Investigation of the Effect of Debris-Induced Damage for Constructing Tsunami Fragility Curves for Buildings

Abstract

Catastrophe models quantify potential losses from disasters, and are used in the insurance, disaster-risk management, and engineering industries. Tsunami fragility and vulnerability curves are key components of catastrophe models, providing probabilistic links between Tsunami Intensity Measures (TIMs), damage and loss. Building damage due to tsunamis can occur due to fluid forces or debris impact; two effects which have different implications for building damage levels and failure mechanisms. However, existing fragility functions are generally derived using all available damage data for a location, regardless of whether damage was caused by fluid or debris effects. It is therefore not clear whether the inclusion of debris-induced damage introduces bias in existing functions. Furthermore, when modelling areas likely to be affected by debris (e.g., adjacent to ports), it is not possible to account for this increased likelihood of debris-induced damage using existing functions. This paper proposes a methodology to quantify the effect that debris-induced damage has on fragility and vulnerability function derivation, and subsequent loss estimates. A building-by-building damage dataset from the 2011 Great East Japan Earthquake and Tsunami is used, together with several statistical techniques advanced in the field of fragility analysis. First, buildings are identified which are most likely to have been affected by debris from nearby 'washed away' buildings. Fragility functions are then derived incorporating this debris indicator parameter. The debris parameter is shown to be significant for all but the lowest damage state ("minor damage"), and functions which incorporate the debris parameter are shown to have a statistically significant better fit to the observed damage data than models which omit debris information. Finally, for a case study scenario simulated economic loss is compared for estimates from vulnerability functions which do and do not incorporate a debris term. This comparison suggests that biases in loss estimation may be introduced if not explicitly modelling debris. The proposed methodology provides a step towards allowing catastrophe models to more reliably predict the expected damage and losses in areas with increased likelihood of debris, which is of relevance for the engineering, disaster risk-reduction and insurance sectors.

Estimating Tsunami-Induced Building Damage through Fragility Functions: Critical Review and Research Needs

“…MAR refers to the case where the information is not MCAR but can be accounted for by using other attributes. The only study to analyze and treat missing data before conducting fragility function derivation is Macabuag et al (2016a). All other studies that produce fragility functions for various building classifications based on data from existing fragility functions may be susceptible to bias introduced by the removal of incomplete data-entries.…”

“…Studies that have compared TIMs have generally concluded that velocity alone is less effective than depth as an indicator of damage for buildings for the datasets investigated (Koshimura et al, 2009a,b;Macabuag et al, 2016a). However, velocity is often used to calculate the fluid force TIMs shown in Table 7.…”

“…Macabuag et al (2016a) is the only study to consider Froude Number as a TIM and found it to be a poor indicator of building damage when used alone, for the dataset considered. However, Froude Number is used to calculate the quasi-steady force discussed below (Qi et al, 2014;Foster et al, 2017), and recommend using different fragility curves for flow conditions characterized by high and low Froude numbers.…”

“…Momentum flux is proportional to hydrodynamic form-drag (Table 7) and so they can be considered equivalent TIMs [i.e., fragility functions derived from momentum flux and drag force will give identical goodness-of-fit results, Macabuag et al (2016a)]. Park et al (2014) compares damage estimates for a case-study town in the USA using fragility functions for depth, velocity, and momentum flux, concluding that velocity and momentum flux provide the most realistic damage estimates, though this is only based on a qualitative visual assessment of damage locations and the authors acknowledge that this conclusion must be verified with field data.…”

“…are the only empirical study to consider moment of momentum flux in their fragility curves. Note that nearly all current studies that consider force are using the standard drag equation (all except Macabuag et al (2016a), below, and who additionally consider moment of momentum flux), however, this does not account for alternative estimations, such as equivalent hydrostatic methods (MLIT, 2011), bore impact (Robertson and Riggs, 2011), or changes in flow regime (Qi et al, 2014;Foster et al, 2017). Macabuag et al (2016a) derived fragility functions using an equivalent quasi-steady force proposed by Qi et al (2014) and …”