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After more than a decade of recurring tsunamis, identification of tsunami deposits, a part of hazard characterization, still remains a challenging task that is not fully understood. The lack of sufficient monitoring equipment and rare tsunami frequency are among the primary obstacles that limit our fundamental understanding of sediment transport mechanisms during a tsunami. The use of numerical simulations to study tsunami-induced sediment transport was rare in Indonesia until the 2004 Indian Ocean tsunami. This study aims to couple two hydrodynamic numerical models in order to reproduce tsunami-induced sediment deposits, i.e., their locations and thicknesses. Numerical simulations were performed using the Cornell Multi-grid Coupled Tsunami (COMCOT) model and Delft3D. This study reconstructed tsunami wave propagation from its source using COMCOT, which was later combined with Delft3D to map the location of the tsunami deposits and calculate their thicknesses. Two-dimensional horizontal (2-DH) models were used as part of both simulation packages. Four sediment transport formulae were used in the simulations, namely van Rijn 1993, Engelund–Hansen 1967, Meyer-Peter–Mueller (MPM) 1948, and Soulsby 1997. Lhoong, in the Aceh Besar District, located approximately 60 km southwest of Banda Aceh, was selected as the study area. Field data collected in 2015 and 2016 validated the forward modeling techniques adopted in this study. However, agreements between numerical simulations and field observations were more robust using data collected in 2005, i.e., just months after the tsunami (Jaffe et al., 2006). We conducted pit (trench) tests at select locations to obtain tsunami deposit thickness and grain size distributions. The resulting numerical simulations are useful when estimating the locations and the thicknesses of the tsunami deposits. The agreement between the field data and the numerical simulations is reasonable despite a trend that overestimates the field observations. [ABSTRACT FROM AUTHOR]

After more than a decade of recurring tsunamis, identification of tsunami deposits, a part of hazard characterization, still remains a challenging task not fully understood. The lack of sufficient monitoring equipment and rare tsunami frequency are among the primary obstacles that limit our fundamental understanding of sediment transport mechanisms during a tsunami. The use of numerical simulations to study tsunami-induced sediment transport was rare in Indonesia until the 2004 Indian Ocean tsunami. This study aims to couple two hydrodynamic numerical models in order to reproduce tsunami-induced sediment deposits, i.e., their locations and thicknesses. Numerical simulations were performed using the Cornell Multi-Grid Coupled Tsunami Model (COMCOT) and Delft3D. This study reconstructed tsunami wave propagation from its source using COMCOT, which was later combined with Delft3D to map the location of the tsunami deposits and calculate their thicknesses. Two Dimensional-Horizontal (2DH) models were used as part of both simulation packages. Lhoong, in the Aceh Besar District, located approximately 60km southwest of Banda Aceh, was selected as the study area. Field data collected in 2015 and 2016 validated the forward modeling techniques adopted in this study. However, agreements between numerical simulations and field observations were more robust using data collected in 2005, i.e., just months after the tsunami (Jaffe et al., 2006). We conducted pit (trench) tests at select locations to obtain tsunami deposit thickness and grain size distributions. The resulting numerical simulations are useful when estimating the locations and the thicknesses of the tsunami deposits. The agreement between the field data and the numerical simulations is reasonable despite a trend that overestimates the field observations. [ABSTRACT FROM AUTHOR]

Tsunamis are normally associated with submarine earthquakes along subduction zones, such as the 2011 Japan tsunami. However, there are significant tsunami sources related to submarine volcanic eruptions. Volcanic tsunamis, like tectonic tsunamis, typically occur with little warning and can devastate populated coastal areas at considerable distances from the volcano. There have been more than 90 volcanic tsunamis accounting for about 25% of all fatalities directly attributable to volcanic eruptions during the last 250 years. The two deadliest non-tectonic tsunamis in the past 300 years are due to the 1883 Krakatoa eruption in Indonesia with associated pyroclastic flows and Japan's Mount Unzen lava dome collapse in 1792. At the source, volcanic tsunamis can exceed tectonic tsunamis in wave height. There are at least nine different mechanisms by which volcanoes produce tsunamis. Most volcanic tsunami waves have been produced by extremely energetic explosive volcanic eruptions in submarine or near water surface settings, or by flow of voluminous pyroclastic flows or debris avalanches into the sea. The "orange" alert in July 2015 at the Kick 'em Jenny submarine volcano off Granada in the Caribbean Sea highlighted the challenges in characterizing the tsunami waves for a potential submarine volcanic eruption. The recent activity and collapse of the volcanic cone at Anak Krakatau generated tsunami waves that impacted coasts along the Sunda Strait without any prior warnings and caused more than 400 fatalities on December 22, 2018.Source and runup scenarios are physically modeled using generalized Froude similarity in the three dimensional NHERI tsunami wave basin at Oregon State University. A novel volcanic tsunami generator (VTG) was deployed to simulate submarine volcanic eruptions with varying initial submergence and kinematics. The VTG consists of a telescopic eruptive column with an approximate outer diameter of 1.2 m. The top cap of the pressurized eruptive column is accelerated vertically by eight synchronized 80 mm diameter pneumatic pistons with a stroke of approximately 0.3 m. More than 300 experimental runs have been performed in summer 2018, which include around 120 combinations of velocities and water depths. The variable eruption velocities of the VTG mimic relatively slow mud volcanoes and rapid explosive eruptions. The gravitational collapse of the eruptive column represents the potential engulfment and caldera formation. Water surface elevations are recorded by an array of resistance wave gauges. The VTG displacement is measured with an internal linear potentiometer and from above and underwater camera recordings. Water surface reconstruction and kinematics are determined with a stereo particle image velocimetry (PIV) system. Wave runup is recorded with resistance wave gauges along the slope and verified with video image processing. The water surface spike from the concentric collision of wave crest is observed under a limited range of water depths and Froude numbers. The energy conversion rates from the volcanic eruption to the wave train are quantified for various scenarios. The measured volcanic eruption and tsunami data serve to validate and advance three-dimensional numerical volcanic tsunami prediction models. [ABSTRACT FROM AUTHOR]

On September 28, 2018, a magnitude Mw 7.5 earthquake occurred in the neck of Sulawesi's Minahasa peninsula. The combined effects of the earthquake and tsunami caused catastrophic damage and more than 2000 deaths. An international tsunami survey team (ITST) was deployed 3 weeks after the event to document flow depths, runup heights, inundation distances, sediment deposition, damage patterns at various scales, performance of the man-made infrastructure and impact on the natural environment. The 23 to 29 October ITST covered a 100 km stretch of coastline circling the entire Palu Bay and adjacent coastlines along the Makassar Strait. A 200 km long reconnaissance flight with an Indonesian Army Mil Mi-17 helicopter provided oblique aerial photography of impacted sites. The collected field survey data includes 130 tsunami runup and flow depth measurements. The tsunami impact peaked inside Palu Bay with flow depths above ground reaching 6 m and maximum runup heights exceeding 10 m. Inundation and tsunami damage was mostly limited to within 0.5 km of the shoreline except along rivers. A rapid decrease of tsunami heights was observed towards the bay entrance and outside of the Palu Bay along the Makassar Strait coastlines. Two tsunami eyewitness video recording locations inside Palu Bay were surveyed for subsequent video image calibration, tsunami hydrograph and flow velocity analysis. We deployed a Leica BLK360 scanner from the NHERI RAPID facility. We acquired precise topographic data using terrestrial laser scanning (TLS) at selected video sites with multiple scans acquired from different instrument positions. These ground-based LiDAR measurements produce 3-dimensional "point cloud" datasets. Digital photography from 3 scanner-mounted cameras yields full dome panoramic images overlaid on highly accurate point clouds. The main coastal road in Palu was overwashed with flow velocities of more than 7 m/s. Field observations, drone videos, helicopter and satellite imagery are presented. Eyewitnesses interviewed based on established protocols indicate rapid tsunami arrivals within a few minutes of the earthquake. We educated residents about tsunami hazards as community-based education and awareness programs are essential to save lives in locales at risk from locally generated tsunamis. [ABSTRACT FROM AUTHOR]