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Copyright © The Author(s) 2022. Eastern Mediterranean Sea has experienced four tsunamigenic earthquakes since 2017, which delivered moderate damage to coastal communities in Turkey and Greece. The most recent of these tsunamis occurred on 30 October 2020 in the Aegean Sea, which was generated by an Mw 7.0 normal-faulting earthquake, offshore Izmir province (Turkey) and Samos Island (Greece). The earthquake was destructive and caused death tolls of 117 and 2 in Turkey and Greece, respectively. The tsunami produced moderate damage and killed one person in Turkey. Due to the semi-enclosed nature of the Aegean Sea basin, any tsunami perturbation in this sea is expected to trigger several basin oscillations. Here, we study the 2020 tsunami through sea level data analysis and numerical simulations with the aim of further understanding tsunami behavior in the Aegean Sea. Analysis of data from available tide gauges showed that the maximum zero-to-crest tsunami amplitude was 5.1–11.9 cm. The arrival times of the maximum tsunami wave were up to 14.9 h after the first tsunami arrivals at each station. The duration of tsunami oscillation was from 19.6 h to > 90 h at various tide gauges. Spectral analysis revealed several peak periods for the tsunami; we identified the tsunami source periods as 14.2–23.3 min. We attributed other peak periods (4.5 min, 5.7 min, 6.9 min, 7.8 min, 9.9 min, 10.2 min and 32.0 min) to non-source phenomena such as basin and sub-basin oscillations. By comparing surveyed run-up and coastal heights with simulated ones, we noticed the north-dipping fault model better reproduces the tsunami observations as compared to the south-dipping fault model. However, we are unable to choose a fault model because the surveyed run-up data are very limited and are sparsely distributed. Additional researches on this event using other types of geophysical data are required to determine the actual fault plane of the earthquake. National Science Foundation under Cooperative Support Agreement; Royal Society

Tsunami potential from high dip-angle splay faults is an understudied topic, although such splay faults can significantly amplify coastal tsunami heights as compared with ordinary thrust faults. Here, we identify a hotspot for tsunamis from splay faulting in the Molucca Sea arc–arc collision zone in eastern Indonesia, which accommodates one of the world’s most complicated tectonic settings. The November 2019 Mw 7.2 earthquake and tsunami are studied through teleseismic inversions assuming rupture velocities in the range 1.5–4.0 km/s followed by tsunami simulations. The normalized root mean square error index was applied and revealed that the best model has a rupture velocity of 2.0 km/s from the steeply dipping plane. The recent high dip-angle reverse 2019 Mw 7.2 and 2014 Mw 7.1 earthquakes combined with numerous similar seismic events may indicate that this region is prone to splay faulting. This study highlights the need for understanding tsunamis from splay faulting in other subduction zones.

An M7.0 earthquake followed by moderate tsunami destructed Majene region, western Sulawesi on 23 February 1969. This event claimed at least 64 lives and caused severe damage to infrastructure. In this study, we reconstructed the earthquake and tsunami source of this event by optimising macroseismic and tsunami dataset reported as well as analysed the earthquake focal mechanism. We estimated that the maximum intensity of the earthquake was VIII (in Modified Mercalli Intensity). From the first motion polarity analysis, the earthquake had a thrust mechanism which was plausibly from the Makassar Thrust. Further, deterministic ground motion modelling successfully fits the intensity data. However, thrust earthquake from the Makassar Thrust was unable to reconstruct 4 m tsunami height observed at Pelattoang. The estimated ratio between maximum tsunami run-up height and lateral distribution distance (I2) from the dataset indicates that the tsunami was generated by a local coastal landslide.(This study is funded by the Royal Society (UK) grant number CHL/R1/180173)

Supplementary data: The following is the Supplementary data to this article: Acrobat PDF file (2MB) available at: https://ars.els-cdn.com/content/image/1-s2.0-S2212420921007329-mmc1.pdf Copyright © 2022 The Authors. Very large tsunamis are associated with low probabilities of occurrence. In many parts of the world, these events have usually occurred in a distant time in the past. As a result, there is low risk perception and a lack of collective memories, making tsunami risk communication both challenging and complex. Furthermore, immense challenges lie ahead as population and risk exposure continue to increase in coastal areas. Through the last decades, tsunamis have caught coastal populations off-guard, providing evidence of lack of preparedness. Recent tsunamis, such as the Indian Ocean Tsunami in 2004, 2011 Tohoku and 2018 Palu, have shaped the way tsunami risk is perceived and acted upon. Based on lessons learned from a selection of past tsunami events, this paper aims to review the existing body of knowledge and the current challenges in tsunami risk communication, and to identify the gaps in the tsunami risk management methodologies. The important lessons provided by the past events call for strengthening community resilience and improvement in risk-informed actions and policy measures. This paper shows that research efforts related to tsunami risk communication remain fragmented. The analysis of tsunami risk together with a thorough understanding of risk communication gaps and challenges is indispensable towards developing and deploying comprehensive disaster risk reduction measures. Moving from a broad and interdisciplinary perspective, the paper suggests that probabilistic hazard and risk assessments could potentially contribute towards better science communication and improved planning and implementation of risk mitigation measures. COST (European Cooperation in Science and Technology); Royal Society, UK (grant number CHL\R1\180173); Severo Ochoa Centers of Excellence Program (CEX 2018-000797-S) funded by MCIN/ AEI /10.13039/501100011033; Lloyd's Tercentenary Research Foundation, the Lighthill Risk Network, and the Lloyd's Register Foundation-Data Centric Engineering Programme of the Alan Turing Institute.

© Copyright 2021 The Author(s). We studied the February 23rd, 1969 M7.0 Majene, Sulawesi earthquake and tsunami. It was followed by tsunami reported at five locations. At least 64 people were killed and severe damage on infrastructures were reported in Majene region. Based on damage data, we estimated that the maximum intensity of the earthquake was MMI VIII. Focal mechanisms, derived using first motion polarity analysis, indicated that the earthquake had a thrust mechanism. Furthermore, we built hypothetical earthquake scenarios based on a rectangular fault plane of 40 km × 20 km with a homogeneous slip model of 1.5 m. We run the Open Quake and the JAGURS code to validate the macroseismic and tsunami observation data, respectively. Our best-fitted earthquake model generates maximum intensity of 8+ which is in line with the reported macroseismic data. However, the maximum simulated tsunami height from all scenario earthquakes is 2.25 m which is smaller than the 4 m tsunami height observed at Pelattoang. The possibility of contribution of another mechanism to tsunami generation requires further investigation. Royal Society, UK (grant number CHL\R1\180173).

We present an analysis of the oldest detailed account of tsunami run-up in Indonesia, that of the 1674 Ambon tsunami (Rumphius in Waerachtigh Verhael van de Schuckelijcke Aerdbebinge, BATAVIA, Dutch East Indies, 1675). At 100 m this is the largest run-up height ever documented in Indonesia, and with over 2300 fatalities even in 1674, it ranks as one of Indonesia’s most deadly tsunami disasters. We consider the plausible sources of earthquakes near Ambon that could generate a large, destructive tsunami, including the Seram Megathrust, the South Seram Thrust, and faults local to Ambon. We conclude that the only explanation for the extreme run-up observed on the north coast of Amon is a tsunami generated by an earthquake-triggered coastal landslide. We use a two-layer tsunami model to show that a submarine landslide, with an approximate volume of 1 km3, offshore the area on Ambon’s northern coast, between Seith and Hila, where dramatic changes in coastal landscape were observed can explain the observed tsunami run-up along the coast. Thus, the 1674 Ambon tsunami adds weight to the evidence from recent tsunamis, including the 1992 Flores, 2018 Palu and Sunda Strait tsunamis, that landslides are an important source of tsunami hazard in Indonesia.

Eastern Indonesia is one of the world’s most complex regions in terms of tsunami hazards, as it accommodates numerous seismic and non-seismic tsunami sources with a history of deadly tsunamis. This study is an effort to enhance tsunami hazard knowledge in eastern Indonesia where limited data and analyses exist. We provide a brief understanding of eastern Indonesia’s tsunami hazards by modelling selected deterministic tsunami scenarios from tectonic, submarine mass failure (SMF), and volcanic sources. To our knowledge, this is the first time that tsunami hazards modelling from such diverse sources in Indonesia has been performed. Our methodology is a deterministic tsunami hazard analysis considering credible tsunami sources from historical and contemporary data, modelling them using state-of-the-art simulation tools. We modelled two Mw7.8 tsunamigenic earthquake scenarios on the Flores back-arc thrust, one rupturing the basal fault (FBT-BF) and the other rupturing the splay fault (FBT-SF), showing that the two scenarios produce maximum tsunami amplitudes of$$\sim$$∼5.3 m and$$\sim$$∼4.2 m, respectively, which are comparable to the deadly 1992 Flores tsunami. We modelled potential SMF-generated tsunamis in the Makassar Strait with SMF volumes of 5$$\hbox {km}^3$$km3and 225$$\hbox {km}^3$$km3which yielded maximum tsunami heights of$$\sim$$∼1.1 m and$$\sim$$∼4.3 m along the eastern coast of Kalimantan Island and$$\sim$$∼2.9 m and$$\sim$$∼11.1 m along the west shore of Sulawesi Island, respectively. The 1871 Ruang volcanic tsunami is studied through existing historical documents and a source model is proposed comprising a flank collapse with volume of$$0.10\ \mathrm{km}^3$$0.10km3. Such a source model successfully reproduced the 25 m runup reported in a historical account.

The 30 October 2020 tsunami in the Aegean Sea was generated by an Mw 7.0 normal-faulting earthquake at a depth of 21 km. The earthquake epicenter was near the city of Izmir (Turkey) in the Aegean Sea and left 117 fatalities in Turkey and two deaths in Greece. A moderate tsunami was generated, which attacked the nearby coast of Turkey and the north coast of Samos island, Greece. A maximum runup height of ~3.8 m was observed in Akarca with extensive inundation at the low elevation nearshore areas of the small bays from Akarca (South) to Alacati (North) of the central Aegean coast of Turkey (field surveys by Yalciner et al., 2020). The maximum tsunami penetration was ~2500 m along Azmak streambed at Alacati, Turkey. One casualty and at least one injury were directly attributed to the tsunami in Sigacik, Turkey. The predecessors of this event were other normal-faulting events: i) Lesvos-Karaburun (Mw 6.3) earthquake (Greece-Turkey) on 12 June 2017 approximately 110 km to the North-northwest, and ii) Bodrum-Kos (Mw 6.6) earthquake (Turkey-Greece) on 20 July 2017 approximately 110 km to the south-southeast of the epicenter of the 30 October 2020 event. The events of 2017 and 2020 show high similarities in terms of faulting mechanism and tsunami-genesis. The tsunami generated by the last event caused extensive loss of properties and damage to marine vessels. Here, we study the 30 October 2020 tsunami through analysis of eight tide gauge records as well as numerical simulations. Tide gauge data revealed that the tsunami’s zero-to-crest amplitudes, on tide gauges, was in the range of 5 – 12 cm with maximum amplitude (12 cm) recorded at Kos (Greece). The tsunami duration was unusually long and varied from 20 h to 35 h. Such long tsunami oscillations are not expected from an Mw 7.0 normal-faulting tsunamigenic earthquake and can be most likely attributed to several reflections due to the confined nature of the Aegean Sea region. We conducted Fourier and Wavelet analyses to detect tsunami’s spectral characteristics. Our tsunami simulation was able to reproduce most features of the recorded waves both in terms of amplitudes and duration. This research is suported by Royal Society (UK), grant number CHL/R1/180173.

We revisit the source of the 1992 Flores earthquake and tsunami using finite-fault inversion. We simultaneously invert teleseismic body and surface waves together with coseismic uplift/subsidence datasets. We then verify the inverted source against tsunami run-up heights along the northern coast of Flores Island and the only tide gauge recording of the tsunami. Our preferred source model provides a good fit to all the datasets, whereas previous models only explained a subset of the available data. We show that the fault geometry implies segmentation of the back-arc thrust system in the eastern Sunda Arc.

As the world's largest archipelagic country in Earth's most active tectonic region, Indonesia faces a substantial earthquake and tsunami threat. Understanding this threat is a challenge because of the complex tectonic environment, the paucity of observed data and the limited historical record. Here we combine information from recent studies of the geology of Indonesia's Banda Sea with Global Positioning System observations of crustal motion and an analysis of historical large earthquakes and tsunamis there. We show that past destructive earthquakes were not caused by the supposed megathrust of the Banda outer arc as previously thought but are due to a vast submarine normal fault system recently discovered along the Banda inner arc. Instead of being generated by coseismic seafloor displacement, we find the tsunamis were more likely caused by earthquake-triggered submarine slumping along the fault's massive scarp, the Weber Deep. This would make the Banda detachment representative not only as a modern analogue for terranes hyper-extended by slab rollback but also for the generation of earthquakes and tsunamis by a submarine extensional fault system. Our findings suggest that low-angle normal faults in the Banda Sea generate large earthquakes, which in turn can generate tsunamis due to earthquake-triggered slumping. Low-angle normal faults in the Banda Sea have caused large earthquakes that indirectly generated tsunamis due to earthquake-triggered submarine slumping, according to an analysis of historical earthquake and tsunami events and GPS observations.

Probabilistic hazard assessments are a fundamental tool for assessing the threats posed by hazards to communities and are important for underpinning evidence-based decision-making regarding risk mitigation activities. Indonesia has been the focus of intense tsunami risk mitigation efforts following the 2004 Indian Ocean tsunami, but this has been largely concentrated on the Sunda Arc with little attention to other tsunami prone areas of the country such as eastern Indonesia. We present the first nationally consistent probabilistic tsunami hazard assessment (PTHA) for Indonesia. This assessment produces time-independent forecasts of tsunami hazards at the coast using data from tsunami generated by local, regional and distant earthquake sources. The methodology is based on the established monte carlo approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. We account for sources of epistemic and aleatory uncertainty in the analysis through the use of logic trees and sampling probability density functions. For short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, south coast of Java and the north coast of Papua. For longer return periods (500–2500 years), the tsunami hazard is highest along the Sunda Arc, reflecting the larger maximum magnitudes. The annual probability of experiencing a tsunami with a height of > 0.5 m at the coast is greater than 10% for Sumatra, Java, the Sunda islands (Bali, Lombok, Flores, Sumba) and north Papua. The annual probability of experiencing a tsunami with a height of > 3.0 m, which would cause significant inundation and fatalities, is 1–10% in Sumatra, Java, Bali, Lombok and north Papua, and 0.1–1% for north Sulawesi, Seram and Flores. The results of this national-scale hazard assessment provide evidence for disaster managers to prioritise regions for risk mitigation activities and/or more detailed hazard or risk assessment.

In order to reliably assess tsunami hazard in eastern Indonesia, we need to understand how historical events were generated. Here we consider two such events: the 1674 Ambon and the 1992 Flores tsunamis. Firstly, Ambon Island suffered a devastating earthquake that generated a tsunami with 100 m run-up height on the north coast of the island in 1674. However, there is no known active fault around the island capable of generating such a gigantic wave. Rumphius’ report describes that the initial wave was coming from three villages that collapsed immediately after the earthquake with width as far as a musket shot. Moreover, a very high tsunami was only observed locally. We suspect that a submarine landslide was the main cause of the gigantic tsunami on the north side of Ambon Island. Unfortunately, there is no data available to confirm if landslide have occurred in this region. Secondly, several tsunami source models for the 1992 Flores event have been suggested. However, the fault strike is quite different compare to the existing Flores back-arc thrust and has not been well validated against a tide gauge waveform at Palopo, Sulawesi. We considered a tsunami model based on Griffin, et al., 2015, extended with high resolution bathymetry laround Palopo, in order to validate the latest tsunami source model available. In general, the model produces a good agreement with tsunami waveforms, but arrives 10 minutes late compared to observed data. In addition, the source overestimates the tsunami inundation west of Maumere, and does not account for the presumed landslide tsunami on the east side of Flores Island.

Disaster preparedness activities aim to reduce the impact of disasters by being better prepared to respond when a disaster occurs. In order to better anticipate requirements during a disaster, contingency planning activities can be undertaken prior to a disaster based on a realistic disaster scenario. InaSAFE is a tool that can inform this process. InaSAFE is a free and open source software that estimates the impact to people and infrastructure from potential hazard scenarios. By using InaSAFE, disaster managers can develop scenarios of disaster impacts (people and infrastructures affected) to inform their contingency plan and emergency response operation plan. While InaSAFE provides the software framework exposure data and hazard data are needed as inputs to run this software. Then InaSAFE can be used to forecast the impact of the hazard scenario to the exposure data. InaSAFE outputs include estimates of the number of people, buildings and roads are affected, list of minimum needs (rice and clean water), and response checklist. InaSAFE is developed by Indonesia’s National Disaster Management Agency (BNPB) and the Australian Government, through the Australia-Indonesia Facility for Disaster Reduction (AIFDR), in partnership with the World Bank – Global Facility for Disaster Reduction and Recovery (GFDRR). This software has been used in many parts of Indonesia, including Padang, Maumere, Jakarta, and Slamet Mountain for emergency response and contingency planning.

[1] The Mw 7.8 October 2010Mentawai, Indonesia, earthquake was a“tsunami earthquake,” a rare type of earthquake that generates a tsunami much larger than expected based on the seismicmagnitude.Itproducedalocallydevastatingtsunami,withrunupcommonlyinexcess of 6 m. We examine this event using a combination of high-rate GPS data, from instruments located on the nearby islands, and a tsunami field survey. The GPS displacement time series are deficient in high-frequency energy, and show small coseismic displacements ( 16 m. Our modeling results show that the combination of the small GPS displacements and large tsunami can only be explained by high fault slip at very shallow depths, far from the islands and close to the oceanic trench. Inelastic uplift of trench sediments likely contributed to the size of the tsunami. Recent results for the 2011 Mw 9.0 Tohoko-Oki earthquake have also shown shallow fault slip, but the results from our study, which involves a smaller earthquake, provide much stronger constraints on how shallow the rupture can be, with the majority of slip for the Mentawai earthquake occurring at depths of