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Insights into earthquake hazard map performance from shaking history simulations
Kris Vanneste1, Seth Stein2, Thierry Camelbeeck3
1Royal Observatory of Belgium, B-1180, Brussels, Belgium. kris.vanneste@oma.be.
Recent earthquakes have shown stronger shaking than predicted by earthquake hazard maps. This study suggests probabilistic seismic hazard analysis (PSHA) is internally consistent, but validating map accuracy against real-world events remains challenging due to inherent variability.
Area of Science:
- Earthquake seismology
- Geophysics
- Hazard assessment
Background:
- Recent large earthquakes have exhibited ground shaking exceeding predictions from standard earthquake hazard maps for typical return periods.
- Discrepancies raise questions about the accuracy of current probabilistic seismic hazard analysis (PSHA) methodologies and map parameters.
Purpose of the Study:
- To investigate the discrepancy between predicted and observed earthquake shaking.
- To assess the verification (map implementation) and validation (forecasting accuracy) of seismic hazard maps.
Main Methods:
- Simulated an area's seismic history to generate shaking distributions.
- Compared simulated "observed" shaking with predictions from hazard maps created using identical parameters.
- Evaluated map performance by assessing internal consistency and forecasting capability.
Main Results:
- Simulated shaking distributions showed consistency with the hazard map's mean predictions.
- Individual simulated earthquake histories exhibited significant scatter, with infrequent large events causing shaking stronger than mapped.
- Probabilistic seismic hazard analysis (PSHA) demonstrated internal consistency, suggesting maps are "built right" in terms of methodology.
Conclusions:
- The study suggests that probabilistic seismic hazard analysis (PSHA) is internally consistent and verified.
- Validating seismic hazard maps against actual earthquake histories is complex due to inherent variability and the difficulty in distinguishing chance from parameter bias.
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