Ingrid Charvet

Building damage characteristics based on surveyed data and fragility curves of the 2011 Great East Japan tsunami

A large amount of buildings was damaged or destroyed by the 2011 Great East Japan tsunami. Numerous field surveys were conducted in order to collect the tsunami inundation extents and building damage data in the affected areas. Therefore, this event provides us with one of the most complete data set among tsunami events in history. In this study, fragility functions are derived using data provided by the Ministry of Land, Infrastructure and Transportation of Japan, with more than 250,000 structures surveyed. The set of data has details on damage level, structural material, number of stories per building and location (town). This information is crucial to the understanding of the causes of building damage, as differences in structural characteristics and building location can be taken into account in the damage probability analysis. Using least squares regression, different sets of fragility curves are derived to demonstrate the influence of structural material, number of stories and coastal topography on building damage levels. The results show a better resistant performance of reinforced concrete and steel buildings over wood or masonry buildings. Also, buildings taller than two stories were confirmed to be much stronger than the buildings of one or two stories. The damage characteristic due to the coastal topography based on limited number of data in town locations is also shortly discussed here. At the same tsunami inundation depth, buildings along the Sanriku ria coast were much greater damaged than buildings from the plain coast in Sendai. The difference in damage states can be explained by the faster flow velocities in the ria coast at the same inundation depth. These findings are key to support better future building damage assessments, land use management and disaster planning.

Empirical fragility analysis of building damage caused by the 2011 Great East Japan tsunami in Ishinomaki city using ordinal regression, and influence of key geographical features

Tsunamis are disastrous events typically causing loss of life, and extreme damage to the built environment, as shown by the recent disaster that struck the East coast of Japan in 2011. In order to quantitatively estimate damage in tsunami prone areas, some studies used a probabilistic approach and derived fragility functions. However, the models chosen do not provide a statistically sound representation of the data. This study applies advanced statistical methods in order to address these limitations. The area of study is the city of Ishinomaki in Japan, the worst affected area during the 2011 event and for which an extensive amount of detailed building damage data has been collected. Ishinomaki city displays a variety of geographical environments that would have significantly affected tsunami flow characteristics, namely a plain, a narrow coast backed up by high topography (terrain), and a river. The fragility analysis assesses the relative structural vulnerability between these areas, and reveals that the buildings surrounding the river were less likely to be damaged. The damage probabilities for the terrain area (with relatively higher flow depths and velocities) were lower or similar to the plain, which confirms the beneficial role of coastal protection. The model diagnostics show tsunami flow depth alone is a poor predictor of tsunami damage for reinforced concrete and steel structures, and for all structures other variables are influential and need to be taken into account in order to improve fragility estimations. In particular, evidence shows debris impact contributed to at least a significant amount of non-structural damage.

Empirical fragility assessment of buildings affected by the 2011 Great East Japan tsunami using improved statistical models

Tsunamis are destructive natural phenomena which cause extensive damage to the built environment, affecting the livelihoods and economy of the impacted nations. This has been demonstrated by the tragic events of the Indian Ocean tsunami in 2004, or the Great East Japan tsunami in 2011. Following such events, a few studies have attempted to assess the fragility of the existing building inventory by constructing empirical stochastic functions, which relate the damage to a measure of tsunami intensity. However, these studies typically fit a linear statistical model to the available damage data, which are aggregated in bins of similar levels of tsunami intensity. This procedure, however, cannot deal well with aggregated data, low and high damage probabilities, nor does it result in the most realistic representation of the tsunami-induced damage. Deviating from this trend, the present study adopts the more realistic generalised linear models which address the aforementioned disadvantages. The proposed models are fitted to the damage database, containing 178,448 buildings surveyed in the aftermath of the 2011 Japanese tsunami, provided by the Ministry of Land, Infrastructure Transport and Tourism in Japan. In line with the results obtained in previous studies, the fragility curves show that wooden buildings (the dominant construction type in Japan) are the least resistant against tsunami loading. The diagnostics show that taking into account both the building’s construction type and the tsunami flow depth is crucial to the quality of the damage estimation and that these two variables do not act independently. In addition, the diagnostics reveal that tsunami flow depth estimates low levels of damage reasonably well; however, it is not the most representative measure of intensity of the tsunami for high damage states (especially structural damage). Further research using disaggregated damage data and additional explanatory variables is required in order to obtain reliable model estimations of building damage probability.

A multivariate generalized linear tsunami fragility model for Kesennuma City based on maximum flow depths, velocities and debris impact, with evaluation of predictive accuracy

The recent losses caused by the unprecedented 2011 Great East Japan Tsunami disaster have stimulated further research efforts, notably in the mechanisms and probabilistic determination of tsunami-induced damage, in order to provide the necessary information for future risk assessment and mitigation. The stochastic approach typically adopts fragility functions, which express the probability that a building will reach or exceed a predefined damage level usually for one, sometimes several measures of tsunami intensity. However, improvements in the derivation of fragility functions are still needed in order to yield reliable predictions of tsunami damage to buildings. In particular, extensive disaggregated databases, as well as measures of tsunami intensity beyond the commonly used tsunami flow depth should be used to potentially capture variations in the data which have not been explained by previous models. This study proposes to derive fragility functions with additional intensity measures for the city of Kesennuma, which was extensively damaged during the 2011 tsunami and for which a large and disaggregated dataset of building damage is available. In addition to the surveyed tsunami flow depth, the numerically estimated flow velocities as well as a binary indicator of debris impact are included in the model and used simultaneously to estimate building damage probabilities. Following the recently proposed methodology for fragility estimation based on generalized linear models, which overcomes the shortcomings of classic linear regression in fragility analyses, ordinal regression is applied and the reliability of the model estimates is assessed using a proposed penalized accuracy measure, more suitable than the traditional classification error rate for ordinal models. In order to assess the predictive power of the model, penalized accuracy is estimated through a repeated tenfold cross-validation scheme. For the first time, multivariate tsunami fragility functions are derived and represented in the form of fragility surfaces. The results show that the model is able to predict tsunami damage with satisfactory predictive accuracy and that debris impact is a crucial factor in the determination of building collapse probabilities.

Building damage from the 2011 Great East Japan tsunami: quantitative assessment of influential factors

Abstract Based on the classification provided by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT), the damage level of buildings impacted by the 2011 Great East Japan tsunami can be separated into six levels (from minor damage to washed away). The objective of this paper is to identify the significant predictor variables and the direction of their potential relationship to the damage level in order to create a predicting formula for damage level. This study used the detailed data of damaged buildings in Ishinomaki city, Miyagi prefecture, Japan, collected by MLIT. The explanatory variables tested included the inundation depth, number of floors, structural material, and function of the building. Ordinal regression was applied to model the relationship between the ordinal outcome variable (damage level) and the predictors. The findings indicated that inundation depth, structural material, and function of building were significantly associated with the damage level. In addition to this new type of model, this research provides a valuable insight into the relative influence of different factors on building damage and suggestions that may help to revise the classification of current standards. This study can contribute to academic tsunami research by assessing the contribution of different variables to the observed damage using new approaches based on statistical analysis and regression. Moreover, practical applications of these results include understanding of the predominant factors driving tsunami damage to structures, implementation of the relevant variables into the proposed, or alternative model in order to improve current damage predictions by taking into account not only inundation depth, but also variables such as structural material and function of building.

Fragility Curves Based on Data from the 2011 Tohoku-Oki Tsunami in Ishinomaki City, with Discussion of Parameters Influencing Building Damage

The 63,605 damaged buildings from the 2011 Tohoku-oki tsunami in Ishinomaki were used to develop 52 fragility curves using linear regression. The data comprise the damage level and the measured inundation depth for each building. In agreement with previous studies, the present results indicate that reinforced concrete and steel buildings with three stories or more perform better under tsunami loading. Performance with respect to their intended function was found to depend mainly on structural material. Moreover, based on Japans design code for earthquake-resistant buildings, buildings constructed after 1981 do not display a better performance compared to more recent constructions. Finally, the results show that for the same inundation depth, a higher damage probability exists along a ria coast due to higher flow velocities, confirmed by numerical simulation and survivor videos. These new findings are useful for building damage assessment, town reconstruction, and comparison of vulnerability functions in future studies.

Assessment of tsunami hazards in ports and their impact on marine vessels derived from tsunami models and the observed damage data

This paper presents a detailed study of tsunami hazard in ports and its correlation with the damage suffered by marine vessels. The study aims to develop a new loss function to estimate the potential damage of marine vessels due to tsunami attack based on a novel multivariate statistical modeling method, which used several explanatory variables simultaneously to estimate an outcome or the probability of such outcome. In the first part of the paper, tsunami heights and velocities are numerically modeled by using high-resolution bathymetry and topography data for the southern part of Honshu Island. We apply statistical methods to the complete sequence of spatially distributed time series of tsunami parameters in order to obtain the best fit with the observed damage data. In the second part, we develop loss functions for marine vessels by using ordinal regression, which uses simultaneously several explanatory variables. We perform several statistical tests to determine the appropriate model variables to be used in developing three-dimensional loss estimation surfaces, which provide probability of loss for each combination of measured or simulated values of tsunami parameters. The main feature of the developed loss functions presented in this study is their capability to integrate the key factors influencing the damage probability, such as tsunami parameters, characteristics of marine vessels and the impact of collision experienced by the vessels during the tsunami. Such a robust method, therefore, is crucially important to understand the tsunami impact on ports and, particularly on marine vessels.

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

Tsunami damage, fragility and vulnerability functions are statistical models which provide an estimate of expected damage or losses due to tsunami. They allow for quantification of risk, and so are a vital component of catastrophe models used for human and financial loss estimation, and for land-use and emergency planning. This paper collates and reviews the currently available tsunami fragility functions in order to highlight the current limitations, outline significant advances in this field, make recommendations for model derivation, and propose key areas for further research. Existing functions are first presented, and then key issues are identified in the current literature for each of the model components: building damage data (the response variable of the statistical model), tsunami intensity data (the explanatory variable), and the statistical model which links the two. Finally, recommendations are made regarding areas for future research and current best practices in deriving tsunami fragility functions (section 6). The information presented in this paper may be used to assess the quality of current estimations (both based on the quality of the data, and the quality of the models and methods adopted), and to adopt best practice when developing new fragility functions.

Building Damage Assessment and Implications for Future Tsunami Fragility Estimations

Abstract This chapter summarizes perspectives on building damage assessment and their implication for future fragility estimations using damage data from recent tsunamis, including the 2011 event in Japan. Causes of building damage, i.e., a combination of hydrostatic and hydrodynamic forces, debris impact and foundation effects, are explained. Damage scales used in previous studies are introduced, including the scale used for the 2011 tsunami, and possible future damage to be considered in the construction of tsunami evacuation shelters is discussed. Fragility estimations methods are presented, including the PTVA/BTV methods and fragility functions. Fragility functions provide superior, quantitative information compared to other tools, and are thus discussed in depth, from statistical considerations (differences between each model, including the traditional liner models and the new generalized linear models), to the factors affecting the structural performance of buildings. These factors include the type of construction material and the buildings height, function and surroundings. Future improvements and applications of fragility functions considering model diagnostics, additional tsunami parameters, additional building characteristics, and damage scale improvements are also considered. In this sense, research on fragility functions that cover both the preceding earthquake induced damage and the subsequent damage by tsunami represents a challenging future research topic.

Can we spread the risk? A demand-share perspective to sustained hamstring health. Practical examples

This short practical paper gives examples of exercises of synergists that assist the biceps femoris long head, the most commonly injured hamstring muscle in repeated sprint field sports (soccer, rugby) with the aim of reducing risk of or recurrence of injury. It is a companion to the theoretical piece of the same name.