Estimating the Topography Before Volcanic Sector Collapses Using Tsunami Survey Data and Numerical Simulations

Yamanaka, Yusuke; Tanioka, Yuichiro

doi:10.1007/s00024-017-1589-8

Cited by 10 publications

(5 citation statements)

References 36 publications

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“…In previous studies, K = 0.99 and κ = 1.76 was estimated for near‐source region in the case of the two‐layer slide model (Kawamata et al, ). Yamanaka and Tanioka () also estimated K = 1.23 and κ = 1.91 for the two‐layer model when the volume is 100%. Smaller κ of our estimation indicate that this studies model is better fit with comparison of tsunami heights.…”

Section: Resultsmentioning

confidence: 97%

“…A detailed bathymetric survey around Oshima-Oshima volcano revealed the extent of the 1741 landslide deposits on the seafloor (Satake & Kato, 2001). Using that landslide extent, tsunami generation was simulated using a kinematic landslide model (Satake, 2007) and a two-layer model (Imamura, Hashi, & Imteaz, 2001;Imamura, Goto, Shigihara, Kitamura, Matsubara, Takaoka & Ban, 2001;Kawamata et al, 2005;Yamanaka & Tanioka, 2017). However, these models cannot explain both the distribution of the landslide deposit and tsunami heights.…”

Section: Introductionmentioning

confidence: 99%

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Numerical Simulation of the Landslide and Tsunami Due to the 1741 Oshima‐Oshima Eruption in Hokkaido, Japan

et al. 2019

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Sector collapse during the 1741 eruption of Oshima‐Oshima volcano (southwestern Hokkaido, Japan) generated a large tsunami in the Japan Sea. The tsunami caused severe damage along the Oshima (Hokkaido) and Tsugaru (Honshu) peninsulas. Tsunami deposits due to the 1741 event were identified along the Okushiri and Hiyama coast in Hokkaido. In this study, we numerically simulated the landslide and tsunami generated by the 1741 Oshima‐Oshima eruption using an improved two‐layer model to explain the depositional area of the landslide, the tsunami heights written in historical records, and the distributions of tsunami deposits. Areas of erosion and deposition by the 1741 landslide were estimated from the bathymetric data on the northern slope of Oshima‐Oshima volcano. In addition, previous topography before the sector collapse was restored. From the bathymetry difference before and after the landslide, the volume of collapsed material was estimated at 2.2 km3. Based on those data, the landslide and tsunami were numerically simulated by solving equations of an improved two‐layer model that incorporates Manning's formula in the bottom friction terms of the lower layer. An apparent friction angle of 2.5 and a Manning's roughness coefficient of 0.15 were selected to explain the area of deposition estimated from the bathymetry analysis and distributions of tsunami deposits. The thickness distribution of the computed landslide mass fits relatively well with the depositional area. Computed tsunami heights match those from historical records along the Hiyama coast. Computed tsunami inundation areas cover most of the distributions of tsunami deposits identified along the coasts.

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Section: Resultsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of the Landslide and Tsunami Due to the 1741 Oshima‐Oshima Eruption in Hokkaido, Japan

et al. 2019

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“…The VolcFlow model is capable of simulating both the behavior of collapsed materials and the propagation of tsunamis, but the speed of tsunami propagation is limited to that of the long waves. To account for dispersive characteristics of tsunami, we employ a non-linear dispersive theory (Boussinesq model) (Yamanaka and Tanioka, 2017) to simulate the tsunami propagation from the tsunami wave field first estimated by VolcFlow model. Manning roughness coefficient of 0.025 m −1/3 was assumed for the bottom friction terms in the Boussinesq model.…”

Section: Methodsmentioning

confidence: 99%

“…Tsunamis associated with volcanic sector collapse are widely recognized worldwide. Although their occurrence is less-frequent than that of earthquake-generated tsunamis, the potential catastrophe from volcanic tsunamis cannot be underestimated and should be considered an important tsunami source in terms of hazards and disaster strategies (Yamanaka and Tanioka, 2017;Williams et al, 2019). The underlying processes of a tsunami associated with mass failure can be investigated through physical experiments and/or numerical simulations of tsunami generation and propagation.…”

Section: Introductionmentioning

confidence: 99%

Development of early warning system for tsunamis accompanied by collapse of Anak Krakatau volcano, Indonesia

Ratnasari,

Tanioka,

Yamanaka

et al. 2023

Front. Earth Sci.

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Present tsunami warning systems have been specialized for earthquake-generated tsunamis, but rapidly evaluating the tsunamis caused by volcanic eruptions and/or volcanic sector collapses remains a challenge. In this study, we applied a numerical model to the 2018 Anak Krakatau tsunami event, which was generated by the sector collapse, investigated a tsunami prediction skill by the model, and developed a real-time forecasting method based on a pre-computed database for future tsunamis accompanied by such eruption of Anak Krakatau. The database stores spatiotemporal changes in water surface level and flux, which are simulated under various collapse scenarios, for confined areas in the vicinity of potential source. The areas also cover the locations of observation stations that are virtually placed on uninhabited island surrounding the source area. During an actual volcanic tsunami event, a tsunami is expected to be observed at the observation stations. For real-time tsunami forecasting, the most suitable scenarios to reproduce the observed waveforms are searched quickly in the database. The precomputed results under the identified scenarios are further provided as input for rapid tsunami propagation simulation. Therefore, an effective real-time forecasting can be conducted to densely populated coastal areas located at a considerable distance from the source, such as the coasts of Java and Sumatra. The forecasting performance was examined by applying the method for three hypothetical collapse scenarios assuming different sliding directions. We demonstrated that the tsunamis along the coasts were successfully forecasted. Moreover, we showed that the combination of a pre-computed database and the existence of observation stations near the source area was able to produce appropriate tsunami forecasting for the coastal area even in a volcanic event.

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“… 25 – 28 ), at Stromboli (e.g. 29 , 30 ), or in Japan 31 . However, LSMW in those cases seems closely linked to active tectonics (e.g.…”

Section: Introductionmentioning

confidence: 99%

Large-scale mass wasting on small volcanic islands revealed by the study of Flores Island (Azores)

Hildenbrand

Marques

Catalão

2018

Sci Rep

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Small intra-plate volcanic islands (total height above seafloor <2500 m) have been considered gravitationally stable. Topographic, stratigraphic, structural and new K/Ar data show that the small island of Flores (Azores) is strongly asymmetric and made up of nested volcanic successions. Along the northwestern coastline, ca. 1.2 Ma lava flows are in lateral contact with a younger volcanic unit (ca. 0.7 Ma), reflecting the existence of a steep lateral discontinuity. From the general dip of the lava flows, their age and the arcuate geometry of the contact, we infer a major landslide that removed the western flank of the older volcano. Further inland, E-dipping lava flows at the summit of the island are ca. 1.3 Ma, suggesting another landslide structure that displaced the whole western half of the former volcanic edifice. Available offshore data show a large hummocky field west of Flores, here interpreted as voluminous debris-avalanche deposits. Unlike the eastern and central Azores islands, Flores sits on a relatively stable tectonic setting. Therefore, we propose that small-size volcanic islands can be sufficiently gravitationally unstable to experience recurrent episodes of large-scale mass wasting triggered by mechanisms other than tectonic earthquakes and thus represent an under-evaluated potential source of hazard and, therefore, risk.

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Estimating the Topography Before Volcanic Sector Collapses Using Tsunami Survey Data and Numerical Simulations

Cited by 10 publications

References 36 publications

Numerical Simulation of the Landslide and Tsunami Due to the 1741 Oshima‐Oshima Eruption in Hokkaido, Japan

Numerical Simulation of the Landslide and Tsunami Due to the 1741 Oshima‐Oshima Eruption in Hokkaido, Japan

Development of early warning system for tsunamis accompanied by collapse of Anak Krakatau volcano, Indonesia

Large-scale mass wasting on small volcanic islands revealed by the study of Flores Island (Azores)

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