Tsunami damage to ports: Cataloguing damage to create fragility functions from the 2011 Tohoku event

Abstract

Abstract. Modern tsunami events have highlighted the vulnerability of port structures to these high-impact but infrequent occurrences. However, port planning rarely includes adaptation measures to address tsunami hazards. The 2011 Tohoku tsunami presented us with an opportunity to characterise the vulnerability of port industries to tsunami impacts. Here, we provide a spatial assessment and photographic interpretation of freely available data sources. Approximately 5,000 port structures were assessed for damage and stored in a database. Using the newly developed damage database, tsunami damage is quantified statistically for the first time, through the development of damage fragility functions for eight common port industries. In contrast to tsunami damage fragility functions produced for buildings from existing damage database, our fragility functions showed higher prediction accuracies (up to 75 % accuracy). Pre-tsunami earthquake damage was also assessed in this study, and was found to influence overall damage assessment. The damage database and fragility functions for port industries can inform structural improvements and mitigation plans for ports against future events.

Seismic damage and comparison of fragility functions of public and residential buildings damaged by the 2014 Mae Lao (Northern Thailand) earthquake

“…DS 2 . DS 3, which prevents overlaps in the pathways of the fragility functions (Chua et al, 2021). The probability of damage exceedance in an ordinal logistic regression model can be expressed as follows:…”

“…Confidence intervals reflect the epistemic uncertainty (known uncertainty in the estimate or prediction) in the fragility functions. Following the approach adopted in Chua et al (2021), 95% confidence intervals were constructed around the expected mean of the response variable using bootstrap methods. The bootstrap method treats values from the original dataset as a substitute of the true population.…”

“…Therefore, the ordinal model provides the advantage of utilizing all available data points within the dataset. In addition, an ordinal model considers the ordered nature of the response variable, that is, DS 1 > DS 2 > DS 3, which prevents overlaps in the pathways of the fragility functions (Chua et al, 2021).…”

Lava flow impacts on the built environment: Insights from a new global dataset

“…For example, where structurelevel empirical damage data are available they can be used to provide insights into the vulnerability of similar buildings in future events in the same region or another region with similar building types (Wilson et al, 2014). With enough data, the relationships between damage and hazard intensity can be used to build robust impact forecasting models (e.g., Chua et al, 2021;Lallemant et al, 2015;Suppasri et al, 2011;Tomiczek et al, 2017). This analysis can be used to evaluate building vulnerability, improve building design, and give guidance for mitigation measures.…”

Infrastructure network component vulnerability to damage from the 2015 Illapel tsunami, Coquimbo, Chile

“…Tsunami fragility curves commonly rely on relatively large samples of empirical or modelled impact damage data, yet such quantitative empirical data for infrastructure vulnerability are rare and have only recently been a focus of post-event impact assessment (MLIT, 2012; Paulik et al, 2019Paulik et al, , 2021 and physical modelling studies (C Chen and Melville, 2015; Cheng Chen et al, 2017Chen et al, , 2018Rossetto et al, 2014). For infrastructure networks, transportation components, namely roads, bridges, utility poles and port structures, have been previously analysed for fragility function development from empirical eld surveys and physical modelling (Chua et al, 2020;Eguchi et al, 2013; Kawashima and Buckle, 2013; Koks et al, 2019;Maruyama and Itagaki, 2017;Shoji and Moriyama, 2007;Williams, et al, 2020b;Williams, et al, 2020a). However, the relative importance of network component attribute characteristics in uencing tsunami damage is understudied.…”