Abstract
Based on the definition of tsunami risk, we quantitatively evaluated the annual expected tsunami loss ratio (Tsunami Risk Index) and clarified the quantitative effects of epistemic uncertainties in tsunami hazard assessments on the tsunami risk of buildings by combining probabilistic information regarding tsunami inundation depths at target points and tsunami fragility assessments of buildings. For the risk assessment, we targeted buildings with four different structures (reinforced concrete, steel, brick, wood) located in three different areas (Soma, Sendai, Kesennuma). In conclusion, we demonstrated that the expected tsunami risk could vary by approximately two orders of magnitude when considering tsunami hazard uncertainties between the 95th percentile and the 5th percentile. In addition, we quantitatively clarified the fact that we cannot properly understand the tsunami risk by evaluating the tsunami fragility alone. For example, the analysis results indicate that the tsunami risk of a wood building located in Kesennuma is lower than that of a reinforced concrete building located in either Soma or Sendai.
Highlights
The risks of natural disasters can be understood by multiplying the magnitude of the hazard and the evaluated vulnerability [1]
Tsunami risks can be understood by multiplying the probabilistic tsunami hazard assessment and the tsunami fragility assessment, which represents the vulnerability of the tsunami
A wood building located in Kesennuma has a lower tsunami risk than a reinforced concrete building located in either Soma or Sendai and a steel building located in Soma is at a higher tsunami risk than a wood building located in Kesennuma
Summary
The risks of natural disasters can be understood by multiplying the magnitude of the hazard and the evaluated vulnerability [1]. It is necessary to carry out probabilistic natural hazard assessments in order to properly evaluate such risks. Based on this concept, tsunami risks can be understood by multiplying the probabilistic tsunami hazard assessment and the tsunami fragility assessment, which represents the vulnerability of the tsunami. Probability estimations of tsunami inundation depths at inland locations constitute necessary input information for the quantitative evaluation of tsunami risks; not many studies have conducted probabilistic tsunami inundation assessments (e.g., [2,3,4,5,6,7,8]). Goda et al [4] developed stochastic random-field slip models for the
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