Developing probabilistic models for predicting tsunami-induced building damage

The increased availability of post-tsunami damage data over the past decade has led to a growing inventory of empirical fragility curves that probabilistically model the damage response of buildings to tsunamis. However, these curves are not currently accurate enough to be applied effectively in tsunami damage assessments. This thesis addresses this problem by developing new techniques for deriving fragility curves remotely using a novel web-based building survey tool and "building aware" hydrodynamic inundation models. These techniques were implemented as part of the Tsunami-Impacted Building Collection and Analysis (TIBCA) framework, which was developed to survey, manage and analyse the data necessary to generate fragility curves remotely.TIBCA was applied to a case study of the 2011 Tohoku-oki tsunami. Here, it was used to first, conduct a building survey to classify the type and damage level of buildings in Yuriage, Japan, using pre- and post-event Google StreetView imagery and second, to conduct a hazard modelling study to estimate their flood depth exposure. The modelling study investigated three high-resolution methods of representing buildings, two considering them as static features and one considering them dynamically to simulate collapse. These "building aware" models matched well with the field data in Yuriage, with those considering building collapse, in particular, providing the best estimates. Conversely, the building-exclusive models that were tested were unable to reproduce the flow conditions accurately.In total, 721 buildings were examined and characterised with respect to their type, damage level and hazard exposure. These were used to develop fragility curves for a range of building types, damage states and hazard scenarios. Comparison of these curves to existing field-based work confirmed their accuracy and demonstrated that: (1) the web-based building survey tool was effective at classifying buildings remotely, (2) the "building aware" models predicted flood depths that correlated with the damage sustained by buildings and (3) the type/damage classification systems that were used were effective at precisely describing building characteristics. As such, TIBCA represents significant advances in terms of increasing the capabilities of remote survey techniques, modelling tsunami inundation in the built environment and developing more accurate and precisely defined fragility curves