TY - JOUR
T1 - 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
AU - Charvet, I.
AU - Suppasri, A.
AU - Imamura, F.
N1 - Funding Information:
The authors would like to thank Dr Jeremy Bricker, from IRIDeS (Tohoku University), for providing the numerical simulation results that guided the geographical data split decision making, and for his invaluable insight into Ishinomaki inundation processes during the 2011 tsunami. Similarly, the authors would like to thank Dr Ioanna Ioannou, from EPICentre (UCL—University College London) for her statistical insight. The work of Ingrid Charvet has been funded by JSPS (Japan Society for the Promotion of Science), and the work of all authors has been supported through the collaboration between UCL and Tohoku University (IRIDeS).
Publisher Copyright:
© 2014, The Author(s).
PY - 2014/10
Y1 - 2014/10
N2 - 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.
AB - 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.
KW - Building damage
KW - Fragility functions
KW - Ordinal regression
KW - Tsunami
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U2 - 10.1007/s00477-014-0850-2
DO - 10.1007/s00477-014-0850-2
M3 - Article
AN - SCOPUS:84920255289
SN - 1436-3240
VL - 28
SP - 1853
EP - 1867
JO - Stochastic Environmental Research and Risk Assessment
JF - Stochastic Environmental Research and Risk Assessment
IS - 7
ER -