Journal of Seismology and Earthquake Engineering

Journal of Seismology and Earthquake Engineering

Assessing the Sensitivity of Seismic Loss Estimation to the Geographic Resolution of Building Exposure Model

Document Type : Research Article

Authors
Nazila Kheirkhah 1
Mohsen Kalantari 2
Erfan Firuzi 3
Kambod Amini Hosseini 4
1 M.Sc. Degree, Institute of Geophysics, University of Tehran; Tehran; Iran
2 M.Sc. Degree, K. N. Toosi University of Technology; Tehran, Iran
3 Ph.D. Degree, International Institute of Earthquake Engineering and Seismology (IIEES), Tehran, Iran
4 Associate Professor, Earthquake Risk Management Research Center, International Institute of Earthquake Engineering and Seismology (IIEES), Tehran, Iran
10.48303/jsee.2023.1972319.1034
Abstract
This paper assessed the sensitivity of seismic losses to the geographic resolution of building exposure model. One of the key steps of seismic risk assessment is providing an accurate and reliable building inventory. Generally, building exposure model is derived from various sources of information with different degrees of quality and accuracy. Therefore, compilation of exposure model is a complex process that is associated with uncertainties. In this regard, selecting the most appropriate geographic resolution of building exposure model is a challenge. There is a trade-off between the accuracy of ground motion values in the centroid of grid cells and computation efficiency. On the one hand, selecting a higher resolution will result in less efficient computing. Increased grid cell size, on the other hand, will impose uncertainty on the results due to inaccuracy in estimating ground motion values in the proper location of buildings. The purpose of this study is to address this question “what is the impact of geographic resolution of exposure model on the seismic risk assessment?”. To do so, a sensitivity analysis with three distinct levels of resolution was performed in Tehran, Iran, as a case study, to evaluate the impact of exposure model resolution on estimated losses. The results showed that total damage over the region is almost insensitive to the resolution of exposure models; while, a more accurate damage map with lower standard deviation is achieved by refining resolutions. This is an important outcome that will assist researchers performing seismic risk assessment in large geographic areas, like countries or provinces, to be aware of the effects of geographic resolution of exposure model on results.
Keywords
Exposure Model
Geographic Resolution
Seismic Risk Assessment
Uncertainty
Tehran
Subjects
  1. Firuzi, E., Ansari, A., Amini Hosseini, K., & Rashidabadi, M. (2019) Probabilistic earthquake loss model for residential buildings in Tehran, Iran to quantify annualized earthquake loss. Bulletin of Earthquake Engineering, 17(5), 2383-2406.
  2. Firuzi, E., Ansari, A., Amini Hosseini, K., & Karkooti, E. (2020) Developing a customized system for generating near real time ground motion ShakeMap of Iran’s earthquakes. Journal of Earthquake Engineering, 1-23.
  3. Crowley, H. (2006) Earthquake Risk Assessment: Present Shortcomings and Future Directions, Perspectives on European Earthquake Engineering and Seismology,  515-532.
  4. Organization for Economic Cooperation and Development (OECD) (2012) Global Modelling of Natural Hazard Risks: Enhancing Existing Capabilities to Address New Challenges, OECD Global Science Forum (online), (last accessed November 2014).
  5. Wieland, M. Pittro, M., Parolai, S. Begaliev, U. Yasunov, P. Tyagunov, S., Moldibekov, B. Saidiy, S., Iiyasov, I., Abakanov, T. (2015) A Multiscale Exposure Model for Seismic Risk Assessment in Central Asia, Seismological Research Letter, 86(1), 210-222.
  6. Bazzurro, P. & Park, J. (2007, July) The effects of portfolio manipulation on earthquake portfolio loss estimates. In Proceedings of the 10th International Conference on Applications of Statistics and Probability in Civil Engineering, Tokyo, Japan, 31.
  7. Bal, I.E., Bommer, J.J., Stafford, P.E., Crowley, H., Pinho, R. (2010) The influence of Geographical Resolution of Urban Exposure Data in an Earthquake Loss Model for Istanbul. Earthquake Spectra, 26(3), 619-634.
  8. Scheingraber, C., & Käser, M.A. (2019) The impact of portfolio location uncertainty on probabilistic seismic risk analysis. Risk Analysis, 39(3), 695-712.
  9. Dabbeek, J., Crowley, H., Silva, V., Weatherill, G., Paul, N., & Nievas, C. I. (2021) Impact of exposure spatial resolution on seismic loss estimates in regional portfolios. Bulletin of Earthquake Engineering, 19(14), 5819-5841.
  10. Statistical Centre of Iran (SCI), 1956–2015, Statistical Centre of Iran, Vice-Presidency for Strategic Planning and Supervision, Tehran, National Census of Population and Housing Technical Reports, Sarshomāri 2016 (1395), 2011 (1390), 2006 (1385), 1996 (1375), 1986 (1365), and 1976 (1355): Tehran, SCI, formerly, the Plan & Budget Organization of the Imperial Government of Iran, Statistical Centre, http://www.amar.org.ir/Default.aspx?tabid=116 (accessed 2018).
  11. Motamed, H., Calderon, A., Silva, V., & Costa, C. (2019) Development of a probabilistic earthquake loss model for Iran. Bulletin of Earthquake Engineering, 17(4), 1795-1823.
  12. Mansouri, B., Kiani, A., & Amini-Hosseini, K. (2014) A Platform for earthquake risk assessment in Iran case studies: Tehran scenarios and Ahar-Varzeghan earthquake. Journal of Seismology and Earthquake Engineering, 16(1), 51-69.
  13. Shahbazi, P., Mansouri, B., Ghafory-Ashtiany, M., & Kaeser, M. (2020) Introducing loss transfer functions to model seismic financial loss: A case study of Iran. International Journal of Disaster Risk Reduction, 51, 101883.
  14. Bommer, J.J., Spence, R., Erdik, M., Tabuchi, S., Aydinoglu, , Booth, E., del Rey, D., and Peterken, O. (2002) Development of an earthquake loss model for Turkish catastrophe insurance. J. Seismol., 6, 431–446.
  15. Berberian, M. (1976) An Explanatory Note on the First Seismotectonic Map of Iran, a Seismotectonic Review of the Country. Contribution to the Seismotectonic of Iran (Part III).
  1. Japan International Cooperation Agency (JICA) (2000) Report, The Study on Seismic Microzoning of the Greater Tehran Area in the Islamic Republic of Iran, Final Report, Japan International Cooperation Agency (JICA), Centre for Earthquake and Environmental Studies of Tehran (CEST) Tehran Municipality, November.
  2. Berberian, Manuel, and Robert S. Yeats (2017) Tehran: An earthquake time bomb.
  3. Kalantari, M., Firuzi, E., & Soroushian, S. (2022) Estimating Annualized Earthquake Loss for Residential Buildings in Tehran, Iran.
  4. Mansouri, B., Ghafory-Ashtiany, M., Amini-Hosseini, K., Nourjou, R., & Mousavi, M. (2010). Building seismic loss model for Tehran. Earthquake Spectra, 26(1), 153-168.
  5. Hessami, K., Jamali, F., and Tabassi, H. (2003) Active Fault Maps of Iran. Seismotectonic Department, Seismology Research Center, Institute of Earthquake Engineering and Seismology (IIEES), Iran.
  6. Moinfar, A., Mahdavian, A., Maleki, E. (1994) Historical and instrumental earthquake data collection of Iran. Publication Iranian Culture. Affairs Inst, Tehran, p 446
  7. Pagani, M., Monelli, D., Weatherill, G., Danciu, L., Crowley, H., Silva, V., ... & Vigano, D. (2014) OpenQuake engine: An open hazard (and risk) software for the global earthquake model. Seismological Research Letters, 85(3), 692-702.
  8. Wells, D.L., and K.J. Coppersmith (1994) New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement. Bull. Seism. Soc. Am., 84, 974-1002.
  9. Kale, O., Akkar, S., Ansari, A. and Hamzehloo, H. (2015) A Ground Motion Predictive Model for Iran and Turkey for Horizontal PGA, PGV, and 5% Damped Response Spectrum: Investigation of Possible Regional Effects. Bulletin of the Seismological Society of America, 105(2A), 963-980.
  10. Kotha, S.R., Bindi, D. and Cotton, F. (2016) Partially Non-Ergodic Region Specific GMPE for Europe and Middle-East. Bulletin of Earthquake Engineering, 14(4), 1245-1263.
  11. Akkar, S. and Bommer, J.J. (2010) Empirical Equations for the Prediction of PGA, PGV, and Spectral Accelerations in Europe, the Mediterranean region, and the Middle East. Seismological Research Letters, 81(2), 195-206.
  12. Zhao, J.X., Zhang, J., Asano, A., Ohno, Y., Oouchi, T., Takahashi, T., ... and Fukushima, Y. (2006) Attenuation Relations of Strong Ground Motion in Japan Using Site Classification based on Predominant Period. Bulletin of the Seismological Society of America, 96(3), 898-913.
  13. Idriss, I.M. (2014) An NGA-West2 Empirical Model for Estimating the Horizontal Spectral Values Generated by Shallow Crustal Earthquakes. Earthquake Spectra, 30(3), 1155-1177.
  14. Weatherill, G.A., Silva, V., Crowley, H., & Bazzurro, P. (2015) Exploring the impact of spatial correlations and uncertainties for portfolio analysis in probabilistic seismic loss estimation. Bulletin of Earthquake Engineering, 13(4), 957-981.
  15. Verros, S.A., Wald, D.J., Worden, C.B., Hearne, M., Ganesh, M. (2017) Computing spatial correlation of ground motion intensities for shakemap. Computers and Geosciences, 99, 145-154.
  16. Zafarani, H., Ghafoori, S.M.M., & Adlaparvar, M.R. (2022) Spatial correlation of peak ground motions and pseudo spectral acceleration based on the Iranian multievent datasets. Journal of Earthquake Engineering, 26(12), 6042-6062.
  17. Zafarani, H., Noorzad, A., Ansari, A., & Bargi, K. (2009) Stochastic modeling of Iranian earthquakes and estimation of ground motion for future earthquakes in Greater Tehran. Soil Dynamics and Earthquake Engineering, 29(4), 722-741.
  18. Fallah Tafti, M., Amini Hosseini, K., & Mansouri, B. (2020) Generation of new fragility curves for common types of buildings in Iran. Bulletin of Earthquake Engineering, 18(7), 3079-3099.
  19. Bastami, M., Abbasnejadfard, M., Motamed, H., Ansari, A., & Garakaninezhad, A. (2022) Development of hybrid earthquake vulnerability functions for typical residential buildings in Iran. International Journal of Disaster Risk Reduction, 103087.
  20. Silva, V,. Crowley, H,. Yepes, C,. Pinho, R,. (2014), Presentation of the OpenQuake Engine, an Open Source Software for Seismic Hazard and Risk Assessment, Tenth U.S. National Conference on Earthquake Engineering, Anchorage, Alaska
  21. Whitman, R.V., Anagnos, T., Kircher, C.A., Lagorio, H.J., Lawson, R.S., and Schneider, P. (1997) Development of a national earthquake loss estimation methodology. Earthquake Spectra, 13, 643–661.
Journal of Seismology and Earthquake Engineering
Volume 23, Issue 3
Summer 2021
Pages 67-78

  • Receive Date 08 November 2022
  • Revise Date 10 January 2023
  • Accept Date 28 January 2023
  • Publish Date 01 August 2021