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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.

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.

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.

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.

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.

The U.S. Geological Survey National Earthquake Information Center leads real-time efforts to provide rapid and accurate assessments of the impacts of global earthquakes, including estimates of ground shaking, ground failure, and the resulting human impacts. These efforts primarily rely on analysis of the seismic wavefield to characterize the source of the earthquake, which in turn informs a suite of disaster response products such as ShakeMap and PAGER. In recent years, the proliferation of rapidly acquired and openly available in-situ and remotely sensed geodetic observations has opened new avenues for responding to earthquakes around the world in the days following significant events. Geodetic observations, particularly from interferometric synthetic aperture radar (InSAR) and satellite optical imagery, provide a means to robustly constrain the dimensions and spatial complexity of earthquakes beyond what is typically possible with seismic observations alone. Here, we document recent cases where geodetic observations contributed important information to earthquake response efforts—from informing and validating seismically-derived source models to independently constraining earthquake impact products—and the conditions under which geodetic observations improve earthquake response products. We use examples from the 2013 Mw7.7 Baluchistan, Pakistan, 2014 Mw6.0 Napa, California, 2015 Mw7.8 Gorkha, Nepal, and 2018 Mw7.5 Palu, Indonesia earthquakes to highlight the varying ways geodetic observations have contributed to earthquake response efforts at the NEIC. We additionally provide a synopsis of the workflows implemented for geodetic earthquake response. As remote sensing geodetic observations become increasingly available and the frequency of satellite acquisitions continues to increase, operational earthquake geodetic imaging stands to make critical contributions to natural disaster response efforts around the world.

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.

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.

Substantial effort has been invested to understand where seismically induced landslides may occur in the future, as they are a costly and frequently fatal threat in mountainous regions. The goal of this work is to develop a statistical model for estimating the spatial distribution of landslides in near real-time around the globe for use in conjunction with the U.S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system. This model uses standardized outputs of ground shaking from the USGS ShakeMap Atlas 2.0 to develop an empirical landslide probability model, combining shaking estimates with broadly available landslide susceptibility proxies, i.e., topographic slope, surface geology, and climate parameters. We focus on four earthquakes for which digitally mapped landslide inventories and well-constrained ShakeMaps are available. The resulting database is used to build a predictive model of the probability of landslide occurrence. The landslide database includes the Guatemala (1976), Northridge (1994), Chi-Chi (1999), and Wenchuan (2008) earthquakes. Performance of the regression model is assessed using statistical goodness-of-fit metrics and a qualitative review to determine which combination of the proxies provides both the optimum prediction of landslide-affected areas and minimizes the false alarms in non-landslide zones. Combined with near real-time ShakeMaps, these models can be used to make generalized predictions of whether or not landslides are likely to occur (and if so, where) for earthquakes around the globe, and eventually to inform loss estimates within the framework of the PAGER system.

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 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

This study presents a quantitative and geospatial description of global losses due to earthquake-induced secondary effects, including landslide, liquefaction, tsunami, and fire for events during the past 40 years. These processes are of great importance to the US Geological Survey’s (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system, which is currently being developed to deliver rapid earthquake impact and loss assessments following large/significant global earthquakes. An important question is how dominant are losses due to secondary effects (and under what conditions, and in which regions)? Thus, which of these effects should receive higher priority research efforts in order to enhance PAGER’s overall assessment of earthquakes losses and alerting for the likelihood of secondary impacts? We find that while 21.5% of fatal earthquakes have deaths due to secondary (non-shaking) causes, only rarely are secondary effects the main cause of fatalities. The recent 2004 Great Sumatra–Andaman Islands earthquake is a notable exception, with extraordinary losses due to tsunami. The potential for secondary hazards varies greatly, and systematically, due to regional geologic and geomorphic conditions. Based on our findings, we have built country-specific disclaimers for PAGER that address potential for each hazard (Earle et al., Proceedings of the 14th World Conference of the Earthquake Engineering, Beijing, China, 2008). We will now focus on ways to model casualties from secondary effects based on their relative importance as well as their general predictability.

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.

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]

We compare two methods of seismic-intensity estimation from ground-motion records for the two recent strong earthquakes: the 1999 ( M 7.1) Hector Mine, California, and the 1999 ( M 7.6) Chi-Chi, Taiwan. The first technique utilizes the peak ground acceleration (PGA) and velocity (PGV), and it is used for rapid generation of the instrumental intensity map in California. The other method is based on the revised relationships between intensity and Fourier amplitude spectrum (FAS). The results of using the methods are compared with independently observed data and between the estimations from the records. For the case of the Hector Mine earthquake, the calculated intensities in general agree with the observed values. For the case of the Chi-Chi earthquake, the areas of maximum calculated intensity correspond to the areas of the greatest damage and highest number of fatalities. However, the FAS method producees higher-intensity values than those of the peak amplitude method. The specific features of ground-motion excitation during the large, shallow, thrust earthquake may be considered a reason for the discrepancy. The use of PGA and PGV is simple; however, the use of FAS provides a natural consideration of site amplification by means of generalized or site-specific spectral ratios. Because the calculation of seismic-intensity maps requires rapid processing of data from a large network, it is very practical to generate a “first-order” map from the recorded peak motions. Then, a “second-order” map may be compiled using an amplitude–spectra method on the basis of available records and numerical modeling of the site-dependent spectra for the regions of sparse station spacing.

INTRODUCTION The most common information available immediately following a damaging earthquake is its magnitude and the epicentral location. However, it is also desirable to know the extent of the felt area, and, more important, the range of shaking experienced and the areal extent of strongest shaking. For most of the United States, there is insufficient seismic strong-motion station coverage to portray quickly and accurately the extent of strong shaking. Seismic intensity has been traditionally used worldwide as a method for quantifying the shaking pattern and the extent of damage for earthquakes. Though developed prior to the advent of today's modern seismometric instrumentation, seismic intensity scales nonetheless provide a useful framework to describe, in a simplified fashion, the complexity of ground motions and the extent and nature of the damage. A limitation of traditional intensity mapping has been the long time required to generate a detailed seismic intensity map, typically weeks...

INTRODUCTION The Pasadena Office of the U.S. Geological Survey (USGS), together with the Caltech Seismological Laboratory, operates a network of more than 350 remote seismometers in southern California called the S outhern C alifornia S eismic N etwork (SCSN). SCSN is part of TriNet, a cooperative project between the USGS, Caltech, and the California Division of Mines and Geology (CDMG). TriNet will upgrade the existing network to digital, add new stations, and develop real-time and early-warning capabilities. Signals from the SCSN sites are telemetered to a central processing location at the Caltech Seismological Lab in Pasadena. These signals are continuously monitored by computers that detect and record thousands of earthquakes each year. Phase arrival times for these events are picked by analysts and archived along with digital seismograms. Data acquisition, processing, and archiving are achieved using the Caltech/USGS Seismic Processing (CUSP) system (Dollar, 1989). These data have been compiled into the SCSN Catalog of...

INTRODUCTION A large amount of work has been done in recent years to estimate the distribution of slip on the fault surface during earthquakes. Generally, these slip models are derived from longer period ground motions: strong-motion velocity and displacement, and teleseismic velocity seismograms. At these longer periods, ground motions are predominantly deterministic and their waveforms can in general be accurately modeled using simple descriptions of the source and crustal structure. The opposite situation exists for the prediction of high-frequency strong ground motions. Ground motions at high frequencies are predominantly stochastic, and their waveforms in general cannot be accurately modeled using simple descriptions of the source and crustal structure. However, preliminary evidence ( e.g. , Hartzell et al. , 1996; Kamae and Irikura, 1998; Somerville, 1993; Somerville et al ., 1996; Wald et al. , 1988) suggests that variable slip models derived from longer-period ground-motion recordings are relevant for the prediction of higher-frequency ground motions. For...

We assess two competing dynamic interpretations that have been proposed for the short slip durations characteristic of kinematic earthquake models derived by inversion of earthquake waveform and geodetic data. The first interpretation would require a fault constitutive relationship in which rapid dynamic restrengthening of the fault surface occurs after passage of the rupture front, a hypothesized mechanical behavior that has been referred to as “self-healing.” The second interpretation would require sufficient spatial heterogeneity of stress drop to permit rapid equilibration of elastic stresses with the residual dynamic friction level, a condition we refer to as “geometrical constraint.” These interpretations imply contrasting predictions for the time dependence of the fault-plane shear stresses. We compare these predictions with dynamic shear stress changes for the 1992 Landers (M 7.3), 1994 Northridge (M 6.7), and 1995 Kobe (M 6.9) earthquakes. Stress changes are computed from kinematic slip models of these earthquakes, using a finite-difference method. For each event, static stress drop is highly variable spatially, with high stress-drop patches embedded in a background of low, and largely negative, stress drop. The time histories of stress change show predominantly monotonic stress change after passage of the rupture front, settling to a residual level, without significant evidence for dynamic restrengthening. The stress change at the rupture front is usually gradual rather than abrupt, probably reflecting the limited resolution inherent in the underlying kinematic inversions. On the basis of this analysis, as well as recent similar results obtained independently for the Kobe and Morgan Hill earthquakes, we conclude that, at the present time, the self-healing hypothesis is unnecessary to explain earthquake kinematics.

Using strong-motion data recorded in the Los Angeles region from the 1992 (Mw 7.3) Landers earthquake, we have tested the accuracy of existing three-dimensional (3D) velocity models on the simulation of long-period (≧2 sec) ground motions in the Los Angeles basin and surrounding San Fernando and San Gabriel Valleys. First, the overall pattern and degree of long-period excitation of the basins were identified in the observations. Within the Los Angeles basin, the recorded amplitudes are about three to four times larger than at sites outside the basins; amplitudes within the San Fernando and San Gabriel Valleys are nearly a factor of 3 greater than surrounding bedrock sites. Then, using a 3D finite-difference numerical modeling approach, we analyzed how variations in 3D earth structure affect simulated waveforms, amplitudes, and the fit to the observed patterns of amplification. Significant differences exist in the 3D velocity models of southern California that we tested (Magistrale et al., 1996; Graves, 1996a; Hauksson and Haase, 1997). Major differences in the models include the velocity of the assumed background models; the depth of the Los Angeles basin; and the depth, location, and geometry of smaller basins. The largest disparities in the response of the models are seen for the San Fernando Valley and the deepest portion of the Los Angeles basin. These arise in large part from variations in the structure of the basins, particularly the effective depth extent, which is mainly due to alternative assumptions about the nature of the basin sediment fill. The general ground-motion characteristics are matched by the 3D model simulations, validating the use of 3D modeling with geologically based velocity-structure models. However, significant shortcomings exist in the overall patterns of amplification and the duration of the long-period response. The successes and limitations of the models for reproducing the recorded ground motions as discussed provide the basis and direction for necessary improvements to earth structure models, whether geologically or tomographically derived. The differences in the response of the earth models tested also translate to variable success in the ability to successfully model the data and add uncertainty to estimates of the basin response given input “scenario” earthquake source models.

The Pasadena Office of the U.S. Geological Survey, together with the California Institute of Technology Seismology Laboratory (Caltech Seismo Lab), operates a network of more than 300 analog and digital remote seismometers in southern California called the Southern California Seismic Network (SCSN). Signals from these sites are telemetered to the central processing site at the Caltech Seismology Laboratory in Pasadena. These signals are continuously monitored by computers that detect and record thousands of earthquakes each year. Phase arrival times for these events are picked by analysts and archived along with digital seismograms. Data acquisition, processing, and archiving is achieved using the CUSP system (Dollar, 1989). These data are used to compile the SCSN Catalog of Earthquakes, a list beginning in 1932 that currently contains more than 300,000 events. This data set is critical to the evaluation of earthquake hazards in California and to the advancement of geoscience as a whole.

We present a rupture model of the Northridge earthquake, determined from the joint inversion of near-source strong ground motion recordings, P and SH teleseismic body waves, Global Positioning System (GPS) displacement vectors, and permanent uplift measured along leveling lines. The fault is defined to strike 122° and dip 40° to the south-southwest. The average rake vector is determined to be 101°, and average slip is 1.3 m; the peak slip reaches about 3 m. Our estimate of the seismic moment is 1.3 ± 0.2 × 1026 dyne-cm (potency of 0.4 km3). The rupture area is small relative to the overall aftershock dimensions and is approximately 15 km along strike, nearly 20 km in the dip direction, and there is no indication of slip shallower than about 5 to 6 km. The up-dip, strong-motion velocity waveforms are dominated by large S-wave pulses attributed to source directivity and are comprised of at least 2 to 3 distinct arrivals (a few seconds apart). Stations at southern azimuths indicate two main S-wave arrivals separated longer in time (about 4 to 5 sec). These observations are best modeled with a complex distribution of subevents: The initial S-wave arrival comes from an asperity that begins at the hypocenter and extends up-dip and to the north where a second, larger subevent is centered (about 12 km away). The secondary S arrivals at southern azimuths are best fit with additional energy radiation from another high slip region at a depth of 19 km, 8 km west of the hypocenter. The resolving power of the individual data sets is examined by predicting the geodetic (GPS and leveling) displacements with the dislocation model determined from the waveform data, and vice versa, and also by analyzing how well the teleseismic solution predicts the recorded strong motions. The general features of the geodetic displacements are not well predicted from the model determined independently from the strong-motion data; likewise, the slip model determined from geodetic data does not adequately reproduce the strong-motion characteristics. Whereas a particularly smooth slip pattern is sufficient to satisfy the geodetic data, the strong-motion and teleseismic data require a more heterogeneous slip distribution in order to reproduce the velocity amplitudes and frequency content. Although the teleseismic model can adequately reproduce the overall amplitude and frequency content of the strong-motion velocity recordings, it does a poor job of predicting the geodetic data. Consequently, a robust representation of the slip history and heterogeneity requires a combined analysis of these data sets.