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USGS2021

Evaluating spectral ratio methods for characterizing fundamental resonance peaks on flat sediments: An example from the Atlantic Coastal Plain, Eastern United States

Damaging ground motions from the 2011 M w "> M w 5.8 Virginia earthquake were likely increased due to site amplification from the unconsolidated sediments of the Atlantic Coastal Plain (ACP), highlighting the need to understand site response on these widespread strata along the coastal regions of the eastern United States. The horizontal‐to‐vertical spectral ratio (HVSR) method, using either earthquake signals or ambient noise as input, offers an appealing method for measuring site response on laterally extensive sediments, because it requires a single seismometer rather than requiring a nearby bedrock site to compute a horizontal sediment‐to‐bedrock spectral ratio (SBSR). Although previous studies show mixed results when comparing the two methods, the majority of these studies investigated site responses in confined sedimentary basins that can generate substantial 3D effects or have relatively small reflection coefficients at their base. In contrast, the flat‐lying ACP strata and the underlying bedrock reflector should cause 1D resonance effects to dominate site response, with amplification of the fundamental resonance peaks controlled by the strong impedance contrast between the base of the sediments and the underlying bedrock. We compare site‐response estimates on the ACP strata derived using the HVSR and SBSR methods from teleseismic signals recorded by regional arrays and observe a close match in the frequencies of the fundamental resonance peak ( ⁠ f 0 "> f 0 ⁠ ) determined by both methods. We find that correcting the HVSR amplitude using source term information from a bedrock site and multiplying the peak by a factor of 1.2 results in amplitude peaks that, on average, match SBSR results within a factor of 2. We therefore conclude that the HVSR method may successfully estimate regional linear weak‐motion site‐response amplifications from the ACP, or similar geologic environments, when appropriate region‐specific corrections to the amplitude ratios are used.

Atlantic Coastal Plain↗

USGS2022

Partitioning ground motion uncertainty when conditioned on station data

Rapid estimation of earthquake ground shaking and proper accounting of associated uncertainties in such estimates when conditioned on strong‐motion station data or macroseismic intensity observations are crucial for downstream applications such as ground failure and loss estimation. The U.S. Geological Survey ShakeMap system is called upon to fulfill this objective in light of increased near‐real‐time access to strong‐motion records from around the world. Although the station data provide a direct constraint on shaking estimates at specific locations, these data also heavily influence the uncertainty quantification at other locations. This investigation demonstrates methods to partition the within‐ (phi) and between‐event (tau) uncertainty estimates under the observational constraints, especially when between‐event uncertainties are heteroscedastic. The procedure allows the end users of ShakeMap to create separate between‐ and within‐event realizations of ground‐motion fields for downstream loss modeling applications in a manner that preserves the structure of the underlying random spatial processes.

Bulletin of the Seismological Society of America↗

USGS2015

How to recognize a “Beast Quake” and a “Dance Quake”

Any good seismologist–carryball (i.e., American football) fan remembers the “beast quake” of 2011. Seahawks fans’ exuberant reactions to a Marshawn Lynch (in beast mode) run caused the stadium to shake enough to be well recorded on a strong‐motion seismograph a block away ( Vidale, 2011 ). With the Seahawks at home for the National Football Conference (NFC) Championship playoffs, both last year and this year, the Pacific Northwest Seismic Network (PNSN) received permission to install some seismometers in the stadium. Motivations for the experiment included testing the field and telemetry equipment, examining analysis and display techniques, and practicing quick reactions to mobilize field experiments. With PNSN students and staff who are also Seahawks fans, it was not hard to get volunteers to do the installations and monitor the on‐field actions and the resulting seismograms.

Seismological Research Letters↗

USGS2022

Prospective and retrospective evaluation of the U.S. Geological Survey public aftershock forecast for the 2019-2021 Southwest Puerto Rico Earthquake and aftershocks

The M w "> M w 6.4 Southwest Puerto Rico Earthquake of 7 January 2020 was accompanied by a robust fore‐ and aftershock sequence. The U.S. Geological Survey (USGS) has issued regular aftershock forecasts for more than a year since the mainshock, available on a public webpage. Forecasts were accompanied by interpretive and informational material, published in English and Spanish. Informational products included narrative “scenarios” for how the aftershock sequence could play out, infographics, and a report on the potential duration of the aftershock sequence through the next decade. Forecasts are based on the epidemic‐type aftershock sequence (ETAS) model and generated using the USGS AftershockForecaster software—an interactive graphical user interface built on the OpenSHA platform ( Field et al. , 2003 ). The initial forecast is based on past sequences in similar tectonic environments; subsequent forecasts are tuned to the ongoing sequence via Bayesian model updating. Probabilistic aftershock forecasts for the next day, week, month, and year were publicly released and archived at a daily to monthly tempo, allowing for a truly prospective test of the forecast. Here, we evaluate the forecast over the first year of the recorded aftershocks. The ETAS‐based forecast performed well overall, successfully capturing both the chance of having at least one earthquake of a given magnitude in a forecast interval as well as the non‐Poissonian distribution of the total number of aftershocks within an interval. A retrospective analysis shows that the ETAS model is a substantial improvement over the existing Reasenberg and Jones (1989) forecast model. The exercise also reveals some limitations of the current model, in particular, with respect to nonstationarities in the aftershock magnitude distribution and model parameters throughout the evolving sequence.

Puerto Rico↗

USGS2023

MLAAPDE: A machine learning dataset for determining global earthquake source parameters

The Machine Learning Asset Aggregation of the Preliminary Determination of Epicenters (MLAAPDE) dataset is a labeled waveform archive designed to enable rapid development of machine learning (ML) models used in seismic monitoring operations. MLAAPDE consists of more than 5.1 million recordings of 120 s long three‐component broadband waveform data (raw counts) for P , Pn , Pg , S , Sn , and Sg arrivals. The labeled catalog is collected from the U.S. Geological Survey National Earthquake Information Center’s (NEIC) Preliminary Determination of Epicenters bulletin, which includes local to teleseismic observations for earthquakes ∼ M 2.5 and larger. Each arrival in the labeled dataset has been manually reviewed by NEIC staff. An accompanying Python module enables users to develop customized training datasets, which includes different time‐series lengths, distance ranges, sampling rates, and/or phase lists. MLAAPDE is distinct from other publicly available datasets in containing local (14%), regional (36%), and teleseismic (50%) observations, in which local, regional, and teleseismic distance are 0°–3°, 3°–30°, and 30°+, respectively. A recent version of the dataset is publicly available (see Data and Resources ), and user‐specific versions can be generated locally with the accompanying software. MLAAPDE is an NEIC supported, curated, and periodically updated dataset that can contribute to seismological ML research and development.

Seismological Research Letters↗

USGS2016

Uncertainty in V s30 -based site response

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.

Bulletin of the Seismological Society of America↗

USGS2014

Why the New Madrid earthquakes are M 7–8 and the Charleston earthquake is ∼M 7

Estimates of magnitudes of large historical earthquakes are an essential input to and can seriously affect seismic‐hazard estimates. The earthquake‐intensity observations, modified Mercalli intensities (MMI), and assigned magnitudes M of the 1811–1812 New Madrid events have been reinterpreted several times in the last decade and have been a source of controversy in making seismic‐hazard estimates in the central United States. Observations support the concept that the larger the earthquake, the greater the maximum‐felt distance. For the same crustal attenuation and local soil conditions, magnitude should be the main influence on intensity values at large distances. We apply this concept by comparing the mean MMI at distances of 600–1200 km for each of the four largest New Madrid 1811–1812 earthquakes, the 1886 Charleston, South Carolina, earthquake, the 1929 M 7.2 Grand Banks earthquake, and the 2001 M 7.6 Bhuj, India, earthquake. We fit the intensity observations using the form MMI= A + C ×dist−0.8×log(dist) to better define intensity attenuation in eastern North America (ENA). The intensity attenuation in cratonic India differs from ENA and is corrected to ENA using both the above estimate and published intensity relations. We evaluate source, marine geophysical, Q , and stress‐drop information, as well as a 1929 Milne–Shaw record at Chicago to confirm that the 1929 Grand Banks earthquake occurred in ENA crust. Our direct comparison of mean intensities beyond 600 km suggests M 7.5, 7.3, 7.7, and 6.9 for the three New Madrid 1811–1812 mainshocks and the largest aftershock and M 7.0 for the 1886 Charleston, South Carolina, earthquake, with an estimated uncertainty of 0.3 units at the 95% confidence level (based on a Monte Carlo analysis). Our mean New Madrid and Charleston mainshock magnitudes are similar to those of Bakun and Hopper (2004) and are much higher than those of Hough and Page (2011) for New Madrid.

Bulletin of the Seismological Society of America↗

USGS2014

Frequency-dependent seismic attenuation in the eastern United States as observed from the 2011 central Virginia earthquake and aftershock sequence

Ground shaking due to earthquakes in the eastern United States (EUS) is felt at significantly greater distances than in the western United States (WUS) and for some earthquakes it has been shown to display a strong preferential direction. Shaking intensity variation can be due to propagation path effects, source directivity, and/or site amplification. In this paper, we use S and Lg waves recorded from the 2011 central Virginia earthquake and aftershock sequence, in the Central Virginia Seismic Zone, to quantify attenuation as frequency‐dependent Q ( f ). In support of observations based on shaking intensity, we observe high Q values in the EUS relative to previous studies in the WUS with especially efficient propagation along the structural trend of the Appalachian mountains. Our analysis of Q ( f ) quantifies the path effects of the northeast‐trending felt distribution previously inferred from the U.S. Geological Survey (USGS) “Did You Feel It” data, historic intensity data, and the asymmetrical distribution of rockfalls and landslides.

Bulletin of the Seismological Society of America↗

USGS2023

Nonlinear radiation damping: A new method for dissipating energy in dynamic earthquake rupture simulations

Dynamic earthquake rupture simulations are used to understand earthquake mechanics and the ground shaking that earthquakes produce. These simulations can help diagnose past earthquake behavior and are also used to generate scenarios of possible future earthquakes. Traditional dynamic rupture models generally assume elastic rock response, but this can lead to peak on‐fault slip rates and ground shaking that are higher than those inferred from seismological observations. Some have approached this challenge using inelastic off‐fault rock behavior to dissipate energy, but the addition of inelasticity can make it difficult to select parameters and establish suitable initial conditions, and increases the model’s complexity and computational cost. We propose a new method that works by adding a nonlinear radiation damping term to the friction law, with the surrounding rocks remaining linear elastic. Our new method results in lower peak slip rates, reduced seismic radiation, and an increasing slip‐weakening critical distance with increasing rupture propagation distance, all within a linear elastic model. In addition, it is easy to implement.

The Seismic Record↗

USGS2000

Geology in the 1996 USGS seismic-hazard maps, central and eastern United States

The current (1996) national probabilistic seismic-hazard maps utilize information about geologic structure and tectonics of the central and eastern U.S. to compensate for uncertainty that arises from the short seismicity record. Geology was incorporated into the maps mainly as seven source zones that are delineated in three distinct ways. The North American stable continental region is divided into two large zones, the sparsely seismic Precambrian craton and the more active Phanerozoic rim. Five other source zones are much smaller - the Wabash Valley source zone is within the craton, whereas the Reelfoot Rift, eastern Tennessee, Charleston, and Charlevoix source zones are in the Phanerozoic rim of the continent. We document these zones and explain and justify their use. The seven zones provide a foundation from which we suggest a criterion for including more geology in future maps.

Seismological Research Letters↗

USGS1990

Source parameters and effects of bandwidth and local geology on high- frequency ground motions observed for aftershocks of the northeastern Ohio earthquake of 31 January 1986

A 10-station array (GEOS) yielded recordings of exceptional bandwidth (400 sps) and resolution (up to 96 dB) for the aftershocks of the moderate ( m b ≈ 4.9) earthquake that occurred on 31 January 1986 near Painesville, Ohio. Nine aftershocks were recorded with seismic moments ranging between 9 × 10 16 and 3 × 10 19 dyne-cm ( M w : 0.6 to 2.3). The two largest aftershocks (depth 5.3, 5.6 km; oblique right slip, rake ≈30°, strike ≈N25°E) yielded seismic signals above background noise at frequencies as high as 130 Hz at epicentral distances up to 17 km. The aftershock recordings at a site underlain by ≈8 m of lakeshore sediments show significant levels of high-frequency soil amplification of vertical motion at frequencies near 8, 20, and 70 Hz. Viscoelastic models for P and SV waves incident at the base of the sediments yield estimates of vertical P -wave response consistent with the observed high-frequency site resonances, but suggest additional detailed shear-wave logs are needed to account for observed S -wave response. Peak acceleration values obtained from the broadband recordings are about two and four times as large as those that would be recorded on strong-motion recorders or short-period networks with upper bandwidth limits of 30 and 15 Hz, respectively. Attenuation-corrected acceleration spectra are used to reduce the influence of high-frequency (up to 100 Hz) local site effects on corner frequency estimates. The moment versus source radius trend inferred for events with moments as small as 9 × 10 16 dyne-cm, based on the Brune source model, extends previous relations inferred for the central United States, shows little evidence for a minimum source radius, and suggests that stress drops for the smaller events ( M 0 < 10 19 dyne-cm) decrease with decreasing moment.

Ohio↗

USGS2001

Trends in long-period seismicity related to magmatic fluid compositions

Sound speeds and densities are calculated for three different types of fluids: gas-gas mixture; ash-gas mixture; and bubbly liquid. These fluid properties are used to calculate the impedance contrast (Z) and crack stiffness (C) in the fluid-driven crack model (Chouet: J. Geophys. Res., 91 (1986) 13,967; 101 (1988) 4375; A seismic model for the source of long-period events and harmonic tremor. In: Gasparini, P., Scarpa, R., Aki, K. (Eds.), Volcanic Seismology, IAVCEI Proceedings in Volcanology, Springer, Berlin, 3133). The fluid-driven crack model describes the far-field spectra of long-period (LP) events as modes of resonance of the crack. Results from our calculations demonstrate that ash-laden gas mixtures have fluid to solid density ratios comparable to, and fluid to solid velocity ratios lower than bubbly liquids (gas-volume fractions <10%). This difference results in synthetic far-field spectra with higher impedance contrasts and narrower spectral bandwidths for ash-laden gas mixture than spectra for bubbly liquids. Spectral characteristics are described in terms of the quality factor Q-1. Q-1 is measured by the ratio of the frequency of the dominant spectral peak to the bandwidth of the peak measured at one half of its amplitude. This factor expresses the losses of energy due to elastic radiation Q-1r and other dissipative mechanisms Q-1i at the source, Q-1 = Q-1r + Q-1i. Spectra for LP events recorded at active volcanoes such as Galeras in Colombia and Kilauea in Hawaii, have Q-1 factors in the range of 0.1-0.002. The Q-1r factors due to radiation loss calculated for a sphere filled with a H2O-CO2 or H2O-SO2 gas mixture, vary between 0.0015 and 0.0040 with a change in wt% H2O at 800-1600 K and 10-50 MPa. For gas-rich mixtures, Q-1r has a strong dependence on resonator geometry (spherical versus rectangular). The spectra from a resonating sphere filled with gas-rich mixture yields values of Q-1r an order of magnitude smaller than those from a rectangular crack. For a resonating crack filled with an ash-gas mixture (or pseudogas), Q-1r varies parabolically from ???0.006 for an ash-rich mixture, to 0.0015 or 0.0023 for a H2O-rich or CO2-rich mixture at 800 K and 25 MPa. For low (<20%) gas-volume fraction fluids (foams, bubbly fluids and ash-rich pseudogases), the magnitudes for Q-1r are independent of crack geometry. Spectra associated with a foam (gas-volume fractions 10-90%) or bubbly basalt (gas-volume fractions <10%) may have a dominant spectral peak with values of Q-1r on the order of 0.01 and 0.1, respectively. The spectra from a resonating sphere filled with a foam containing >20% gas-volume fraction yields values of Q-1r similar to those for a rectangular crack. As with gas-gas and ash-gas mixtures, an increase in mass fraction narrows the bandwidth of the dominant mode and shifts the spectra to lower frequencies. Including energy losses due to dissipative processes in a bubbly liquid increases attenuation. Attenuation may also be higher in ash-gas mixtures and foams if the effects of momentum and mass transfer between the phases were considered in the calculations. ?? 2001 Elsevier Science B. V. All rights reserved.

Journal of Volcanology and Geothermal Research↗

USGS2021

Coseismic fault slip and afterslip associated with the M5.7 March 18, 2020 Magna, Utah, earthquake

The 2020 Magna, Utah, earthquake produced observable crustal deformation over a ∼ 100 km 2 area around the southeast margin of Great Salt Lake, but it did not produce any surface rupture. To obtain a detailed picture of the fault slip, we combine strong motion seismic waveforms with GPS static oﬀsets and Interferometric Synthetic Aperture Radar (InSAR) observations to obtain kinematic and static slip models of the event. We sample the regional seismic waveﬁeld with 3-component records from 68 stations of the University of Utah Seismograph Stations network. We ﬁnd that coseismic slip and afterslip, with predominantly normal slip, distributed on a shallowly west-dipping plane, possibly augmented by afterslip on a steeply northeast-dipping plane, best ﬁts the joint dataset. The west-dipping plane locates near previously inferred sources of interseismic creep at depth. Hence the earthquake may have occurred on the downdip ex-tension of the Wasatch fault and activated further slip (afterslip) at shallow depth east of the hypocenter. This inferred afterslip may have driven the vigorous aftershock activity that was concentrated east of the hypocenter.

Utah↗

USGS2007

The energy radiated by the 26 December 2004 Sumatra-Andaman earthquake estimated from 10-minute P-wave windows

The rupture process of the Mw 9.1 Sumatra-Andaman earthquake lasted for approximately 500 sec, nearly twice as long as the teleseismic time windows between the P and PP arrival times generally used to compute radiated energy. In order to measure the P waves radiated by the entire earthquake, we analyze records that extend from the P-wave to the S-wave arrival times from stations at distances ?? >60??. These 8- to 10-min windows contain the PP, PPP, and ScP arrivals, along with other multiply reflected phases. To gauge the effect of including these additional phases, we form the spectral ratio of the source spectrum estimated from extended windows (between TP and TS) to the source spectrum estimated from normal windows (between TP and TPP). The extended windows are analyzed as though they contained only the P-pP-sP wave group. We analyze four smaller earthquakes that occurred in the vicinity of the Mw 9.1 mainshock, with similar depths and focal mechanisms. These smaller events range in magnitude from an Mw 6.0 aftershock of 9 January 2005 to the Mw 8.6 Nias earthquake that occurred to the south of the Sumatra-Andaman earthquake on 28 March 2005. We average the spectral ratios for these four events to obtain a frequency-dependent operator for the extended windows. We then correct the source spectrum estimated from the extended records of the 26 December 2004 mainshock to obtain a complete or corrected source spectrum for the entire rupture process (???600 sec) of the great Sumatra-Andaman earthquake. Our estimate of the total seismic energy radiated by this earthquake is 1.4 ?? 1017 J. When we compare the corrected source spectrum for the entire earthquake to the source spectrum from the first ???250 sec of the rupture process (obtained from normal teleseismic windows), we find that the mainshock radiated much more seismic energy in the first half of the rupture process than in the second half, especially over the period range from 3 sec to 40 sec.

Bulletin of the Seismological Society of America↗

USGS2006

A stochastic estimate of ground motion at Oceano, California, for the M 6.5 22 December 2003 San Simeon earthquake, derived from aftershock recordings

The U.S. Geological Survey deployed a digital seismic station in Oceano, California, in February 2004, to investigate the cause of damage and liquefaction from the 22 December 2003 M 6.5 San Simeon earthquake. This station recorded 11 M > 2.8 aftershocks in almost 8 weeks. We analyze these recordings, together with recordings of the mainshock and the same aftershocks obtained from nearby stations in Park Hill and San Luis Obispo, to estimate the mainshock ground motion in Oceano. We estimate the Fourier amplitude spectrum using generalized spectral ratio analysis. We test a set of aftershocks as Green's functions by comparing simulated and recorded acceleration amplitude spectra for the mainshock at San Luis Obispo and Park Hill. We convolve the aftershock accelerograms with a stochastic operator to simulate the duration and phase of the mainshock accelerograms. This approximation allows us to extend the range of aftershocks that can be used as Green's functions to events nearly three magnitude units smaller than the mainshock. Our realizations for the mainshock accelerogram at Oceano yield peak ground accelerations distributed as 28% ?? 4%g. We interpret these realizations as upper bounds for the actual ground motion, because our analysis assumes a linear response, whereas the presence of liquefaction indicates that the ground behaved nonlinearly in Oceano.

Bulletin of the Seismological Society of America↗

USGS1994

Seismological aspects of the 1989-1990 eruptions at redoubt volcano, Alaska: the SSAM perspective

SSAM is a simple and inexpensive tool for continuous monitoring of average seismic amplitudes within selected frequency bands in near real-time on a PC-based data acquisition system. During the 1989-1990 eruption sequence at Redoubt Volcano, the potential of SSAM to aid in rapid identification of precursory Long-Period (LP) event swarms was realized, and since this time SSAM has been incorporated in routine monitoring efforts of the Alaska Volcano Observatory. In particular, an eruption that occurred on April 6 was successfully forecast primarily on the basis of recognizing the precursory LP activity on SSAM. Of twenty-two significant eruptions that occurred between December 14 and April 21, eleven had precursory swarms longer than one hour in duration that could be detected on SSAM. For individual swarms, the patterns of relative spectral amplitudes are distinct at each station and remain largely stationary through time, thus indicating that one source may have been preferentially and repeatedly activated throughout the swarm. Typically, a single spectral band dominates the signal at each seismic station: for the vigorous one-day swarm that preceded the first eruption on December 14, signals were sharply peaked in the 1.9-2.7 Hz band at the closest station, located 4 km from the vent, but were dominated by 1.3-1.9 Hz energy at three more distant stations located 7.5-22 km from the vent. The tendency for the signals from different swarms recorded at the same station to be peaked in the same frequency band suggests that all of the sources are characterized by a predominant length scale. Signals from the precursory LP swarms became weaker as the eruption sequence progressed, and swarms that occurred in March and April could only be detected at seismographs on the volcanic edifice. Onset times of precursory LP swarms prior to eruptions ranged from a few hours to about one week, but after the initial vent-clearing phase that ended December 19 these intervals tended to become progressively shorter for successive swarms. These trends in the relative onset times and intensities of successive precursory LP swarms are consistent with an overall depressurization of the magmatic system through time. In general, each of the swarms had an emergent onset, but the intensities did not always increase steadily until the eruptions. Instead, as the time of an eruption approached the intensity usually increased more rapidly before peaking and then declining prior to the eruption; for three of the swarms, two distinct peaks in intensity were apparent. The time intervals between final peaks in swarm intensity and ensuing eruptions ranged from about 2 hours to almost 2 days, but the peaks always occurred closer to the eruptions than to the swarm onsets. Both the onset of LP swarm activity and a decline in intensity prior to an eruption may represent critical points in the process of pressurization that drives the flow of fluids and gas in a sealed magmatic system. A notable exception to this pattern is the eruption of March 9 which lacked a detectable precursory LP swarm, but was followed by an unusually long period of strong LP seismicity that may have been stimulated by a depressurization of the magmatic system resulting from dome failure. On both December 14 and January 2, the spectra of early syn-eruptive signals have peaked signatures much like those of the spectra of precursory LP activity from shortly before the eruptions; these similarities may indicate that the source of precursory seismicity continued to be active during at least the early part of each eruption. In syn-eruptive signals from March and April recorded at stations on the volcanic edifice, the dominant spectral energy progressively shifts with time during the eruption to lower frequencies; at least part of the energy in these signals may have been generated by the debris flows associated with dome failures. ?? 1994.

Journal of Volcanology and Geothermal Research↗

USGS1985

Determination of elastic wave velocity and relative hypocenter locations using refracted waves. I. Methodology

An arrival time difference method utilizing refracted arrivals from earthquakes in a homogeneous, layered earth model has been developed for the simultaneous determination of near-source (in situ) velocity and relative locations of earthquakes. The method is particularly applicable when analyzing data from arrays in which most of the recording stations are far (i.e., several focal depths) from a group of events. This iterative scheme locates earthquakes relative to a master event and performs an inversion for in situ velocity using a generalized inverseleast squares estimation procedure. Direct arrivals, when available, may be included to stabilize the inversion and increase the accuracy of the event locations. We tested this scheme on artificial data contaminated by random and systematic arrival time errors, gaps in azimuthal coverage, and inaccuracies in the assumed velocity model. As usual, depth is the least well-resolved hypocenter coordinate, but this scheme yielded accurate locations of most events while converging to the correct velocity model.

Bulletin of the Seismological Society of America↗

USGS1994

Southern surface rupture associated with the M 7.3 1992 Landers, California, earthquake

Although most evidence suggests that the 28 June 1992 M 7.3 Landers earthquake ruptured unilaterally north, significant surface rupture was mapped on the Eureka Peak and Burnt Mountain faults, to the south of the Landers epicenter. An eyewitness account reports that surface rupture occurred on the northern Eureka Peak fault within approximately 35 sec of the mainshock initiation. Array analysis of the Landers mainshock provides evidence in support of this report; a significant southern subevent in the early mainshock coda. I also analyze dense array recordings of a M 5.6 aftershock that occurred 3 min after the mainshock at 34°7.65′N, 116°23.82′W and show that there is strong evidence that this event was also associated with significant rupture on the Eureka Peak fault. This analysis thus suggests that the Eureka Peak fault rupture was not caused by direct bilateral mainshock rupture but instead was initially triggered less than a minute after the mainshock and reruptured by the M 5.6 aftershock. Results for the evolution of the Landers sequence suggest that mainshock subevents may in some cases be accurately described as aftershocks (i.e., disjoint triggered events) that occur within the duration of mainshock strong ground motion.

California↗