2:45 PM - 3:15 PM
[MIS15-03] Advances in tsunami numerical modeling after the 2011 Tohoku earthquake and future challenges related to tsunami deposit research
★Invited Papers
Keywords:source modeling, sediment transport modeling, uncertainty
Tsunami numerical modeling, such as source modeling and hazard assessment, has been playing a crucial role in policy making and consensus building for disaster mitigation actions. While the 2011 Tohoku-oki earthquake tsunami brought unexpected disasters, it also left valuable lessons for improving tsunami numerical modeling. Since tsunamis cause not only surges and inundations of the seawater, but also induced phenomena such as sediment erosion and deposition, debris drift and structural damage, development of multi-physics model is a key challenge, in terms of improved hazard assessment. Verification and validation of such multi-physics models have been promoted with aids from the groundbreaking data of the Tohoku-oki earthquake and tsunami.
Tsunami numerical modeling has been used to estimate the source of past disastrous tsunamis by bridging the findings from different disciplines, such as seismology, geodesy, geology, geomorphology, ecology, coastal engineering, archaeology and history. An established approach is comparison of the spatial distribution of tsunami deposits, such as sand layers and boulders, and simulated tsunami inundation area. Although gaps between sediment distribution and inundation limit are a well-known concern, source models of paleotsunami events, such as the 869 Jogan earthquake tsunami in the Tohoku region, have been deduced based on such comparisons. Upgrading the ability of the source modeling is expected with aids from the sediment transport simulations. Numerical modeling of tsunami-induced sediment transport and morphological change due to the Tohoku-oki tsunami have been providing physical explanations for geological and geomorphological features of sandy tsunami deposits in Sendai Bay and Sanriku Coast. It encourages application of the tsunami sediment transport modeling to paleotsunami researches. A recent case study of the 1867 Keelung tsunami in the northern Taiwan demonstrated that the tsunami sediment transport modeling benefit interpreting sparse historical and geological records of the tsunami and estimating the mechanism and size of the tsunamigenic earthquake.
A key challenge of tsunami numerical modeling is quantification and reduction of uncertainty. Various factors are involving in the uncertainty in tsunami numerical modeling, such as inputs, formulations and model parameters. With regard to the modeling of paleotsunami deposits, the uncertainty due to inputs include the vegetation, sediment source and grain-size composition and sea level, in addition to the bathymetry and topography at that time. A numerical experiment showed that simulated thickness and inland extent of onshore sandy tsunami deposits may be several times larger or smaller, depending on the assumptions of the height of coastal sand dunes. A systematic framework to quantify the uncertainty is needed for further utilization of tsunami numerical modeling. The quantification of uncertainty provides the range of variability of the outputs, which is beneficial when comparing the simulations with sedimentary data. Efforts to collect contextual data, such as long-term change in coastal environment, annual and seasonal variation of beach topography and anthropogenic land modification, in addition to reconstructed paleo-topographic and bathymetric data, will be needed to reduce the uncertainty in numerical modeling of paleotsunamis.
Tsunami numerical modeling has been used to estimate the source of past disastrous tsunamis by bridging the findings from different disciplines, such as seismology, geodesy, geology, geomorphology, ecology, coastal engineering, archaeology and history. An established approach is comparison of the spatial distribution of tsunami deposits, such as sand layers and boulders, and simulated tsunami inundation area. Although gaps between sediment distribution and inundation limit are a well-known concern, source models of paleotsunami events, such as the 869 Jogan earthquake tsunami in the Tohoku region, have been deduced based on such comparisons. Upgrading the ability of the source modeling is expected with aids from the sediment transport simulations. Numerical modeling of tsunami-induced sediment transport and morphological change due to the Tohoku-oki tsunami have been providing physical explanations for geological and geomorphological features of sandy tsunami deposits in Sendai Bay and Sanriku Coast. It encourages application of the tsunami sediment transport modeling to paleotsunami researches. A recent case study of the 1867 Keelung tsunami in the northern Taiwan demonstrated that the tsunami sediment transport modeling benefit interpreting sparse historical and geological records of the tsunami and estimating the mechanism and size of the tsunamigenic earthquake.
A key challenge of tsunami numerical modeling is quantification and reduction of uncertainty. Various factors are involving in the uncertainty in tsunami numerical modeling, such as inputs, formulations and model parameters. With regard to the modeling of paleotsunami deposits, the uncertainty due to inputs include the vegetation, sediment source and grain-size composition and sea level, in addition to the bathymetry and topography at that time. A numerical experiment showed that simulated thickness and inland extent of onshore sandy tsunami deposits may be several times larger or smaller, depending on the assumptions of the height of coastal sand dunes. A systematic framework to quantify the uncertainty is needed for further utilization of tsunami numerical modeling. The quantification of uncertainty provides the range of variability of the outputs, which is beneficial when comparing the simulations with sedimentary data. Efforts to collect contextual data, such as long-term change in coastal environment, annual and seasonal variation of beach topography and anthropogenic land modification, in addition to reconstructed paleo-topographic and bathymetric data, will be needed to reduce the uncertainty in numerical modeling of paleotsunamis.