Mapping Seismic Hazard for Canadian Sites Using Spatially Smoothed Seismicity Model

Chao Feng , Han-Ping Hong

International Journal of Disaster Risk Science ›› 2023, Vol. 14 ›› Issue (6) : 898 -918.

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International Journal of Disaster Risk Science ›› 2023, Vol. 14 ›› Issue (6) : 898 -918. DOI: 10.1007/s13753-023-00521-x
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Mapping Seismic Hazard for Canadian Sites Using Spatially Smoothed Seismicity Model

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Abstract

The estimated seismic hazard based on the delineated seismic source model is used as the basis to assign the seismic design loads in Canadian structural design codes. An alternative for the estimation is based on a spatially smoothed source model. However, a quantification of differences in the Canadian seismic hazard maps (CanSHMs) obtained based on the delineated seismic source model and spatially smoothed model is unavailable. The quantification is valuable to identify epistemic uncertainty in the estimated seismic hazard and the degree of uncertainty in the CanSHMs. In the present study, we developed seismic source models using spatial smoothing and historical earthquake catalogue. We quantified the differences in the estimated Canadian seismic hazard by considering the delineated source model and spatially smoothed source models. For the development of the spatially smoothed seismic source models, we considered spatial kernel smoothing techniques with or without adaptive bandwidth. The results indicate that the use of the delineated seismic source model could lead to under or over-estimation of the seismic hazard as compared to those estimated based on spatially smoothed seismic source models. This suggests that an epistemic uncertainty caused by the seismic source models should be considered to map the seismic hazard.

Keywords

Adaptive kernel smoothing / Fixed kernel smoothing / Ground motion model / Probabilistic seismic hazard analysis / Seismic hazard map / Uniform hazard spectra

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Chao Feng, Han-Ping Hong. Mapping Seismic Hazard for Canadian Sites Using Spatially Smoothed Seismicity Model. International Journal of Disaster Risk Science, 2023, 14(6): 898-918 DOI:10.1007/s13753-023-00521-x

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