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Earthquake early warning (EEW) systems are relatively new technologies having first emerged as regional systems in the 1990s. Japan was the first nation to develop and implement a nationwide system in October 2007, and in the United States, ShakeAlert® became available on the entire length of the US West Coast in May 2021. Assessing how EEW is perceived and utilized by alert recipients is considered essential. Such assessments are necessary to evaluate whether alert recipients are taking advantage of alert messages to initiate protective actions upon receipt of an alert, how they regard the usefulness of alerts, desirable thresholds for issuing alerts, and other aspects of these systems. Having information from users will also facilitate assessments of the success of earthquake preparedness educational programs such as the ShakeOut and whether annual drills which include information on EEW systems are resulting in behavioral response consistent with the content of these programs. Finally, information on EEW utilization will provide data useful to social scientists who study hazards to advance our understanding of behavioral response to warnings. Survey research in the aftermath of a significant earthquake in which an EEW has been issued is one obvious method of achieving these objectives and there already exist a number of survey instruments for this purpose. A related strategy and the goal of the present research is to develop a brief questionnaire, consistent with those already developed, as a supplement to the United States Geological Survey’s “Did You Feel It?” questionnaire that has provided earthquake intensities and information on behavioral response in earthquakes, both domestic and international, since 2004. Having the intensity level at each respondent’s location is essential for relating their perspectives and actions to the shaking they experienced.

In their analysis of the U.S. Geological Survey’s (USGS) “Did You Feel It?” (DYFI) data Hough and Martin (2021) claim, among other assertions, that the following: Socioeconomic and geopolitical factors can introduce biases in the USGS’ characterization of earthquakes and their effects, especially if online data collection systems are not designed to be broadly accessible;These biases can, in turn, potentially cascade in myriad ways, potentially shaping our understanding of an earthquake’s impact and the characterization of seismic hazard; andCaution should be urged when relying on data from the DYFI system to characterize the distribution of shaking from large earthquakes in India and other parts of the world (outside of the United States). Claims of inequity in access, systematic data biases, or urging caution in the usage of data from critical governmental earthquake information systems should not be made, nor taken, lightly. Several assertions made by Hough and Martin (hereafter, H&M) about the nature of DYFI contributors—and the data they provide—leave a false narrative concerning DYFI system accessibility and quality that H&M have not adequately substantiated. I describe several shortcomings of H&M’s demographic statistics and methodology, focusing on four main concerns. First, DYFI has revolutionized and greatly facilitated access to reporting intensities, in contrast to H&M claims to the contrary. Second, because DYFI does not directly collect demographic data other than the observer’s location, any demographic analyses require extraordinary inferences, well outside the normal bounds of sociodemographic analyses. Third, independent of accessibility and the geographic distribution of contributions from the public, the macroseismic data collected are nonetheless representative of the shaking and impact at each location, of quality, rapid, and thus extremely useful. Lastly, H&M fail to cite critical and pertinent prior, highly relevant scholarly studies, and as such, they misrepresent the novelty of their own work as well as miss key practical matters detailed in those prior studies. Prior to rebutting what H&M claim DYFI does not do, I will remind the reader the ways in which DYFI excels.

This study assesses existing intensity prediction equations (IPEs) for small unspecified magnitude (M ≤3.5) earthquakes at short hypocentral distances (Dh) and explores such earthquakes’ contribution to the felt shaking hazard. In particular, we consider IPEs by Atkinson and Wald (2007) and Atkinson et al. (2014), and evaluate their performance based on “Did You Feel It” (DYFI) reports and recorded peak ground velocities (PGVs) in the central United States. Both IPEs were developed based on DYFI reports in the central and eastern United States with moment magnitudes above Mw 3.0. DYFI reports are often used as the ground truth when evaluating and developing IPEs, but they could be less reliable when there are limited responses for small-magnitude earthquakes. We first compare the DYFI reports with intensities interpolated from recorded PGVs. Results suggest a minimal discrepancy between the two when the intensity is large enough to be felt (i.e., M >2 and Dh

Since late 2018, the US Geological Survey (USGS) ground failure (GF) earthquake product has provided publicly available spatial estimates of earthquake-triggered landslide and liquefaction hazards, along with the qualitative hazard and population exposure-based alerts for M > 6 earthquakes worldwide and in near real time (within ∼30 min). Earthquake losses are oftentimes greatly aggravated by the impacts due to ground failure, yet those particular events with dramatic additional losses have not, heretofore, been rapidly identifiable. The GF product now provides situational awareness about the potential extent and severity of ground failure in the crucial time period before direct observations are available. We describe our implementation of the GF product and the lessons learned from the earthquakes that have occurred since the GF product was released. We describe the product design process, the underlying GF models, the methods we have developed for modeling uncertainty, and the development of the alert levels. The GF product has been produced in near real time for 320 events over the 2-year period since its public implementation in late 2018 through early 2021. The majority of these events yielded the lowest level (green) alerts for all ground-failure types, with 25 resulting in elevated hazard or exposure to landslides and 47 for liquefaction. In a qualitative comparison between the GF product alerts and GF occurrence information, we found that the product succeeds at assigning appropriate alert levels in the majority of cases. Based on our experience with the product, we have identified the following priorities for future improvements: (1) refinements of the underlying probabilistic models to incorporate severity and explicitly model the type of landslide/liquefaction; (2) development of models for fatalities and economic losses due to ground failure; and (3) estimation of the impacts of ground failure on infrastructure.

The US Geological Survey’s ShakeMap is used domestically and globally for post-earthquake emergency management and response, engineering analyses, financial instruments, and other decision-making activities. Recent developments in the insurance, reinsurance, and catastrophe bond sectors link payouts of potentially hundreds of millions of dollars to ShakeMap products. Similarly, building codes, post-earthquake building damage forensic evaluations, and geotechnical evaluations often rely on estimated peak response-spectral values for site-specific evaluations that may lead to costly analyses, retrofits, or other expenditures. Given such activities, financial, engineering, and other technical users demand processing specifications and a metadata trail for actuarial, escrow, and forensic purposes for each significant earthquake. Recent inquiries include how and why maps change with time, how to interpret metadata, and how to obtain the creation and update history of various map layers. Similarly, the collection of ShakeMap scenarios and historical ShakeMaps—either created in earlier versions or rerun as part of the latest version of the ShakeMap Atlas—warrant a full explanation of the inputs, processing, and archiving given their contribution to fragility curve development and loss model calibration. For these reasons, in addition to event-specific ShakeMap metadata and a comprehensive online ShakeMap Manual, we have crafted this practice paper to answer several of the most frequently asked technical questions. We also describe an application programming interface (API) for accessing site-specific shaking metrics and their uncertainties for earthquake forensic purposes in a consistent fashion. In all, we describe the advantages of employing ShakeMaps for these critical purposes as well as describe their limitations and uncertainties, offering an extensive set of instructions and disclaimers that can be referenced by ShakeMap users.

We introduce a Bayesian framework for incorporating time-varying noisy reported data on damage and loss information to update near real-time loss estimates/alerts for the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) system. Initial loss estimation by PAGER immediately following an earthquake includes several uncertainties. Historically, the PAGER’s alerting on fatality and economic losses has not incorporated location-specific reported data on physical damage or casualties for a given earthquake. The proposed framework provides the ability to include early reports on fatalities at any given time and improve the overall impact forecast for the earthquake. The reported data on fatalities or damage are generally incomplete and noisy, especially in the early hours of the disaster. To address these challenges, we develop a recursive Bayesian updating framework that takes into account the loss projection model and the measurement and model uncertainties. The framework is applied to loss data for three example earthquakes, and the results show that the proposed updating improves the loss estimates and alert level to the correct level within the first day of the earthquake.

Time-averaged shear wave velocity over the upper 30 m of the earth’s surface ( V S30) is a key parameter for estimating ground motion amplification as both a predictive and a diagnostic tool for earthquake hazards. The first-order approximation of V S30 is commonly obtained through a topographic slope–based or terrain proxy due to the widely available nature of digital elevation models. However, better-constrained V S30 maps have been developed in many regions. Such maps preferentially employ various combinations of V S30 measurements, higher-resolution elevation models, lithologic, geologic, geomorphic, and other proxies and often utilize refined interpolation schemes. We develop a new hybrid global V S30 map database that defaults to the global slope-based V S30 map, but smoothly inserts regional V S30 maps where available. In addition, we present comparisons of the default slope-based proxy maps against the new hybrid version in terms of V S30 and amplification ratio maps, and uncertainties in assigned V S30 values.

Earthquake early warning (EEW) entails detection of initial earthquake shaking and rapid estimation and notification to users prior to imminent, stronger shaking. EEW (ShakeAlert Phase 1, version 2.0) went operational in California in October 2019 and is coming to the rest of the U.S. West Coast. But what are the technical and social challenges to delivering actionable information on earthquake shaking before it arrives? Although there will be tangible benefits, there are also limitations. Basic seismological principles, alert communication challenges, and potential response actions, as well as substantial lessons learned from the use of EEW in Japan, point to more limited opportunities to warn and protect than perhaps many expect. This is in part because potential warning times vary by region and are influenced by tectonic environment, hypocentral depth, and the fault’s proximity to the alert user. For the U.S. West Coast, particularly for crustal earthquakes, warning times are shorter—and possible mitigation actions are likely to be less effective—than often maintained. Nevertheless, EEW is an additional arrow in the quiver of earthquake information tools available in the service of earthquake risk reduction. What is called for, then, is transparency and balance in the EEW discussion: along with its potential, the acknowledgment of EEW’s inherent and practical limitations is needed. Recognizing these limitations could, in fact, make EEW implementation more successful as part of a holistic earthquake mitigation strategy, where its role among other earthquake information tools is quite natural.

Large earthquakes, such as Wenchuan in 2008, Mw 7.9, Sichuan, China, provide an opportunity for earthquake early warning (EEW), as many heavily shaken areas are far (∼50 km) from the epicenter and warning times could be sufficient (≥5 s) to take preventive action. On the other hand, earthquakes with magnitudes larger than ∼M 6.5 are challenging for EEW because source dimensions need to be defined to adequately estimate shaking. Finite-fault rupture detector (FinDer) is an approach to identify fault rupture extents from real-time seismic records. In this study, we playback local and regional onscale strong-motion waveforms of the 2008 Mw 7.9 Wenchuan, 2013 Mw 6.6 Lushan, and 2017 Mw 6.5 Jiuzhaigou earthquakes to study the performance of FinDer for the current layout of the China Strong Motion Network. Overall, the FinDer line-source models agree well with the observed spatial distribution of aftershocks and models determined from waveform inversion. However, because FinDer models are constructed to characterize seismic ground motions (as needed for EEW) instead of source parameters, the rupture length can be overestimated for events radiating high levels of high-frequency motions. If the strong-motion data used had been available in real time, 50%–80% of sites experiencing intensity modified Mercalli intensity IV–VII (light to very strong) and 30% experiencing VIII–IX (severe to violent) could have been issued a warning with 10 and 5 s, respectively, before the arrival of the S wave. We also show that loss estimates based on the FinDer line source are more accurate compared to point-source models. For the Wenchuan earthquake, for example, they predict a four to six times larger number of fatalities and injured, which is consistent with official reports. These losses could be provided 1/2∼3 hr faster than if they were based on more complex inversion rupture models.

The United States Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) alert system provides rapid (10–20 min) but general loss estimates of ranges of fatalities and economic impact for significant global earthquakes. FEMA’s Hazus software, in contrast, provides time-consuming (2–5 h) but more detailed loss information quantified in terms of structural, social, and economic consequences estimated at a much higher spatial resolution for large domestic earthquakes. We developed a rapid hybrid post-earthquake product that takes advantage of the best of both loss models. First, though, we conducted a systematic comparison of loss estimates from PAGER with Hazus for all significant, relatively recent, domestic earthquakes for which adequate loss data exist—augmented by a dozen ShakeMap scenarios. The systematic comparison of Hazus and PAGER losses provided the basis for selecting the specific loss metrics to present from each system. The signature product will serve as a supplement to the widely deployed PAGER alert product for significant domestic earthquakes.

In the minutes to hours after a major earthquake, such as the recent 2018 Mw 7.1 Anchorage event, the U.S. Geological Survey (USGS) produces a suite of interconnected earthquake products that provides diverse information ranging from basic earthquake source parameters to loss estimates. The 2018 Anchorage earthquake is the first major domestic earthquake to occur since several new USGS products have been developed, thus providing an opportunity to discuss the newly expanded USGS earthquake product suite, its timeliness, performance, and reception. Overall, the products were relatively timely, accurate, well received, and widely used, including by the media, who used information and visualizations from many products to frame their early reporting. One downside of the codependence of multiple products is that reasonable updates to upstream products (e.g., magnitude and source characterization) can result in significant changes to downstream products; this was the case for the Anchorage earthquake. However, the coverage of strong‐motion stations and felt reports was so dense that the ShakeMap and downstream products were relatively insensitive to changes in magnitude or fault‐plane orientation once the ground‐motion data were available. Shaking and loss indicators initially fluctuated in the first hour or two after the earthquake, but they stabilized quickly. To understand how the products are being used and how effectively they are being communicated, we analyze the media coverage of USGS earthquake products. Most references to USGS products occurred within the first 48 hr after the event. The lack of coverage after 48 hr could indicate that longer‐term products addressing what actions the USGS is taking or what early reconnaissance has revealed might be useful for those people wanting additional information about the earthquake.

Human behavioral response to earthquake ground motion has long been a subject of multidisciplinary interest and research. In most versions of seismic intensity scales, human perceptions and behavior are one component of the assignment of intensity. Public health research has shown that actions taken during earthquakes have a significant impact on the incidence of injury or the maintenance of safety. Based on this research, emergency managers and organizations promoting emergency preparedness have advocated strategies such as drop, cover, and hold on (DCHO) and promoted this safety measure through public education and annual drills. The “Did You Feel It?” (DYFI) mapping system (see Data and Resources) based on an online questionnaire developed and maintained by the U.S. Geological Survey has provided opportunities for those who have experienced an earthquake to report this experience worldwide since 2004. The DYFI questionnaire, although designed to assign intensity, also contains questions regarding the behavior in which one has engaged during the earthquake. The questionnaire includes other important information that may elucidate behavioral response to earthquakes, including assigned intensity, emotional reaction, and whether damage occurred at the location where the earthquake was experienced. The very large number of people who completed DYFI questionnaires following the July 2019 Ridgecrest, California, earthquakes provides a robust dataset for analysis and suggests that as intensity and levels of fear increase, behavior becomes more active in terms of physical movement to locations of presumed safety. Among active responses including DCHO, going to a doorway, and running outside, DCHO was the least likely to be implemented. The study provides possible explanations for low participation in DCHO despite active campaigns to promote this strategy.

Earthquake‐triggered landslides are a significant hazard in seismically active regions, but our ability to assess the hazard they pose in near real‐time is limited. In this study, we present a new globally applicable model for seismically induced landslides based on the most comprehensive global dataset available; we use 23 landslide inventories that span a range of earthquake magnitudes and climatic and tectonic settings. We use logistic regression to relate the presence and distribution of earthquake‐triggered landslides with spatially distributed estimates of ground shaking, topographic slope, lithology, land cover type, and a topographic index designed to estimate variability in soil wetness to provide an empirical model of landslide distribution. We tested over 100 combinations of independent predictor variables to find the best‐fitting model, using a diverse set of statistical tests. Blind validation tests show the model accurately estimates the distribution of available landslide inventories. The results indicate that the model is reliable and stable, with high “balanced accuracy” (correctly vs. incorrectly classified pixels) for the majority of test events. A cross validation analysis shows high balanced accuracy for a majority of events as well. By combining near‐real time estimates of ground shaking with globally available landslide susceptibility data, this model provides a tool to estimate the distribution of coseismic landslide hazard within minutes of the occurrence of any earthquake worldwide for which a U.S. Geological Survey ShakeMap is available.

The impressive number of stream gauges in Chile, combined with a suite of past and recent large earthquakes, makes Chile a unique natural laboratory to study several streams that recorded responses to multiple seismic events. We document changes in discharge in eight streams in Chile following two or more large earthquakes. In all cases, discharge increases. Changes in discharge occur for peak ground velocities greater than about 7-11cm/s. Above that threshold, the magnitude of both the increase in discharge and the total excess water do not increase with increasing peak ground velocities. While these observations are consistent with previous work in California, they conflict with lab experiments that show that the magnitude of permeability changes increases with increasing amplitude of ground motion. Instead, our study suggests that streamflow responses are binary. Plain Language Summary Earthquakes deform and shake the surface and the ground below. These changes may affect groundwater flows by increasing the permeability along newly formed cracks and/or clearing clogged pores. As a result, groundwater flow may substantially increase after earthquakes and remain elevated for several months. Here we document streamflow anomalies following multiple high magnitude earthquakes in multiple streams in one of the most earthquake prone regions worldwide, Chile. We take advantage of the dense monitoring network in Chile that recorded streamflow since the 1940s. We show that once a critical ground motion is exceeded, streamflow responses to earthquakes can be expected.

We make and analyze structural damage observations from within the Kathmandu valley following the 2015 M7.8 Gorkha, Nepal earthquake to derive macroseismic intensities at several locations including some located near ground motion recording sites. The macroseismic intensity estimates supplement the limited strong ground motion data in order to characterize the damage statistics. This augmentation allows for direct comparisons between ground motion amplitudes and structural damage characteristics and ultimately produces a more constrained ground shaking hazard map for the Gorkha earthquake. For systematic assessments, we focused on damage to three specific building categories: (a) low/mid-rise reinforced concrete frames with infill brick walls, (b) unreinforced brick masonry bearing walls with reinforced concrete slabs, and (c) unreinforced brick masonry bearing walls with partial timber framing. Evaluating dozens of photos of each construction type, assigning each building in the study sample to a European Macroseismic Scale (EMS)-98 Vulnerability Class based upon its structural characteristics, and then individually assigning an EMS-98 Damage Grade to each building allows a statistically derived estimate of macroseismic intensity for each of nine study areas in and around the Kathmandu valley. This analysis concludes that EMS-98 macroseismic intensities for the study areas from the Gorkha mainshock typically were in the VII–IX range. The intensity assignment process described is more rigorous than the informal approach of assigning intensities based upon anecdotal media or first-person accounts of felt-reports, shaking, and their interpretation of damage. Detailed EMS-98 macroseismic assessments in urban areas are critical for quantifying relations between shaking and damage as well as for calibrating loss estimates. We show that the macroseismic assignments made herein result in fatality estimates consistent with the overall and district-wide reported values.

Methods that account for site response range in complexity from simple linear categorical adjustment factors to sophisticated nonlinear constitutive models. Seismic‐hazard analysis usually relies on ground‐motion prediction equations (GMPEs); within this framework site response is modeled statistically with simplified site parameters that include the time‐averaged shear‐wave velocity to 30 m ( V S 30 ) and basin depth parameters. Because V S 30 is not known in most locations, it must be interpolated or inferred through secondary information such as geology or topography. In this article, we analyze a subset of stations for which V S 30 has been measured to address effects of V S 30 proxies on the uncertainty in the ground motions as modeled by GMPEs. The stations we analyze also include multiple recordings, which allow us to compute the repeatable site effects (or empirical amplification factors [EAFs]) from the ground motions. Although all methods exhibit similar bias, the proxy methods only reduce the ground‐motion standard deviations at long periods when compared to GMPEs without a site term, whereas measured V S 30 values reduce the standard deviations at all periods. The standard deviation of the ground motions are much lower when the EAFs are used, indicating that future refinements of the site term in GMPEs have the potential to substantially reduce the overall uncertainty in the prediction of ground motions by GMPEs.

Earthquake response and related information products are important for placing recent seismic events into context and particularly for understanding the impact earthquakes can have on the regional community and its infrastructure. These tools are even more useful if they are available quickly, ahead of detailed information from the areas affected by such earthquakes. Here we provide an overview of the response activities and related information products generated and provided by the U.S. Geological Survey National Earthquake Information Center in association with the 2015 M 7.8 Gorkha, Nepal, earthquake. This group monitors global earthquakes 24 hrs/day and 7 days/week to provide rapid information on the location and size of recent events and to characterize the source properties, tectonic setting, and potential fatalities and economic losses associated with significant earthquakes. We present the timeline over which these products became available, discuss what they tell us about the seismotectonics of the Gorkha earthquake and its aftershocks, and examine how their information is used today, and might be used in the future, to help mitigate the impact of such natural disasters.

We describe an approach to model liquefaction extent that focuses on identifying broadly available geospatial variables (e.g., derived from digital elevation models) and earthquake-specific parameters (e.g., peak ground acceleration, PGA). A key step is database development: We focus on the 1995 Kobe and 2010–2011 Christchurch earthquakes because the presence/absence of liquefaction has been mapped so that the database is unbiased with respect to the areal extent of liquefaction. We derive two liquefaction models with explanatory variables that include PGA, shear-wave velocity, compound topographic index, and a newly defined normalized distance parameter (distance to coast divided by the sum of distance to coast and distance to the basin inland edge). To check the portability/reliability of these models, we apply them to the 2010 Haiti earthquake. We conclude that these models provide first-order approximations of the extent of liquefaction, appropriate for use in rapid response, loss estimation, and simulations.

We analyzed the regional dependence of ground motion to intensity conversion equations and derived a new global relationship to improve ground motion and intensity estimates for earthquake hazard applications, including those related to the ShakeMap system. For this purpose, we merged several databases collected by other authors in different geographical regions to highlight any systematic regional effects in the relationship between macroseismic intensities and both peak ground velocity and peak ground acceleration. Our database contains macroseismic intensities derived from expert assignments or from the “Did You Feel It?” database, paired with peak ground motions (PGM) from seismic stations. We constrain our intensity–ground‐motion pairs to those with a maximum 2 km separation. For each region, we derived invertible relationships between intensities and ground motion using an orthogonal regression. We also derived a global relationship to quantify the regional differences. We investigated the dependence of intensity on predictor variables such as PGM, magnitude, and hypocentral distance. Our analyses indicate that PGM is the most robust predictor variable of intensity. Within one standard deviation, our regional and global results are in agreement with the relations of Worden et al. (2012) for California, Faenza and Michelini (2010) for Italy, Tselentis and Danciu (2008) for Greece, and Atkinson and Kaka (2007) for central–eastern United States. The earthquakes in the study ranged in magnitude from 2.5 to 7.3, and the distances ranged from less than a kilometer to about 200 km from the epicenter. Online Material: Table summarizing published relationships and figures showing the relationship between peak ground acceleration and intensity.

The M w 6.0 South Napa earthquake, which occurred at 10:20 UTC 24 August 2014 was the largest earthquake to strike the greater San Francisco Bay area since the M w 6.9 1989 Loma Prieta earthquake. The rupture from this right‐lateral earthquake propagated mostly unilaterally to the north and up‐dip, directing the strongest shaking toward the city of Napa, where peak ground accelerations (PGAs) between 45% g and 61% g were recorded and modified Mercalli intensities (MMIs) of VII–VIII were reported. Tectonic surface rupture with dextral slip of up to 46 cm was observed on a 12.5 km long segment, some of which was along a previously mapped strand of the West Napa fault system, although the rupture extended to the north of the mapped Quaternary strand. Modeling of seismic and geodetic data suggests an average coseismic slip of 50 cm, with a maximum slip of about 1 m at depths of 10–11 km. We observed up to 35 cm of afterslip along the surface trace in the week following the mainshock, primarily along the southern half of the surface rupture that experienced relatively little coseismic offset. Relocation of the sparse aftershock sequence suggests en echelon southwest‐ and northeast‐dipping fault planes, reflective of the complex fault geometry in this region. The Napa basin and historic and late Holocene alluvial flood deposits in downtown Napa amplified the ground motions there. Few ground failures were mapped, reflecting the dry season (as well as a persistent drought that had lowered the groundwater table) and the short duration of strong shaking in the epicentral area. The South Napa fault rupture lies within an 80 km wide set of major north‐northwest‐trending faults of the San Andreas fault system, forming the boundary between the Pacific and North American tectonic …

Equations that predict intensity as a function of magnitude and distance are useful tools for hazard and risk assessment, and in interpretation of both contemporary and historical earthquake information. The intensity prediction equations of Atkinson and Wald (2007; hereafter AW07) have been remarkably successful in describing the level and intensity of motions reported under the “Did You Feel It?” (DYFI) program over the last several years. Examination of the performance of AW07 for North American earthquakes, evaluated using an extensive compiled database of DYFI observations from 2000 to 2013, suggests that there is little statistical basis for revising these equations. However, a problem with the AW07 equations is that they predict unrealistically large median intensities for large events ( M >6) at close distances. In this study, we revise AW07 to improve the intensity scaling at large magnitudes and close distances, by reconciling intensity equations with ground‐motion prediction equations.

For many earthquake engineering applications, site response is estimated through empirical correlations with the time‐averaged shear‐wave velocity to 30 m depth ( V S 30 ). These applications therefore depend on the availability of either site‐specific V S 30 measurements or V S 30 maps at local, regional, and global scales. Because V S 30 measurements are sparse, a proxy frequently is needed to estimate V S 30 at unsampled locations. We present a new V S 30 map for California, which accounts for observational constraints from multiple sources and spatial scales, such as geology, topography, and site‐specific V S 30 measurements. We apply the geostatistical approach of regression kriging (RK) to combine these constraints for predicting V S 30 . For the V S 30 trend, we start with geology‐based V S 30 values and identify two distinct trends between topographic gradient and the residuals from the geology V S 30 model. One trend applies to deep and fine Quaternary alluvium, whereas the second trend is slightly stronger and applies to Pleistocene sedimentary units. The RK framework ensures that the resulting map of California is locally refined to reflect the rapidly expanding database of V S 30 measurements throughout California. We compare the accuracy of the new mapping method to a previously developed map of V S 30 for California. We also illustrate the sensitivity of ground motions to the new V S 30 map by comparing real and scenario ShakeMaps with V S 30 values from our new map to those for existing V S 30 maps. Online Material: California statewide V S 30 and ShakeMaps for Loma Prieta.

We extended the U.S. Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER) empirical fatality estimation methodology proposed by Jaiswal et al. (2009) to rapidly estimate economic losses after significant earthquakes worldwide. The requisite model inputs are shaking intensity estimates made by the ShakeMap system, the spatial distribution of population available from the LandScan database, modern and historic country or sub-country population and Gross Domestic Product (GDP) data, and economic loss data from Munich Re's historical earthquakes catalog. We developed a strategy to approximately scale GDP-based economic exposure for historical and recent earthquakes in order to estimate economic losses. The process consists of using a country-specific multiplicative factor to accommodate the disparity between economic exposure and the annual per capita GDP, and it has proven successful in hindcast-ing past losses. Although loss, population, shaking estimates, and economic data used in the calibration process are uncertain, approximate ranges of losses can be estimated for the primary purpose of gauging the overall scope of the disaster and coordinating response. The proposed methodology is both indirect and approximate and is thus best suited as a rapid loss estimation model for applications like the PAGER system.

Rapid evaluation of strong ground‐shaking maps after moderate‐to‐large earthquakes is crucial to recognizing those areas where the largest damage and losses are expected. These maps play a fundamental role for emergency management. This is particularly important for areas having high seismic risk potential and covered by dense seismic networks. In near‐real‐time applications, ground‐shaking maps are produced by integrating recorded data and estimates obtained by using ground‐motion predictive equations, which assume point‐source models. However, particularly for large earthquakes, improvements in the predictions of the peak ground motion can be obtained when fault extension and orientation are available. In fact, detailed source information allows one to use a more robust source‐to‐site distance metric compared with hypocentral distance. In this paper, a technique for estimating both fault extent (in terms of its surface projection) and dominant rupture direction is presented. This technique can be used in near‐real‐time ground‐motion map calculation codes with the aim of improving ground‐motion estimates with respect to a point‐source model. The model parameters are estimated by maximizing a probability density function based on the residuals between observed and predicted peak‐ground‐motion quantities, the latter obtained by using predictive equations. The model space to be investigated is defined through a Bayesian approach, and it is explored by a grid‐searching technique. The effectiveness of the proposed technique is demonstrated by offline numerical tests using data from three earthquakes occurring in different seismotectonic environments. The selected earthquakes are the 17 August 1999 M w 7.5 Kocaeli (Turkey) earthquake, the 6 April 2009 M w 6.3 L’Aquila (Italy) earthquake, and the 17 January 1994 M w 6.7 Northridge (California) earthquake. The obtained results show that the proposed technique allows for fast and first order estimates of the fault extent and dominant rupture direction, which could be used to improve ground‐shaking map calculations.

We develop globally applicable macroseismic intensity prediction equations (IPEs) for earthquakes of moment magnitude M W 5.0–7.9 and intensities of degree II and greater for distances less than 300 km for active crustal regions. The IPEs are developed for two distance metrics: closest distance to rupture (R rup) and hypocentral distance (R hyp). The key objective for developing the model based on hypocentral distance—in addition to more rigorous and standard measure R rup—is to provide an IPE which can be used in near real-time earthquake response systems for earthquakes anywhere in the world, where information regarding the rupture dimensions of a fault may not be known in the immediate aftermath of the event. We observe that our models, particularly the model for the R rup distance metric, generally have low median residuals with magnitude and distance. In particular, we address whether the direct use of IPEs leads to a reduction in overall uncertainties when compared with methods which use a combination of ground-motion prediction equations and ground motion to intensity conversion equations. Finally, using topographic gradient as a proxy and median model predictions, we derive intensity-based site amplification factors. These factors lead to a small reduction of residuals at shallow gradients at strong shaking levels. However, the overall effect on total median residuals is relatively small. This is in part due to the observation that the median site condition for intensity observations used to develop these IPEs is approximately near the National Earthquake Hazard Reduction Program CD site-class boundary.

We present a new automatic earthquake discrimination procedure to determine in near-real time the tectonic regime and seismotectonic domain of an earth- quake, its most likely source type, and the corresponding ground-motion prediction equation (GMPE) class to be used in the U.S. Geological Survey (USGS) Global ShakeMap system. This method makes use of the Flinn-Engdahl regionalization scheme, seismotectonic information (plate boundaries, global geology, seismicity cat- alogs, and regional and local studies), and the source parameters available from the USGS National Earthquake Information Center in the minutes following an earthquake to give the best estimation of the setting and mechanism of the event. Depending on the tectonic setting, additional criteria based on hypocentral depth, style of faulting, and regional seismicity may be applied. For subduction zones, these criteria include the use of focal mechanism information and detailed interface models to discriminate among outer-rise, upper-plate, interface, and intraslab seismicity. The scheme is validated against a large database of recent historical earthquakes. Though developed to assess GMPE selection in Global ShakeMap operations, we anticipate a variety of uses for this strategy, from real-time processing systems to any analysis involving tectonic classification of sources from seismic catalogs.

We use a database of approximately 200,000 modified Mercalli intensity (MMI) observations of California earthquakes collected from USGS “Did You Feel It?” (DYFI) reports, along with a comparable number of peak ground‐motion amplitudes from California seismic networks, to develop probabilistic relationships between MMI and peak ground velocity (PGV), peak ground acceleration (PGA), and 0.3‐s, 1‐s, and 3‐s 5% damped pseudospectral acceleration (PSA). After associating each ground‐motion observation with an MMI computed from all the DYFI responses within 2 km of the observation, we derived a joint probability distribution between MMI and ground motion. We then derived reversible relationships between MMI and each ground‐motion parameter by using a total least squares regression to fit a bilinear function to the median of the stacked probability distributions. Among the relationships, the fit to peak ground velocity has the smallest errors, though linear combinations of PGA and PGV give nominally better results. We also find that magnitude and distance terms reduce the overall residuals and are justifiable on an information theoretic basis. For intensities MMI≥5, our results are in close agreement with the relations of Wald, Quitoriano, Heaton, and Kanamori (1999); for lower intensities, our results fall midway between Wald, Quitoriano, Heaton, and Kanamori (1999) and those of Atkinson and Kaka (2007). The earthquakes in the study ranged in magnitude from 3.0 to 7.3, and the distances ranged from less than a kilometer to about 400 km from the source. Online Material: Figures showing the relationship between 0.3 s, 1.0 s, and 3.0 s pseudospectral acceleration and MMI.

Building collapse is the dominant cause of casualties during earthquakes. In order to better predict human fatalities, the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) program requires collapse fragility functions for global building types. The collapse fragility is expressed as the probability of collapse at discrete levels of the input hazard defined in terms of macroseismic intensity. This article provides a simple procedure for quantifying collapse fragility using vulnerability criteria based on the European Macroseismic Scale (1998) for selected European building types. In addition, the collapse fragility functions are developed for global building types by fitting the beta distribution to the multiple experts’ estimates for the same building type (obtained from EERI’s World Housing Encyclopedia (WHE)PAGER survey). Finally, using the collapse probability distributions at each shaking intensity level as a prior and field-based collapse-rate observations as likelihood, it is possible to update the collapse fragility functions for global building types using the Bayesian procedure. [DOI: 10.1193/1.3606398]

Online material : Timeline movie The M 9.0 11 March 2011 Tohoku, Japan, earthquake and associated tsunami near the east coast of the island of Honshu caused tens of thousands of deaths and potentially over one trillion dollars in damage, resulting in one of the worst natural disasters ever recorded. The U.S. Geological Survey National Earthquake Information Center (USGS NEIC), through its responsibility to respond to all significant global earthquakes as part of the National Earthquake Hazards Reduction Program, quickly produced and distributed a suite of earthquake information products to inform emergency responders, the public, the media, and the academic community of the earthquake's potential impact and to provide scientific background for the interpretation of the event's tectonic context and potential for future hazard. Here we present a timeline of the NEIC response to this devastating earthquake in the context of rapidly evolving information emanating from the global earthquake-response community. The timeline includes both internal and publicly distributed products, the relative timing of which highlights the inherent tradeoffs between the requirement to provide timely alerts and the necessity for accurate, authoritative information. The timeline also documents the iterative and evolutionary nature of the standard products produced by the NEIC and includes a behind-the-scenes look at the decisions, data, and analysis tools that drive our rapid product distribution. The NEIC operates a 24/7 service dedicated to the rapid determination of the location and size of all significant earthquakes worldwide and to the immediate dissemination of this information to concerned national and international agencies, scientists, critical facilities, and the general public. Within its 24/7 operations, the NEIC is constantly staffed by at least two geophysicists who are responsible for reviewing and reporting all magnitude 5 or larger events within 20 minutes of origin time. These analysts also field incoming calls from the …

Wedescribe aweighted-average approach for incorporating varioustypes of data (observed peak ground motions and intensities and estimates from ground- motion prediction equations) into theShakeMap ground motion and intensity mapping framework.ThisapproachrepresentsafundamentalrevisionofourexistingShakeMap methodology. In addition, the increased availability of near-real-time macroseismic intensitydata,thedevelopmentofnewrelationshipsbetweenintensityandpeakground motions, and new relationships to directly predict intensity from earthquake source information have facilitated the inclusion of intensity measurements directly into ShakeMap computations. Our approach allows for the combination of (1) direct observations (ground-motion measurements or reported intensities), (2) observations converted from intensity to ground motion (or vice versa), and (3) estimated ground motionsandintensities frompredictionequationsornumerical models.Critically,each oftheaforementioneddatatypesmustincludeanestimateofitsuncertainties,including those caused by scaling the influence of observations to surrounding grid points and those associated with estimates given an unknown fault geometry. The ShakeMap ground-motion and intensity estimates are an uncertainty-weighted combination of these various data and estimates. A natural by-product of this interpolation process is an estimate of total uncertainty at each point on the map, which can be vital for comprehensive inventory loss calculations. We perform a number of tests to validate this new methodology and find that it produces a substantial improvement in the accuracy of ground-motion predictions over empirical prediction equations alone.

We analyzed mortality rates of earthquakes worldwide and developed a country/region-specific empirical model for earthquake fatality estimation within the U.S. Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER) system. The earthquake fatality rate is defined as total killed divided by total population exposed at specific shaking intensity level. The total fatalities for a given earthquake are estimated by multiplying the number of people exposed at each shaking intensity level by the fatality rates for that level and then summing them at all relevant shaking intensities. The fatality rate is expressed in terms of a two-parameter lognormal cumulative distribution function of shaking intensity. The parameters are obtained for each country or a region by minimizing the residual error in hindcasting the total shaking-related deaths from earthquakes recorded between 1973 and 2007. A new global regionalization scheme is used to combine the fatality data across different countries with similar vulnerability traits.

We develop a global database of building inventories using taxonomy of global building types for use in near-real-time post-earthquake loss estimation and pre-earthquake risk analysis, for the U.S. Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER) program. The database is available for public use, subject to peer review, scrutiny, and open enhancement. On a country-by-country level, it contains estimates of the distribution of building types categorized by material, lateral force resisting system, and occupancy type (residential or nonresidential, urban or rural). The database draws on and harmonizes numerous sources: (1) UN statistics, (2) UN Habitat's demographic and health survey (DHS) database, (3) national housing censuses, (4) the World Housing Encyclopedia and (5) other literature.

We present an Atlas of ShakeMaps and a catalog of human population expo- sures to moderate-to-strong ground shaking (EXPO-CAT) for recent historical earthquakes (1973-2007). The common purpose of the Atlas and exposure catalog is to calibrate earth- quake loss models to be used in the US Geological Survey's Prompt Assessment of Global EarthquakesforResponse(PAGER).ThefullShakeMapAtlascurrentlycomprisesover5,600 earthquakes from January 1973 through December 2007, with almost 500 of these maps con- strained—tovaryingdegrees—byinstrumentalgroundmotions,macroseismicintensitydata, community internet intensity observations, and published earthquake rupture models. The catalog of human exposures is derived using current PAGER methodologies. Exposure to discrete levels of shaking intensity is obtained by correlating Atlas ShakeMaps with a global population database. Combining this population exposure dataset with historical earthquake lossdata,suchasPAGER-CAT,providesausefulresourceforcalibratinglossmethodologies against a systematically-derived set of ShakeMap hazard outputs. We illustrate two example uses for EXPO-CAT; (1) simple objective ranking of country vulnerability to earthquakes, and; (2) the influence of time-of-day on earthquake mortality. In general, we observe that countriesinsimilargeographicregionswithsimilarconstructionpracticestendtoclusterspa- tiallyintermsofrelativevulnerability.Wealsofindlittlequantitativeevidencetosuggestthat time-of-day is a significant factor in earthquake mortality. Moreover, earthquake mortality appears to be more systematically linked to the population exposed to severe ground shaking (Modified Mercalli Intensity VIII+). Finally, equipped with the full Atlas of ShakeMaps, we merge each of these maps and find the maximum estimated peak ground acceleration at any grid point in the world for the past 35years. We subsequently compare this "composite

An alternative method has recently been proposed for evaluating global seismic site conditions, or the average shear velocity to 30 m depth ( V S 30), from the Shuttle Radar Topography Mission (SRTM) 30 arcsec digital elevation models (DEMs). The basic premise of the method is that the topographic slope can be used as a reliable proxy for V S 30 in the absence of geologically and geotechnically based site-condition maps through correlations between V S 30 measurements and topographic gradient. Here we evaluate the use of higher-resolution (3 and 9 arcsec) DEMs to examine whether we are able to resolve V S 30 in more detail than can be achieved using the lower-resolution SRTM data. High-quality DEMs at resolutions greater than 30 arcsec are not uniformly available at the global scale. However, in many regions where such data exist, they may be employed to resolve finer-scale variations in topographic gradient, and consequently, V S 30. We use the U.S. Geological Survey Earth Resources Observation and Science (EROS) Data Center’s National Elevation Dataset (NED) to investigate the use of high-resolution DEMs for estimating V S 30 in several regions across the United States, including the San Francisco Bay area in California, Los Angeles, California, and St. Louis, Missouri. We compare these results with an example from Taipei, Taiwan, that uses 9 arcsec SRTM data, which are globally available. The use of higher-resolution NED data recovers finer-scale variations in topographic gradient, which better correlate to geological and geomorphic features, in particular, at the transition between hills and basins, warranting their use over 30 arcsec SRTM data where available. However, statistical analyses indicate little to no improvement over lower-resolution topography when compared to V S 30 measurements, suggesting that some topographic smoothing may provide more stable V S 30 estimates. Furthermore, we find that elevation variability in canopy-based SRTM measurements at resolutions greater than 30 arcsec are too large to resolve reliable slopes, particularly in low-gradient sedimentary basins.

SUMMARY A key step in many earthquake source inversions requires knowledge of the geometry of the fault surface on which the earthquake occurred. Our knowledge of this surface is often uncertain, however, and as a result fault geometry misinterpretation can map into significant error in the final temporal and spatial slip patterns of these inversions. Relying solely on an initial hypocentre and CMT mechanism can be problematic when establishing rupture characteristics needed for rapid tsunami and ground shaking estimates. Here, we attempt to improve the quality of fast finite-fault inversion results by combining several independent and complementary data sets to more accurately constrain the geometry of the seismic rupture plane of subducting slabs. Unlike previous analyses aimed at defining the general form of the plate interface, we require mechanisms and locations of the seismicity considered in our inversions to be consistent with their occurrence on the plate interface, by limiting events to those with well-constrained depths and with CMT solutions indicative of shallow-dip thrust faulting. We construct probability density functions about each location based on formal assumptions of their depth uncertainty and use these constraints to solve for the ‘most-likely’ fault plane. Examples are shown for the trench in the source region of the Mw 8.6 Southern Sumatra earthquake of March 2005, and for the Northern Chile Trench in the source region of the November 2007 Antofagasta earthquake. We also show examples using only the historic catalogues in regions without recent great earthquakes, such as the Japan and Kamchatka Trenches. In most cases, this method produces a fault plane that is more consistent with all of the data available than is the plane implied by the initial hypocentre and CMT mechanism. Using the aggregated data sets, we have developed an algorithm to rapidly determine more accurate initial fault plane geometries for source inversions of future earthquakes.

The compilation of a comprehensive global earthquake catalog that delivers both accurate source parameters and fatality estimates is a task that is simple in theory but challenging in practice. The necessary information is spread throughout numerous earthquake catalogs, reports, and online databases. Earthquake catalogs are created for different purposes, and consequently they excel in different areas. Some catalogs provide high-quality hypocenters while others contain carefully researched damage reports. Herein we examine published global catalogs and create PAGER-CAT, a composite global catalog of earthquake source parameters and effects. PAGER-CAT incorporates eight global earthquake catalogs and additional auxiliary data to provide comprehensive information not only for hypocentral locations, magnitudes, and human fatalities, but when available, focal mechanisms, the country of origin or the distance to the nearest landmass, local time and day of week, presence of secondary effects ( e.g. , tsunami, landslide, fire, or liquefaction) and deaths caused by these effects, the number of buildings damaged or destroyed, and the number of people injured or left homeless. The first version of the catalog is composed of more than 140 fields in which detailed event information can be recorded and currently includes events from 1900 through December 2007, with emphasis on earthquakes since 1973. The catalog was compiled for calibration and development of earthquake fatality models to be used by the U.S. Geological Survey's (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system. The PAGER system currently provides estimates of the number of people and the names of cities exposed to severe shaking following significant earthquakes (Earle et al. 2008; Wald et al. 2008). In the future, PAGER will produce rapid fatality estimates within approximately 20 minutes of an earthquake's occurrence anywhere on the globe, using loss models calibrated against PAGER-CAT ( e.g. , Jaiswal et al. 2008; Porter et al. …

When a potentially damaging earthquake occurs, utility and other lifeline managers, emergency responders, and other critical users have an urgent need for information about the impact on their particular facilities so they can make appropriate decisions and take quick actions to ensure safety and restore system functionality. ShakeMap, a tool used to portray the extent of potentially damaging shaking following an earthquake, on its own can be useful for emergency response, loss estimation, and public information. However, to take full advantage of the potential of ShakeMap, we introduce ShakeCast. ShakeCast facilitates the complicated assessment of potential damage to a user's widely distributed facilities by comparing the complex shaking distribution with the potentially highly variable damageability of their inventory to provide a simple, hierarchical list and maps of structures or facilities most likely impacted. ShakeCast is a freely available, post-earthquake situational awareness application that automatically retrieves earthquake shaking data from ShakeMap, compares intensity measures against users’ facilities, sends notifications of potential damage to responsible parties, and generates facility damage maps and other Web-based products for both public and private emergency managers and responders.

At the beginning of 2006, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) introduced a new automated Earthquake Notification Service (ENS) to take the place of the National Earthquake Information Center (NEIC) “Bigquake” system and the various other individual EHP e-mail list-servers for separate regions in the United States. These included northern California, southern California, and the central and eastern United States. ENS is a “one-stop shopping” system that allows Internet users to subscribe to flexible and customizable notifications for earthquakes anywhere in the world. The customization capability allows users to define the what (magnitude threshold), the when (day and night thresholds), and the where (specific regions) for their notifications. Customization is achieved by employing a per-user based request profile, allowing the notifications to be tailored for each individual's requirements. Such earthquake-parameter-specific custom delivery was not possible with simple e-mail list-servers. Now that event and user profiles are in a structured query language (SQL) database, additional flexibility is possible. At the time of this writing, ENS had more than 114,000 subscribers, with more than 200,000 separate user profiles. On a typical day, more than 188,000 messages get sent to a variety of widely distributed users for a wide range of earthquake locations and magnitudes. The purpose of this article is to describe how ENS works, highlight the features it offers, and summarize plans for future developments. ### ENS Features The ENS interface has many customizable features. The current user interface and options were developed as an iterative process over a period of one year, as feedback was received from a group of beta users. Messages were modified from long-established versions sent by the NEIC and the California Integrated Seismic Network (CISN). Specific details and user configuration options for each feature are provided on the ENS signup Web page (http://earthquake.usgs.gov/ens/), but in brief …

We describe a technique to derive first-order site condition maps directly from topographic data. For calibration, we use global 30 arc sec topographic data and V S 30 measurements (here V S 30 , refers to the average shear-velocity down to 30 m) aggregated from several studies in the U.S., as well as in Taiwan, Italy, and Australia. V S 30 values are correlated against topographic slope to develop two sets of parameters for deriving V S 30 : one for active tectonic regions where topographic relief is high, and one for stable shields where topography is more subdued. By taking the gradient of the topography and choosing ranges of slope that maximize the correlation with shallow shear-velocity observations, we can recover, to first order, many of the spatially varying features of sitecondition maps developed for California. Our site-condition map for the low-relief Mississippi Embayment also predicts the bulk of the V S 30 observations in that region despite rather low slope ranges. We find that maps derived from the slope of the topography is often well correlated with other independently-derived, regional-scale site-condition maps, but the latter maps vary in quality and continuity, and subsequently, also in their ability to match observed V S 30 measurements contained therein. Alternatively, the slope-based method provides a simple approach to uniform site condition mapping.

The U.S. Geological Survey is tapping a vast new source of engineering seismology data through its “Did You Feel It?” (DYFI) program, which collects online citizen responses to earthquakes. To date, more than 750,000 responses have been compiled in the United States alone. The DYFI data make up in quantity what they may lack in scientific quality and offer the potential to resolve longstanding issues in earthquake ground-motion science. Such issues have been difficult to address due to the paucity of instrumental ground-motion data in regions of low seismicity. In particular, DYFI data provide strong evidence that earthquake stress drops, which control the strength of high-frequency ground shaking, are higher in the central and eastern United States (CEUS) than in California. Higher earthquake stress drops, coupled with lower attenuation of shaking with distance, result in stronger overall shaking over a wider area and thus more potential damage for CEUS earthquakes in comparison to those of equal magnitude in California—a fact also definitively captured with these new DYFI data and maps.

Slip histories for the 2002 M7.9 Denali fault, Alaska, earthquake are derived rapidly from global teleseismic waveform data. In phases, three models improve matching waveform data and recovery of rupture details. In the first model (Phase I), analogous to an automated solution, a simple fault plane is fixed based on the preliminary Harvard Centroid Moment Tensor mechanism and the epicenter provided by the Preliminary Determination of Epicenters. This model is then updated (Phase II) by implementing a more realistic fault geometry inferred from Digital Elevation Model topography and further (Phase III) by using the calibrated P-wave and SH-wave arrival times derived from modeling of the nearby 2002 M6.7 Nenana Mountain earthquake. These models are used to predict the peak ground velocity and the shaking intensity field in the fault vicinity. The procedure to estimate local strong motion could be automated and used for global real-time earthquake shaking and damage assessment. [DOI: 10.1193/1.1778388]

During the M w 7.1 Hector Mine earthquake, peak ground velocities recorded at sites in the central San Bernardino basin region were up to 2 times larger and had significantly longer durations of strong shaking than sites just outside the basin. To better understand the effects of 3D structure on the long-period ground-motion response in this region, we have performed finite-difference simulations for this earthquake. The simulations are numerically accurate for periods of 2 sec and longer and incorporate the detailed spatial and temporal heterogeneity of source rupture, as well as complex 3D basin structure. Here, we analyze three models of the San Bernardino basin: model A (with structural constraints from gravity and seismic reflection data), model F (water well and seismic refraction data), and the Southern California Earthquake Center version 3 model (hydrologic and seismic refraction data). Models A and F are characterized by a gradual increase in sediment thickness toward the south with an abrupt step-up in the basement surface across the San Jacinto fault. The basin structure in the SCEC version 3 model has a nearly uniform sediment thickness of 1 km with little basement topography along the San Jacinto fault. In models A and F, we impose a layered velocity structure within the sediments based on the seismic refraction data and an assumed depth-dependent V p / V s ratio. Sediment velocities within the SCEC version 3 model are given by a smoothly varying rule-based function that is calibrated to the seismic refraction measurements. Due to computational limitations, the minimum shear-wave velocity is fixed at 600 m/sec in all of the models. Ground-motion simulations for both models A and F provide a reasonably good match to the amplitude and waveform characteristics of the recorded motions. In these models, surface waves are generated as energy enters the basin through the gradually sloping northern margin. Due to the basement step along the San Jacinto fault, the surface wave energy is confined to the region north of this structure, consistent with the observations. The SCEC version 3 model, lacking the basin geometry complexity present in the other two models, fails to provide a satisfactory match to the characteristics of the observed motions. Our study demonstrates the importance of using detailed and accurate basin geometry for predicting ground motions and also highlights the utility of integrating geological, geophysical, and seismological observations in the development and validation of 3D velocity models.

The San Andreas fault is the longest fault in California and one of the longest strike-slip faults in the world, yet little is known about the aftershocks following the most recent great event on the San Andreas, the M_W 7.8 San Francisco earthquake on 18 April 1906. We conducted a study to locate and to estimate magnitudes for the largest aftershocks and triggered events of this earthquake. We examined existing catalogs and historical documents for the period April 1906 to December 1907, compiling data on the first 20 months of the aftershock sequence. We grouped felt reports temporally and assigned modified Mercalli intensities for the larger events based on the descriptions judged to be the most reliable. For onshore and near-shore events, a grid-search algorithm (derived from empirical analysis of modern earthquakes) was used to find the epicentral location and magnitude most consistent with the assigned intensities. For one event identified as far offshore, the event's intensity distribution was compared with those of modern events, in order to constrain the event's location and magnitude. The largest aftershock within the study period, an M ∼6.7 event, occurred ∼100 km west of Eureka on 23 April 1906. Although not within our study period, another M ∼6.7 aftershock occurred near Cape Mendocino on 28 October 1909. Other significant aftershocks included an M ∼5.6 event near San Juan Bautista on 17 May 1906 and an M ∼6.3 event near Shelter Cove on 11 August 1907. An M ∼4.9 aftershock occurred on the creeping segment of the San Andreas fault (southeast of the mainshock rupture) on 6 July 1906. The 1906 San Francisco earthquake also triggered events in southern California (including separate events in or near the Imperial Valley, the Pomona Valley, and Santa Monica Bay), in western Nevada, in southern central Oregon, and in western Arizona, all within 2 days of the mainshock. Of these triggered events, the largest were an M ∼6.1 earthquake near Brawley and an M ∼5.0 event under or near Santa Monica Bay, 11.3 and 31.3 hr after the San Francisco mainshock, respectively. The western Arizona event is inferred to have been triggered dynamically. In general, the largest aftershocks occurred at the ends of the 1906 rupture or away from the rupture entirely; very few significant aftershocks occurred along the mainshock rupture itself. The total number of large aftershocks was less than predicted by a generic model based on typical California mainshock–aftershock statistics, and the 1906 sequence appears to have decayed more slowly than average California sequences. Similarities can be drawn between the 1906 aftershock sequence and that of the 1857 (M_W 7.9) San Andreas fault earthquake.

We describe a new probabilistic method that uses observations of modified Mercalli intensity (MMI) from past earthquakes to make quantitative estimates of ground shaking parameters (i.e., peak ground acceleration, peak ground velocity, 5% damped spectral acceleration values, etc.). The method uses a Bayesian approach to make quantitative estimates of the probabilities of different levels of ground motions from intensity data given an earthquake of known location and magnitude. The method utilizes probability distributions from an intensity/ground motion data set along with a ground motion attenuation relation to estimate the ground motion from intensity. The ground motions with the highest probabilities are the ones most likely experienced at the site of the MMI observation. We test the method using MMI/ground motion data from California and published ground motion attenuation relations to estimate the ground motions for several earthquakes: 1999 Hector Mine, California (M7.1); 1988 Saguenay, Quebec (M5.9); and 1982 Gaza, New Hampshire (M4.4). In an example where the method is applied to a historic earthquake, we estimate that the peak ground accelerations associated with the 1727 (M;5.2) earthquake at Newbury, Massachusetts, ranged from 0.23 g at Newbury to 0.06 g at Boston. [DOI: 10.1193/1.1596549]