Impact of Declustering on Probabilistic Seismic Hazard Estimates in the Western United States
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Authors
Maher, Emily L
Issue Date
2023
Type
Thesis
Language
Keywords
Alternative Title
Abstract
This study explores the relationship between declustering methods and earthquake hazard assessments, focusing on their implications for the USGS National Seismic Hazard Model (NSHM). Accurate seismic hazard analysis is crucial for informed decision-making and risk mitigation in engineering and urban planning.The Zaliapin and Ben-Zion (ZBZ) declustering method, published in 2020, permits multiple iterations of declustering while maintaining the spatial distribution of background seismicity. It was employed to investigate the impact of retaining different proportions of background events in the catalog. Contour maps revealed that ZBZ and USGS declustering methods differ in their event removal patterns. The ZBZ method tended to remove events more densely clustered in areas with higher seismic activity, reflecting its sensitivity to local seismicity.
This study directly linked the number of retained background events in the catalog and earthquake hazard estimates. Maintaining approximately 38% of these events aligned hazard curves with USGS's results, indicating the practical significance of declustering in the creation of hazard assessments.
Variations from 10% to 90% of kept background events led an increase by nearly a factor of three in Peak Ground Acceleration (PGA) estimates. Underscoring the vital role of declustering in accurately characterizing earthquake hazards, especially when the proportion of background events varies.
In conclusion, this research advances the understanding of declustering's impact on earthquake hazard assessments, offering practical insights for enhancing accuracy. These findings contribute to seismology and can inform and improve earthquake preparedness and mitigation strategies. Future work includes expanding the analysis to larger datasets and exploring the effects of declustering in different geographic regions.