Bayesian tsunami fragility modeling considering input data uncertainty View Full Text


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Article Info

DATE

2017-07

AUTHORS

Raffaele De Risi, Katsuichiro Goda, Nobuhito Mori, Tomohiro Yasuda

ABSTRACT

Empirical tsunami fragility curves are developed based on a Bayesian framework by accounting for uncertainty of input tsunami hazard data in a systematic and comprehensive manner. Three fragility modeling approaches, i.e. lognormal method, binomial logistic method, and multinomial logistic method, are considered, and are applied to extensive tsunami damage data for the 2011 Tohoku earthquake. A unique aspect of this study is that uncertainty of tsunami inundation data (i.e. input hazard data in fragility modeling) is quantified by comparing two tsunami inundation/run-up datasets (one by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government and the other by the Tohoku Tsunami Joint Survey group) and is then propagated through Bayesian statistical methods to assess the effects on the tsunami fragility models. The systematic implementation of the data and methods facilitates the quantitative comparison of tsunami fragility models under different assumptions. Such comparison shows that the binomial logistic method with un-binned data is preferred among the considered models; nevertheless, further investigations related to multinomial logistic regression with un-binned data are required. Finally, the developed tsunami fragility functions are integrated with building damage-loss models to investigate the influences of different tsunami fragility curves on tsunami loss estimation. Numerical results indicate that the uncertainty of input tsunami data is not negligible (coefficient of variation of 0.25) and that neglecting the input data uncertainty leads to overestimation of the model uncertainty. More... »

PAGES

1253-1269

References to SciGraph publications

  • 2015-12. A multivariate generalized linear tsunami fragility model for Kesennuma City based on maximum flow depths, velocities and debris impact, with evaluation of predictive accuracy in NATURAL HAZARDS
  • 2015-10. Stochastic analysis and uncertainty assessment of tsunami wave height using a random source parameter model that targets a Tohoku-type earthquake fault in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2015-04. Bayesian Cloud Analysis: efficient structural fragility assessment using linear regression in BULLETIN OF EARTHQUAKE ENGINEERING
  • 2014-10. 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 in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 1989. Generalized Linear Models in NONE
  • 2014. Evaluation of Existing Fragility Curves in SYNER-G: TYPOLOGY DEFINITION AND FRAGILITY FUNCTIONS FOR PHYSICAL ELEMENTS AT SEISMIC RISK
  • 2013-02. Tsunami damage to coastal defences and buildings in the March 11th 2011 Mw9.0 Great East Japan earthquake and tsunami in BULLETIN OF EARTHQUAKE ENGINEERING
  • 2013-03. Joint Monte Carlo and possibilistic simulation for flood damage assessment in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2014-12. Sensitivity of tsunami wave profiles and inundation simulations to earthquake slip and fault geometry for the 2011 Tohoku earthquake in EARTH, PLANETS AND SPACE
  • 2016-12. Uncertainty modeling and visualization for tsunami hazard and risk mapping: a case study for the 2011 Tohoku earthquake in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2013-03. Building damage characteristics based on surveyed data and fragility curves of the 2011 Great East Japan tsunami in NATURAL HAZARDS
  • 2014-05. Best-fit distribution and log-normality for tsunami heights along coastal lines in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2014-09. Empirical fragility assessment of buildings affected by the 2011 Great East Japan tsunami using improved statistical models in NATURAL HAZARDS
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