Numerical Simulations of December 22, 2018 Anak Krakatau Tsunami and Examination of Possible Submarine Landslide Scenarios

Doğan, Gözde Güney; Annunziato, Alessandro; Hidayat, Rahman; Husrin, Semeidi; Prasetya, Gegar; Kongko, Widjo; Zaytsev, Andrey; Pelinovsky, Efim; Imamura, Fumihiko; Yalçıner, Ahmet Cevdet

doi:10.1007/s00024-020-02641-7

Cited by 21 publications

(10 citation statements)

References 56 publications

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“…A post-tsunami database has been established for the Sunda Strait area by Syamsidik et al (2019), Palu Bay by Paulik et al (2019), and Khao Lak-Phuket by Ruangrassamee et al (2006) and Foytong and Ruangrassamee (2007) in urban areas strongly affected by these events. These databases include 98, 371, and 120 observed flow depth traces at buildings, respectively.…”

Section: Post-tsunami Databasesmentioning

confidence: 99%

“…In Fig. 16, we compare (i) the Sunda Strait and Sulawesi-Palu ds 3 -curves based on the simulated tsunami intensity measures for confined masonry-type buildings, (ii) the 2004 Indian Ocean (Khao Lak-Phuket, Thailand) ds 3 -curve based on the observed flow depth for reinforced-concrete infilled frames buildings (Foytong and Ruangrassamee, 2007; Ros- setto Ruangrassamee et al, 2006), and (iii) the 2004 Indian Ocean (Banda Aceh, Indonesia) ds 3 -curves produced by Koshimura et al (2009a). The curves are based on a visual damage interpretation of remaining roofs using the pre-and post-tsunami satellite data (IKONOS) and are thus developed for mixed buildings (low-rise wooden, timberframed, and non-engineered reinforced concrete constructions; Koshimura et al, 2009a;Saatcioglu et al, 2006).…”

Section: Comparison Between the 2018 And 2004 Building Fragility Curvesmentioning

confidence: 99%

“…Here, we empirically developed building fragility curves for the 2018 Sunda Strait, 2018 Sulawesi-Palu, and Indian Ocean (Khao Lak-Phuket, Thailand) tsunamis based on the Global Earthquake Model (GEM) guidelines (Rossetto et al, 2014). From the field surveys conducted after the 2018 Sunda Strait (Syamsidik et al, 2019), 2018 Sulawesi-Palu (Paulik et al, 2019), and 2004 Indian Ocean (Khao Lak-Phuket, Thailand) (Foytong and Ruangrassamee, 2007;Ruangrassamee et al, 2006) events, we utilize three databases called DB_Sunda2018, DB_Palu2018, and DB_Thailand2004, respectively. In the literature, tsunami inundation modelling has been performed many times to better understand the tsunami hydrodynamics, especially for earthquake-generated tsunamis (Charvet et al, 2014;Gokon et al, 2011;Koshimura et al, 2009a;Macabuag et al, 2016;De Risi et al, 2017;Suppasri et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Characteristics of building fragility curves for seismic and non-seismic tsunamis: case studies of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean tsunamis

Lahcene

Ιωάννου

Suppasri

et al. 2021

Nat. Hazards Earth Syst. Sci.

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Abstract. Indonesia has experienced several tsunamis triggered by seismic and non-seismic (i.e., landslides) sources. These events damaged or destroyed coastal buildings and infrastructure and caused considerable loss of life. Based on the Global Earthquake Model (GEM) guidelines, this study assesses the empirical tsunami fragility to the buildings inventory of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean (Khao Lak–Phuket, Thailand) tsunamis. Fragility curves represent the impact of tsunami characteristics on structural components and express the likelihood of a structure reaching or exceeding a damage state in response to a tsunami intensity measure. The Sunda Strait and Sulawesi–Palu tsunamis are uncommon events still poorly understood compared to the Indian Ocean tsunami (IOT), and their post-tsunami databases include only flow depth values. Using the TUNAMI two-layer model, we thus reproduce the flow depth, the flow velocity, and the hydrodynamic force of these two tsunamis for the first time. The flow depth is found to be the best descriptor of tsunami damage for both events. Accordingly, the building fragility curves for complete damage reveal that (i) in Khao Lak–Phuket, the buildings affected by the IOT sustained more damage than the Sunda Strait tsunami, characterized by shorter wave periods, and (ii) the buildings performed better in Khao Lak–Phuket than in Banda Aceh (Indonesia). Although the IOT affected both locations, ground motions were recorded in the city of Banda Aceh, and buildings could have been seismically damaged prior to the tsunami's arrival, and (iii) the buildings of Palu City exposed to the Sulawesi–Palu tsunami were more susceptible to complete damage than the ones affected by the IOT, in Banda Aceh, between 0 and 2 m flow depth. Similar to the Banda Aceh case, the Sulawesi–Palu tsunami load may not be the only cause of structural destruction. The buildings' susceptibility to tsunami damage in the waterfront of Palu City could have been enhanced by liquefaction events triggered by the 2018 Sulawesi earthquake.

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Section: Post-tsunami Databasesmentioning

confidence: 99%

Section: Comparison Between the 2018 And 2004 Building Fragility Curvesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characteristics of building fragility curves for seismic and non-seismic tsunamis: case studies of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean tsunamis

Lahcene

Ιωάννου

Suppasri

et al. 2021

Nat. Hazards Earth Syst. Sci.

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“…The volume of landslide debris material, the process of movement of the landslide debris material and the slope of the mountain slopes are the parameters that most influence the characteristics of the tsunami. The steeper slopes of the mountains will cause landslides to move faster into the water, causing high water waves in the form of tsunamis [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]. The high number of deaths from these events is related to the limited literature on tsunami generation from mechanisms other than fault damage and the lack of an effective tsunami warning system for non-seismic events [31].…”

Section: Introductionmentioning

confidence: 99%

The Development Study of the Drag Coefficient of Solid Cylinder on Inclined Plane in Water

Ariefka

Pramudya

2022

Trends Sci

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The dynamic resistance of a fluid to a cylinder rolling on an inclined plane in water has been experimentally studied. This creates problems in the form of solid-liquid interactions, which include landslides on the seabed and debris flows on the seabed that cause Tsunamis. The development of flow around a rolling cylinder is described to highlight the implications on the nature of the hydrodynamic force coefficient acting on the cylinder as resistance. The coefficient of drag on the cylinder when rolling on an inclined plane in water is the coefficient of drag that prevents the cylinder from rolling. In addition, other external force coefficients (besides the drag coefficient) also impede the cylinder motion. The equation of motion of the cylinder is solved with experimental data which is used as the most suitable solution to get the drag coefficient value. The movement of the cylinder is also not perfectly linear because there is a force from the side of the track and the cylinder moves slightly zigzag in 1-D motion. HIGHLIGHTS In this study, we present the experimental results of cylindrical drag coefficients of various materials on inclined planes in water as modeling of broader scientific problems, especially the potential for hydrometeorological and sedimentation disasters Fluid dynamics of the cylinder drag force on an inclined plane in water were measured experimentally The motion of the cylinder on an inclined plane in water is recorded, then the recorded video is processed using Logger Pro to obtain experimental time, speed, and position data which is processed using the appropriate mathematical equations GRAPHICAL ABSTRACT

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“…A landslide with a volume of \ * 0.2 km 3 estimated from synthetic aperture radar and broadband seismic observations, has been considered as the source of the tsunami (Ye et al, 2020). Dogan et al (2021) hypothesized a flank collapse scenario with a volume of 0.25 km 3 as a combination of submarine and subaerial mass movement as the best scenario for the source mechanism capable of explaining the observed coastal amplitudes, but subject to uncertainties in the numerical modeling due to rheology of the collapsed material, the reflection effects of coastal topography, and the role of coastal protection, including coastal forest in modeling. Two different source models with volumes of 0.175 km 3 and 0.326 km 3 presented by Heidarzadeh et al, (2020aHeidarzadeh et al, ( , 2020b were also able to explain the observations.…”

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confidence: 99%

Landslide Induced Tsunami Hazard at Volcanoes: the Case of Santorini

Necmioğlu

Heidarzadeh

Vougioukalakis

et al. 2023

Pure Appl. Geophys.

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The destructive tsunami on 22 December 2018 due to the flank collapse of the Anak Krakatau volcano was a bitter reminder of large tsunami risks and of the shortcomings of the existing tsunami warning systems for atypical sources (tsunamis generated by non-seismic and complex sources). In the Mediterranean, several tsunamis were generated by landslides associated with volcanic systems in the past.The volcanic unrest experienced in 2011–2012 on the Santorini volcanic island in the Southern Aegean Sea pointed out the need to identify and quantify tsunami hazard and risk due to possible flank instability which may be triggered as a result of volcanic unrest or nearby seismotectonic activities. Inspired from this need, in this study we examined three possible landslide scenarios in Santorini Island with tsunamigenic potential. The results show that the scenarios considered in our study are able to generate significant local tsunamis impacting Santorini and the nearby islands, as well as producing significant impact along the coasts of the Southern Aegean Sea. While maximum tsunami amplitudes/arrival time ranges are 1.2 m/30-90 min for locations in the Greek-Turkish coasts in the far field, they are in the order of ≈60 m/1-2 min for some locations at the Santorini Island. The extreme tsunami amplitudes and short arrival times for locations inside the Santorini Island is a major challenge in terms of tsunami hazard warning and mitigation. As an effort to address this challenge, a discussion on the requirements for local tsunami warning system addressing atypical sources in the context of multi-hazard disaster risk reduction is also provided.

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Numerical Simulations of December 22, 2018 Anak Krakatau Tsunami and Examination of Possible Submarine Landslide Scenarios

Cited by 21 publications

References 56 publications

Characteristics of building fragility curves for seismic and non-seismic tsunamis: case studies of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean tsunamis

Characteristics of building fragility curves for seismic and non-seismic tsunamis: case studies of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean tsunamis

The Development Study of the Drag Coefficient of Solid Cylinder on Inclined Plane in Water

Landslide Induced Tsunami Hazard at Volcanoes: the Case of Santorini

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