From offshore to onshore probabilistic tsunami hazard assessment via efficient Monte-Carlo sampling

Offshore Probabilistic Tsunami Hazard Assessments (offshore PTHAs) provide large-scale analyses of earthquake-tsunami frequencies and uncertainties in the deep ocean, but do not provide high-resolution onshore tsunami hazard information as required for many risk-management applications. To understand the implications of an offshore PTHA for the onshore hazard at any site, in principle the tsunami inundation should be simulated locally for every scenario in the offshore PTHA. In practice this is rarely feasible due to the computational expense of inundation models, and the large number of scenarios in offshore PTHAs. Monte-Carlo methods offer a practical and rigorous alternative for approximating the onshore hazard, using a random subset of scenarios. The resulting Monte-Carlo errors can be quantified and controlled, enabling high-resolution onshore PTHAs to be implemented at a fraction of the computational cost. This study develops novel Monte-Carlo sampling approaches for offshore-to-onshore PTHA. Modelled offshore PTHA wave heights are used to preferentially sample scenarios that have large offshore waves near an onshore site of interest. By appropriately weighting the scenarios, the Monte-Carlo errors are reduced without introducing any bias. The techniques are applied to a high-resolution onshore PTHA for the island of Tongatapu in Tonga. In this region, the new approaches lead to efficiency improvements equivalent to using 4-18 times more random scenarios, as compared with stratified-sampling by magnitude, which is commonly used for onshore PTHA. The greatest efficiency improvements are for rare, large tsunamis, and for calculations that represent epistemic uncertainties in the tsunami hazard. To facilitate the control of Monte-Carlo errors in practical applications, this study also provides analytical techniques for estimating the errors both before and after inundation simulations are conducted. Before inundation simulation, this enables a proposed Monte-Carlo sampling scheme to be checked, and potentially improved, at minimal computational cost. After inundation simulation, it enables the remaining Monte-Carlo errors to be quantified at onshore sites, without additional inundation simulations. In combination these techniques enable offshore PTHAs to be rigorously transformed into onshore PTHAs, with full characterisation of epistemic uncertainties, while controlling Monte-Carlo errors.

Numerical Assessment of Coastal Multi-hazard Vulnerability in Tokyo Bay

Many bays in the world are threatened by coastal hazards such as storm surge, river flood and tsunami. Since most of the existing studies have been focused on one or two of them, in this study, the assessment of coastal vulnerability caused by the three hazards was the research target. Inundation simulation is a widely used and straightforward way in coastal vulnerability assessments; however, it is computationally expensive, and considering an increase in the number of cases in multi-hazard analysis, an efficient method was proposed using an estimated overflow volume without computing inundation, which was validated by comparing with inundation simulation. It shows that when free overflow is dominant, this method is consistent with inundation simulation approach. Using Tokyo Bay as a study area, the efficient method was then applied to multi-hazard vulnerability assessment. By comparing the overflow volume maps and maximum anomaly distribution along the coasts for four types of hazards (worst storm surge; worst concurrent storm surge and river flood; worst concurrent storm surge, river flood and Tokai-Tonankai earthquake tsunami; worst concurrent storm surge, river flood and Tokyo inland earthquake tsunami), we investigated the characteristics of different types of hazards and identified the difference between single hazard and multi-hazards. The characteristic of overflow volume along the coasts is similar to that of maximum anomaly distribution, especially for only storm surge case, the multi-hazard case combining storm surge and river flood, and the multi-hazard case combining storm surge, Tokyo inland earthquake tsunami and river flood. However, for multi-hazard case combining storm surge, Tokai-Tonankai earthquake tsunami and river flood, only by the maximum anomaly distribution, it cannot reflect the real overflow volume condition. For only storm surge case and multi-hazard case combining storm surge and river flood, the head of the bay suffers the highest vulnerability while for multi-hazard cases combining storms surge, tsunami and river flood, the difference of vulnerability in the north and south of the bay is not significant. The difference of superposing method and concurrent method for computing multi-hazards was also compared. It was found that the linear superposing method tends to overestimate the total water elevation in coastal region; however, in the coasts where superposing method underestimates the multi-hazard anomalies, upgrading dikes needs to be considered by policymakers.