A physics-based earthquake simulator replicates seismic hazard statistics across California

Simplifying complex fault data for systems-level analysis: Earthquake geology inputs for U.S. NSHM 2023

As part of the U.S. National Seismic Hazard Model (NSHM) update planned for 2023, two databases were prepared to more completely represent Quaternary-active faulting across the western United States: the NSHM23 fault sections database (FSD) and earthquake geology database (EQGeoDB). In prior iterations of NSHM, fault sections were included only if a field-measurement-derived slip rate was estimated along a given fault. By expanding this inclusion criteria, we were able to assess a larger set of faults for use in NSHM23. The USGS Quaternary Fault and Fold Database served as a guide for assessing possible additions to the NSHM23 FSD. Reevaluating available data from published sources yielded an increase of fault sections from ~650 faults in NSHM18 to ~1,000 faults proposed for use in NSHM23. EQGeoDB, a companion dataset linked to NSHM23 FSD, contains geologic slip rate estimates for fault sections included in FSD. Together, these databases serve as common input data used in deformation modeling, earthquake rupture forecasting, and additional downstream uses in NSHM development.

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Space–Time Trade-Off of Precursory Seismicity in New Zealand and California Revealed by a Medium-Term Earthquake Forecasting Model

The ‘Every Earthquake a Precursor According to Scale’ (EEPAS) medium-term earthquake forecasting model is based on the precursory scale increase (Ψ) phenomenon and associated scaling relations, in which the precursor magnitude MP is predictive of the mainshock magnitude Mm, precursor time TP and precursory area AP. In early studies of Ψ, a relatively low correlation between TP and AP suggested the possibility of a trade-off between time and area as a second-order effect. Here, we investigate the trade-off by means of the EEPAS model. Existing versions of EEPAS in New Zealand and California forecast target earthquakes of magnitudes M > 4.95 from input catalogues with M > 2.95. We systematically vary one parameter each from the EEPAS distributions for time and location, thereby varying the temporal and spatial scales of these distributions by two orders of magnitude. As one of these parameters is varied, the other is refitted to a 20-year period of each catalogue. The resulting curves of the temporal scaling factor against the spatial scaling factor are consistent with an even trade-off between time and area, given the limited temporal and spatial extent of the input catalogue. Hybrid models are formed by mixing several EEPAS models, with parameter sets chosen from points on the trade-off line. These are tested against the original fitted EEPAS models on a subsequent period of the New Zealand catalogue. The resulting information gains suggest that the space–time trade-off can be exploited to improve forecasting.

Seismogenic Potential of the Main Himalayan Thrust Constrained by Coupling Segmentation and Earthquake Scaling

Recent studies have shown that the Himalayan region is under the threat of earthquakes of magnitude nine or larger. These estimates are based on comparisons of the geodetically inferred moment deficit rate with the seismicity of the region. However, these studies did not account for the physics of fault slip, specifically the influence of frictional barriers on earthquake rupture dynamics, which controls the extent and therefore the magnitude of large earthquakes. Here we combine an improved probabilistic estimate of moment deficit rate with results from dynamic models of the earthquake cycle to more fully assess the seismogenic potential of the Main Himalayan Thrust (MHT). We propose a straightforward and efficient methodology for incorporating outcomes of physics-based earthquake cycle models into hazard estimates. We show that, accounting for uncertainties on the moment deficit rate, seismicity and earthquake physics, the MHT is prone to rupturing in M w 8.7 earthquakes every T > 200 years.