Publications

Since 2015 the Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programmes and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset comprising structural and occupancy information regarding the residential, commercial and

Numerical simulations of sequences of earthquakes and aseismic slip (SEAS) have made great progress over past decades to address important questions in earthquake physics. However, significant challenges in SEAS modeling remain in resolving multiscale interactions between earthquake nucleation, dynamic rupture, and aseismic slip, and understanding physical factors controlling observables such as s

AbstractAftershocks (earthquakes clustered spatially and chronologically near the occurrence of a causative earthquake) are ongoing in southwestern Puerto Rico after a series of earthquakes, which include a magnitude 6.4 earthquake that occurred near Barrio Indios, Guayanilla, on January 7, 2020, and affected the surrounding area. This report estimates the expected duration of these aftershocks by

Modern seismology has been able to take advantage of several technological advances. These include feedback loops in the seismometer, specialized digitizers with absolute timing, and compression formats for storing data. While all of these advances have helped to improve the field, they can also leave newcomers a bit confused. Our goal here is to give a brief overview of how recordings of seism

Large earthquakes like in Wenchuan in 2008, MW 7.9, Sichuan, China, provide opportunity for earthquake early warning (EEW) as many heavily shaken areas are far (~50 km) from the epicenter and warning time could be long enough (≥ 5 s) to take effective preventative action. On the other hand, earthquakes with magnitudes larger than ~M 6.5 are challenging for EEW since source dimensions need to be de

The US Geological Survey (USGS) “Did You Feel It?”® (DYFI) system is an automated system for rapidly collecting macroseismic intensity data from Internet users’ shaking and damage reports and generating intensity maps immediately following earthquakes.Although the collection and assignment of DYFI-based Macroseismic Intensity (MI) data depart from traditional assignments, they are made more quickl

No abstract available.

Rocky, alpine mountains are prone to mass wasting from debris flows. The Chalk Cliffs study area (central Colorado, USA) produces debris flows annually. These debris flows are triggered when overland flow driven by intense summer convective storms mobilizes large volumes of sediment within the channel network. Understanding the debris flow hazard in this, and similar alpine settings, requires

I use template matching and precise relative relocation techniques to develop a high-resolution earthquake catalog for the initial portion of the 2019 Ridgecrest earthquake sequence, from July 4-16, encompassing the foreshock sequence and the first 10+ days of aftershocks following the Mw 7.1 mainshock. Using 13,525 routinely cataloged events as waveform templates, I detect and precisely locate a

The three sets of ground‐motion predictions (GMPs) of Boore (2018; hereafter, B18) are compared with a much larger dataset than was used in deriving the predictions. The B18 GMPs work well for response spectra at periods between ∼0.15∼0.15 and 4.0 s after an adjustment accounting for a path bias at distances beyond 200 km—this was the maximum distance used to derive the stress parameters on which

The 2019 M6.4 and M7.1 Ridgecrest earthquake sequence occurred in the eastern California shear zone (ECSZ). The mainshock ruptured the Little Lake fault zone and aftershocks extended from the Garlock fault in the south, to the southern end of the 1872 M7.5 Owens Valley earthquake rupture in the north. We present data from the Southern California Seismic Network (SCSN) and partner seismic networks

The selection and weighting of ground‐motion models (GMMs) introduces a significant source of uncertainty in U.S. Geological Survey (USGS) National Seismic Hazard Modeling Project (NSHMP) forecasts. In this study, we evaluate 18 candidate GMMs using instrumental ground‐motion observations of horizontal peak ground acceleration (PGA) and 5%‐damped pseudospectral acceleration (0.02–10 s) for tectoni