This study presents a rigorous computational framework for visualizing uncertainty of tsunami hazard and risk assessment. The methodology consists of three modules: (i) earthquake source characterization and stochastic simulation of slip distribution, (ii) tsunami propagation and inundation, and (iii) tsunami damage assessment and loss estimation. It takes into account numerous stochastic tsunami scenarios to evaluate the uncertainty propagation of earthquake source characteristics in probabilistic tsunami risk analysis. An extensive Monte Carlo tsunami inundation simulation is implemented for the 2011 Tohoku tsunami (focusing upon on Rikuzentakata along the Tohoku coast of Japan) using 726 stochastic slip models derived from eleven inverted source models. By integrating the tsunami hazard results with empirical tsunami fragility functions, probabilistic tsunami risk analysis and loss estimation are carried out; outputs from the analyses are displayed using various visualization methods. The developed framework is comprehensive, and can provide valuable insights in promoting proactive tsunami risk management and in improving emergency response capability.

This study presents a calibration of CAT-in-a-Box and intensity-based index trigger mechanisms for parametric tsunami catastrophe bonds. Trigger conditions for the former are based on fundamental event characteristics, such as earthquake location and magnitude, whereas those for the latter utilize tsunami wave height measurements at a series of observation stations. These solutions are illustrated for a building portfolio in Iwanuma City in Miyagi Prefecture, Japan, by considering a new seafloor observation network S-net off the Tohoku-Hokkaido coast of Japan. Performances of the two types of parametric solutions are quantitatively evaluated and compared with each other to discuss their advantages and disadvantages.

Inundation depth is commonly used as an intensity measure in tsunami fragility analysis. However, inundation depth cannot be taken as the sole representation of tsunami impact on structures, especially when structural damage is caused by hydrodynamic and debris impact forces that are mainly determined by flow velocity. To reflect the influence of flow velocity in addition to inundation depth in tsunami risk assessment, a tsunami loss estimation method that adopts both inundation depth and flow velocity (i.e., bivariate intensity measures) in evaluating tsunami damage is developed. To consider a wide range of possible tsunami inundation scenarios, Monte Carlo-based tsunami simulations are performed using stochastic earthquake slip distributions derived from a spectral synthesis method and probabilistic scaling relationships of earthquake source parameters. By focusing on Sendai (plain coast) and Onagawa (ria coast) in the Miyagi Prefecture of Japan in a case study, the stochastic tsunami loss is evaluated by total economic loss and its spatial distribution at different scales. The results indicate that tsunami loss prediction is highly sensitive to modelling resolution and inclusion of flow velocity for buildings located less than 1 km from the sea for Sendai and Onagawa of Miyagi Prefecture.

Tsunamis triggered by large offshore earthquakes are devastating, and buildings located near the coast experience damage and loss due to such extreme events. In evaluating regional tsunami impact via numerical tsunami simulations, it is important to pay close attention to local geographical features represented by a digital elevation model (DEM), because tsunami loss estimation is sensitive to its quality and resolution. This study investigates the influence of elevation data resolution on tsunami loss estimation at different scales by comparing tsunami risk results using DEMs of four resolutions (i.e., 10-m, 50-m, 150-m, and 450-m). Using stochastic tsunami modeling, a case study is carried out by focusing on the Tohoku region in Japan to investigate the influence of DEM resolution on tsunami loss estimation considering the effect of location attributes (i.e., coastal topography, distance from the coast, and land elevation) for two building portfolios on plain coast and ria coast. The results indicate the significance of DEM resolution for local tsunami loss estimations at different locations. The local tsunami risk is closely related to the building location, and the increase of distance from the coast and/or land elevation dramatically reduces the local tsunami risk. The investigations extend discussions regarding the calculations of pure insurance premium rate for tsunami loss coverage depending upon structural attributes and location attributes.

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