Panel Review of the USGS 2023 Conterminous U.S. Time-Independent Earthquake Rupture Forecast

This report documents the assessment by the U.S. Geological Survey (USGS) Earthquake Rupture Forecast (ERF) Review Panel of the draft ERF for the conterminous United States (CONUS-ERF23) proposed for the 2023 update of the National Seismic Hazard Model (NSHM23). Panel members participated with the ERF Development Team in several verification and validation exercises, including spot checks of the hazard estimates at key localities. The ERF23 forecast is substantially different from its predecessor, yielding relative differences in hazard that exceed ±50% in some low-hazard areas. These stem primarily from the new model ingredients—new faults, revised deformation rates, and updated seismicity catalogs—rather than from changes in the modeling methodology. The panel found that the main hazard changes are scientifically justified at the long return periods (≥475 yr) for which NSHM23 is applicable. Based on its evaluation of the model, the panel offered six actionable recommendations for improvements to the draft ERF23 for the western United States and two for the Cascadia subduction zone. All eight recommendations were adopted by the USGS for the revised ERF, as documented by Field et al. (2023). The panel concluded that CONUS-ERF23 represents a significant scientific advance over ERF18 and should be incorporated, after suitable revision, into NSHM23. The panel also considered changes to the CONUS-ERF that cannot be feasibly implemented in NSHM23 but could lead to future improvements. Among these aspirational recommendations, the panel prioritized the development of time-dependent extensions of ERF23 that include models of seismic renewal and clustering. The panel endorsed USGS efforts to extend the NSHM to a national earthquake forecasting enterprise capable of continually updating and disseminating authoritative information about future earthquake occurrence through a well-designed hazard-risk interface. Operational earthquake forecasting will place new and heavy demands on USGS cyberinfrastructure, requiring a more integrated approach to software development and workflow management.