the Indonesian Tsunami Warning Center in Jakarta, Indonesia. The method employs a rigorous approach to minimize uncertainty in the assessment of tsunami hazard in the near-field. Multiple independent sensors are evaluated simultaneously in order to achieve an accurate estimation of coastal arrival times and wave heights within very short time after a submarine earthquake event. The method is validated employing a synthetic (simulated) tsunami event, and in hindcasting the minor tsunami following the Padang 30 September 2009 earthquake. [ABSTRACT FROM AUTHOR]

The Indonesian archipelago is known for the occurrence of catastrophic earthquake-generated tsunamis along the Sunda Arc. The tsunami hazard associated with submarine landslides however has not been fully addressed. In this paper, we compile the known tsunamigenic events where landslide involvement is certain and summarize the properties of published landslides that were identified with geophysical methods. We depict novel mass movements, found in newly available bathymetry, and determine their key parameters. Using numerical modeling, we compute possible tsunami scenarios. Furthermore, we propose a way of identifying landslide tsunamis using an array of few buoys with bottom pressure units. [ABSTRACT FROM AUTHOR]