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At least 793 records · Page 44Linked to original sources

USGS2021

Automated detection of clipping in broadband earthquake records

Because the amount of available ground‐motion data has increased over the last decades, the need for automated processing algorithms has also increased. One difficulty with automated processing is to screen clipped records. Clipping occurs when the ground‐motion amplitude exceeds the dynamic range of the linear response of the instrument. Clipped records in which the amplitude exceeds the dynamic range are relatively easy to identify visually yet challenging for automated algorithms. In this article, we seek to identify a reliable and fully automated clipping detection algorithm tailored to near‐real‐time earthquake response needs. We consider multiple alternative algorithms, including (1) an algorithm based on the percentage difference in adjacent data points, (2) the standard deviation of the data within a moving window, (3) the shape of the histogram of the recorded amplitudes, (4) the second derivative of the data, and (5) the amplitude of the data. To quantitatively compare these algorithms, we construct development and holdout datasets from earthquakes across a range of geographic regions, tectonic environments, and instrument types. We manually classify each record for the presence of clipping and use the classified records. We then develop an artificial neural network model that combines all the individual algorithms. Testing on the holdout dataset, the standard deviation and histogram approaches are the most accurate individual algorithms, with an overall accuracy of about 93%. The combined artificial neural network method yields an overall accuracy of 95%, and the choice of classification threshold can balance precision and recall.

Seismological Research Letters↗

USGS2022

Ground failure triggered by the 7 January 2020 M6.4 Puerto Rico earthquake

The 7 January 2020 M 6.4 Puerto Rico earthquake, the mainshock of an extended earthquake sequence, triggered significant ground failure. In this study, we detail the ground failure that occurred based largely on a postearthquake field reconnaissance campaign that we conducted. We documented more than 300 landslides, mainly rock falls that were concentrated in areas where peak ground acceleration (PGA) exceeded 30% g ; sparse smaller landslides occurred in highly susceptible areas more than 50 km from the epicenter and at PGA values <10% g . Though some of the largest mass movements were in natural slopes, rock falls in road cuts had more impact because they caused widespread transportation disruption. Some structures also were damaged by landslides, but no landslide‐related fatalities were reported. Liquefaction and related lateral spreading were severe in some areas, causing damage to residential and commercial structures and a power plant. Most of the liquefaction occurred in coastal areas where shaking exceeded 50% g , though some of the most damaging instances were in Ponce, where shaking estimates were as low as 20% g . In this article, we summarize the most notable ground failures and detail the overall patterns that we observed. The observations and compiled inventory datasets presented here are valuable because no island‐wide hazard maps for earthquake‐triggered landslides or liquefaction have been developed for Puerto Rico, and postevent inventories are vital for such an effort. In general, the datasets presented here contribute to a global understanding of coseismic ground‐failure hazard by presenting detailed observations for a relatively moderate ground‐failure event with well‐constrained shaking estimates; current models and expectations are biased by the tendency to collect detailed datasets mainly for exceptional events.

Puerto Rico↗

USGS2022

Working with dynamic earthquake rupture models: A practical guide

Dynamic rupture models are physics‐based simulations that couple fracture mechanics to wave propagation and are used to explain specific earthquake observations or to generate a suite of predictions to understand the influence of frictional, geometrical, stress, and material parameters. These simulations can model single earthquakes or multiple earthquake cycles. The objective of this article is to provide a self‐contained and practical guide for students starting in the field of earthquake dynamics. Senior researchers who are interested in learning the first‐order constraints and general approaches to dynamic rupture problems will also benefit. We believe this guide is timely given the recent growth of computational resources and the range of sophisticated modeling software that are now available. We start with a succinct discussion of the essential physics of earthquake rupture propagation and walk the reader through the main concepts in dynamic rupture model design. We briefly touch on fully dynamic earthquake cycle models but leave the details of this topic for other publications. We also highlight examples throughout that demonstrate the use of dynamic rupture models to investigate various aspects of the faulting process.

Seismological Research Letters↗

USGS2023

Introduction to the digitization of seismic data: A user’s guide

Modern seismic data are collected, distributed, and analyzed using digital formats, and this has become a standard for the field. Although most modern seismometers still make use of analog electronic circuits, their data are converted from an analog voltage output to time‐tagged counts by way of digitization. Although much of the digitization process is not complicated to conceptualize, there is a fair bit of jargon in digitizer specifications, and a few pitfalls that can arise in the processes of recording and analyzing ground‐motion data. In this article, we review some of the fundamental physical properties of data acquisition systems and the basic steps in digitizing data from an analog instrument (specifically a seismometer). We then briefly discuss the digitization process and some of the key properties needed to make these data useful for seismological applications. Finally, we discuss some of the filtering processes that naturally arise from digitization and how it can affect the processing workflow. The end goal is to provide a user guide that will enable seismologists to have a working knowledge of the digitization process. We focus on aspects central to seismological applications and have tried to avoid getting bogged down in signal processing formalism.

Seismological Research Letters↗

USGS2023

Comparison of co-recorded analog and digital systems for characterization of responses and uncertainties

One of the most prominent challenges related to legacy seismic data is determining how these data can be appropriately used in modern research applications. The wide variety of instrumentation used in the analog era, the format of recording on paper wrapped around a helicorder drum, and limited metadata information introduces ambiguities that are not typical of modern digital data. Therefore, techniques must be developed to help characterize uncertainties in legacy data. This article presents an analysis that compares corecorded signals from two instruments—a Trillium Compact or Press‐Ewing (PE) seismometer for sensing ground motion and two recording systems: a modern Q330 digitizer or heated‐stylus system. Analyses of the recordings in both time and frequency domains indicate time uncertainty on the order of one second, identify a flat response in a 10–60 s band for the PE and drum recorder, and highlight how specific features of scans and paper seismograms (e.g., repeated portions of scans and line thickness) can cause timing jumps or reduced trace amplitude.

Seismological Research Letters↗

USGS2024

Reference 1D seismic velocity models for volcano monitoring and imaging: Methods, models, and applications

Seismic velocity models of the crust are an integral part of earthquake monitoring systems at volcanoes. 1D models that vary only in depth are typically used for real‐time hypocenter determination and serve as critical reference models for detailed 3D imaging studies and geomechanical modeling. Such models are usually computed using seismic tomographic methods that rely on P ‐ and S ‐wave arrival‐time picks from numerous earthquakes recorded at receivers around the volcano. Traditional linearized tomographic methods that jointly invert for source locations, velocity structure, and station corrections depend critically on having reasonable starting values for the unknown parameters, are susceptible to local misfit minima and divergence, and often do not provide adequate uncertainty information. These issues are often exacerbated by sparse seismic networks, inadequate distributions of seismicity, and/or poor data quality common at volcanoes. In contrast, modern probabilistic global search methods avoid these issues only at the cost of increased computation time. In this article, we review both approaches and present example applications and comparisons at several volcanoes in the United States, including Mount Hood (Oregon), Mount St. Helens (Washington), the Island of Hawai’i, and Mount Cleveland (Alaska). We provide guidance on the proper usage of these methods as relevant to challenges specific to volcano monitoring and imaging. Finally, we survey‐published 1D P ‐wave velocity models from around the world and use them to derive a generic stratovolcano velocity model, which serves as a useful reference model for comparison and when local velocity information is sparse.

Seismological Research Letters↗

USGS2024

On algorithmically determined versus traditional macroseismic intensity assignments

The utility of macroseismic data, defined as the effects of earthquakes on humans and the built environment, has been increasingly recognized following the advent of online systems that now produce unprecedented volumes of macroseismic intensity information. Contributed reports from the U.S. Geological Survey “Did You Feel It?” (DYFI) system ( Wald et al ., 1999 ) are used to generate intensity values with an algorithm based on seminal work by Dengler and Dewey (1998) . The algorithm was developed initially to reproduce intensity values assigned by expert opinion using questionnaire results collected by telephone survey. In this article, I discuss reasons why intensity values from (self‐selected) DYFI responses can differ from values that would be assigned by expert opinion given more complete data from randomly selected participants. For example, with the data used by Dengler and Dewey (1998) , intensities near 4 could be determined from the percentage of people who felt shaking in each town. With less spatially rich data from self‐selected participants, this percentage often cannot be determined reliably. Audible noises are key additional diagnostic criteria for modified Mercalli intensity (MMI) 4, but, although the DYFI system includes a question about noise, following Dengler and Dewey (1998) , the DYFI algorithm does not include a noise indicator. At the upper end of the scale, as defined the DYFI algorithm yields a maximum intensity value of 9.05, nominally corresponding to peak ground acceleration of 75% g . These and other factors can result in DYFI values that are low compared to traditional MMI values assigned using expert opinion, even absent factors that can bias traditional MMI assignments. Modern ground‐motion intensity conversion equations determined using DYFI intensities are expected to be appropriate for DYFI intensities, but the results of this study suggest that biases may be introduced if DYFI and traditional intensities are assumed to be interchangeable.

Seismological Research Letters↗

USGS2026

Opportunities and challenges for incorporating lithium-ion batteries into geophysical power systems

Batteries play a critical role at seismic and other geophysical stations in ensuring that the equipment receives uninterrupted power to make continuous observations of the Earth. Often sited in remote environments under a wide range of environmental conditions, these stations have almost ubiquitously used conventional lead‐acid batteries. However, recent advances in rechargeable lithium‐ion battery technology have led to the development of lithium‐iron phosphate (LFP) batteries that can replace lead‐acid batteries in energy storage systems. In the past three years, LFP battery production has grown over an order of magnitude, reducing their cost and increasing their availability. In this article, we examine the benefits and challenges associated with incorporating several types of LFP batteries into the power systems of geophysical stations. We review how fundamental differences in battery chemistry enable LFP batteries to weigh less than half of comparable lead‐acid batteries and may have longer service lives but have the added complexity of being managed by an integrated battery monitoring system (BMS) microcontroller. Through a controlled heat chamber experiment, we demonstrate that LFP batteries can be ideally suited for use in high‐temperature environments by offering longer service lives than lead‐acid batteries. However, for safety reasons, the BMS prevents most LFP batteries from being charged at temperatures <0°C, which complicates their use in colder regions and can lead to equipment damage if the charging system is not appropriately designed for this battery type. Finally, we address some of the unique challenges associated with adopting lithium batteries, including unexpected substantial (≤14 W) power consumption from the BMS, safety concerns, and shipping restrictions. It is our goal to help inform station operators and geophysicists about potential benefits and issues that can arise from using LFP batteries at seismic and geophysical stations in a range of environments.

Seismological Research Letters↗

USGS2025

Long‐period ground motions from dynamic rupture simulations of large earthquakes on the creeping Hayward–Calaveras–Rodgers Creek fault system

he Hayward, Calaveras, and Rodgers Creek faults in the San Francisco Bay region of California have a high probability of producing a large earthquake in the next decades. Although these faults creep, the creep is insufficient to keep up with their relatively rapid slip rates on their deepest sections, so they have been storing tectonic strain since their last large earthquakes, with the Hayward’s and Rodgers Creek’s more than 150 yr ago. We do not know what the next large Hayward–Calaveras–Rodgers Creek earthquakes will look like or how strongly they will shake the San Francisco Bay region. Harris et al. (2021) used the 3D dynamic (spontaneous) rupture method to simulate large earthquakes on these creeping faults. In this article, we examine the resulting simulated long‐period ( T > 1 s) ground shaking from 0 to 50 km distance, for earthquakes nucleating on the Hayward fault and earthquakes nucleating on the Rodgers Creek fault. We compare these simulated long‐period ground motions with the Boore et al. (2014) well‐established empirically based ground‐motion model suitable for the slowest material velocity in our 3D velocity structure. We find that the simulated long‐period ground motions from the creeping‐fault earthquake scenarios produce a reasonable agreement with the empirical expectations if frictional cohesion is included only where it is appropriate.

California↗

USGS2025

Nodal seismic deployment on Mauna Loa volcano, Hawaii: Dataset and preliminary insights

Mauna Loa is the largest active volcano on Earth, comprising ∼51% of the Island of Hawai‘i’s landmass and posing significant risks to the island’s communities, infrastructure, and natural environment. Historical eruptions have produced lava flows that have reached the ocean in as little as 3 hr. The timing and location of such lava flows in the past 200 yr underscore how critical determination of the location and geometry of magma storage and structure is for volcanic hazard assessment and eruption forecasting. Now, after nearly 38 yr of volcanic quiescence, Mauna Loa has erupted again. On 27 November 2022, fissures initiated within the summit caldera and then migrated to the northeast rift zone, where they generated a large lava flow that threatened a major highway. To improve our understanding of the geometry of this magma system, we deployed a temporary nodal array on Mauna Loa in the summer of 2024. This increased our seismic coverage sufficiently to image this magmatic system. This nodal array consists of 33 seismometers distributed on and around the volcano and was deployed for over three months to record seismic signals. The primary objective of this project is to resolve the high‐resolution seismic velocity structure and characterize seismic features associated with magma storage and ascent pathways. In this article, we present an overview of the deployment, evaluate the quality of the data, and show example recordings to evaluate the suitability of the data set for future seismic investigations, including earthquake relocation, seismic tomography, and receiver function analysis. Comparisons with nearby permanent broadband and short‐period seismic stations demonstrate that the nodal array recorded high‐quality waveforms, making it a valuable resource for constraining the magmatic system beneath Mauna Loa at multiple scales.

Hawaii↗

USGS2026

Cascadia Subduction Zone science: Call for the next generation community seismic velocity model

The Cascadia subduction zone (CSZ) hosts major seismic and tsunami hazards, yet key questions persist about the relationship between margin structure, fluid distribution, episodic tremor and slip, shallow megathrust behavior, shaking and tsunamigenesis, and the resulting hazard estimates. Addressing these problems requires an empirically grounded, three‐dimensional seismic velocity model to illuminate subsurface structure and properties and to provide a basis for geophysical studies such as earthquake simulations and ground‐motion estimation. In May 2024, the National Science Foundation‐funded Cascadia Region Earthquake Science Center (CRESCENT) community velocity model (CVM) working group, with U.S. Geological Survey and regional partners, convened a workshop to identify priorities for such a model. Participants emphasized the features necessary for addressing key science questions, including implementing findability, accessibility, interoperability, and reusability (FAIR) access, capturing along‐strike and along‐dip structural heterogeneity, resolving shallow offshore–onshore structure, constraining elastic properties and quantifying their uncertainties for numerical wave propagation simulations, their validation benchmarks, and supporting associated accurate earthquake ground‐motion simulations and hazard assessments. This article describes the priorities defined in the workshop, and a description of how, guided by these needs, CRESCENT plans to develop multiple generations of a CVM to advance CSZ science and improve seismic and tsunami hazard modeling across the Pacific Northwest. The CVM will span the CSZ from the surface to ∼100 km depth, offshore and east of the Cascades into Idaho (∼132°–110° W) and the southern and northern tectonic regime transitions (∼36°–52° N) to capture the entire tectonic system as well as its surroundings.

Cascadia Subduction Zone↗

USGS2023

Evaluating a prospective fault-based stress-transfer forecast for the M7.9 Wenchuan earthquake region 15 years later

Four days after the 12 May 2008 M 7.9 Wenchuan earthquake struck the Sichuan region of China, we submitted a prospective earthquake forecast based on transfer of stress from the mainshock onto significant faults crossing through populated areas. We identified where the largest aftershocks were likely to occur that could cause loss of life. We returned the revised article to the journal on 5 June 2008, marking the last day of our observation period. The primary testable features are locations and focal mechanisms of larger ( M ≥ 4.5) earthquakes; did these events happen on or very near the faults we said they would? Did they have the same strikes, dips, and rakes as the faults we modeled? In retrospect, is the stress transfer method consistent with all M ≥ 4.5 earthquakes that occurred? We find all but one M ≥ 4.5 aftershock with known focal mechanisms located on stress‐increased faults, and their focal mechanism parameters overlap with geological characteristics we used in making calculations. Six of the seven lethal M > 4.5 earthquakes that occurred in the region since 5 June 2008 were located on stress‐increased faults, with the lone exception triggered by hydraulic fracturing.

The Seismic Record↗

USGS1994

Triggered seismicity and deformation between the Landers, California, and Little Skull Mountain, Nevada, earthquakes

This article presents evidence for the channeling of strain energy released by the M s = 7.4 Landers, California, earthquake within the eastern California shear zone ( ECSZ ). We document an increase in seismicity levels during the 22-hr period starting with the Landers earthquake and culminating 22 hr later with the M s = 5.4 Little Skull Mountain ( LSM ), Nevada, earthquake. We evaluate the completeness of regional seismicity catalogs during this period and find that the continuity of post-Landers strain release within the ECSZ is even more pronounced than is evident from the catalog data. We hypothesize that regional-scale connectivity of faults within the ECSZ and LSM region is a critical ingredient in the unprecedented scale and distribution of remotely triggered earthquakes and geodetically manifest strain changes that followed the Landers earthquake. The viability of static strain changes as triggering agents is tested using numerical models. Modeling results illustrate that regional-scale fault connectivity can increase the static strain changes by approximately an order of magnitude at distances of at least 280 km, the distance between the Landers and LSM epicenters. This is possible for models that include both a network of connected faults that slip “sympathetically” and realistic levels of tectonic prestrain. Alternatively, if dynamic strains are a more significant triggering agent than static strains, ECSZ structure may still be important in determining the distribution of triggered seismic and aseismic deformation.

California, Nevada↗

USGS1997

Variability of site response in the Los Angeles urban area

This article addresses the variability of site response in the Los Angeles area and possible structural causes for the observations. Aftershock records from 231 sites in the San Fernando and Los Angeles basins and the surrounding mountains are used in this study. Spectral ratios, taken with respect to a low-amplitude reference site, are used to document the variation in site amplification in the frequency range 2 to 6 Hz, both spatially and with backazimuth to the source. At higher frequencies (6 to 10 Hz), spectral ratios are shown to have greater spatial variability. Interstation spectral ratios are used to measure the standard deviation among source as a function of station separation. An increase in the variation in ground motion is shown to take place at a station separation of 1 km. Relative site-response estimates between nearby stations are used to demonstrate that preferred directions of motion can exist even in areas with no surface topographic effects.

California↗

USGS1998

Seismic-reflection evidence that the hayward fault extends into the lower crust of the San Francisco Bay Area, California

This article presents deep seismic-reflection data from an experiment across San Francisco Peninsula in 1995 using large (125 to 500 kg) explosive sources. Shot gathers show a mostly nonreflective upper crust in both the Franciscan and Salinian terranes (juxtaposed across the San Andreas fault), an onset of weak lower-crustal reflectivity beginning at about 6-sec two-way travel time ( TWTT ) and bright southwest-dipping reflections between 11 and 13 sec TWTT . Previous studies have shown that the Moho in this area is no deeper than 25 km (∼8 to 9 sec TWTT ). Three-dimensional reflection travel-time modeling of the 11 to 13 sec events from the shot gathers indicates that the bright events may be explained by reflectors 15 to 20 km into the upper mantle, northeast of the San Andreas fault. However, upper mantle reflections from these depths were not observed on marine-reflection profiles collected in San Francisco Bay, nor were they reported from a refraction prifile on San Francisco Peninsula. The most consistent interpretation of these events from 2D raytracing and 3D travel-time modeling is that they are out-of-plane reflections from a high-angle (dipping ∼70° to the southwest) impedance contrast in the lower crust that corresponds with the surface trace of the Hayward fault. These results suggest that the Hayward fault truncates the horizontal detachment fault suggested to be active beneath San Francisco Bay.

California↗

USGS1999

Calculation of broadband time histories of ground motion: Comparison of methods and validation using strong-ground motion from the 1994 Northridge earthquake

This article compares techniques for calculating broadband time histories of ground motion in the near field of a finite fault by comparing synthetics with the strong-motion data set for the 1994 Northridge earthquake. Based on this comparison, a preferred methodology is presented. Ground-motion-simulation techniques are divided into two general methods: kinematic- and composite-fault models. Green's functions of three types are evaluated: stochastic, empirical, and theoretical. A hybrid scheme is found to give the best fit to the Northridge data. Low frequencies (< 1 Hz) are calculated using a kinematic-fault model and a 3D finite-difference code to propagate energy through a realistic 3D velocity structure. High frequencies (> 1 Hz) are calculated using a composite-fault model with a fractal subevent size distribution and stochastic, bandlimited, white-noise Green's functions. At frequencies below 1 Hz, theoretical elastic-wave-propagation synthetics introduce proper seismic-phase arrivals of body waves and surface waves. The 3D velocity structure more accurately reproduces record durations for the deep sedimentary basin structures found in the Los Angeles region. At frequencies above 1 Hz, scattering effects become important and wave propagation is more accurately represented by stochastic Green's functions. A fractal subevent size distribution for the composite fault model ensures an ω −2 spectral shape over the entire frequency band considered (0.1-20 Hz).

California↗

USGS2011

8 March 2010 Elazığ-Kovancilar (Turkey) Earthquake: observations on ground motions and building damage

An earthquake of M W = 6.1 occurred in the Elazığ region of eastern Turkey on 8 March 2010 at 02:32:34 UTC. The United States Geological Survey (USGS) reported the epicenter of the earthquake as 38.873°N-39.981°E with a focal depth of 12 km. Forty-two people lost their lives and 137 were injured during the event. The earthquake was reported to be on the left-lateral strike-slip east Anatolian fault (EAF), which is one of the two major active fault systems in Turkey. Teams from the Earthquake Engineering Research Center of the Middle East Technical University (EERC-METU) visited the earthquake area in the aftermath of the mainshock. Their reconnaissance observations were combined with interpretations of recorded ground motions for completeness. This article summarizes observations on building and ground damage in the area and provides a discussion of the recorded motions. No significant observations in terms of geotechnical engineering were made.

Seismological Research Letters↗

USGS2011

Developing seismogenic source models based on geologic fault data

Calculating seismic hazard usually requires input that includes seismicity associated with known faults, historical earthquake catalogs, geodesy, and models of ground shaking. This paper will address the input generally derived from geologic studies that augment the short historical catalog to predict ground shaking at time scales of tens, hundreds, or thousands of years (e.g., SSHAC 1997). A seismogenic source model, terminology we adopt here for a fault source model, includes explicit three-dimensional faults deemed capable of generating ground motions of engineering significance within a specified time frame of interest. In tectonically active regions of the world, such as near plate boundaries, multiple seismic cycles span a few hundred to a few thousand years. In contrast, in less active regions hundreds of kilometers from the nearest plate boundary, seismic cycles generally are thousands to tens of thousands of years long. Therefore, one should include sources having both longer recurrence intervals and possibly older times of most recent rupture in less active regions of the world rather than restricting the model to include only Holocene faults (i.e., those with evidence of large-magnitude earthquakes in the past 11,500 years) as is the practice in tectonically active regions with high deformation rates. During the past 15 years, our institutions independently developed databases to characterize seismogenic sources based on geologic data at a national scale. Our goal here is to compare the content of these two publicly available seismogenic source models compiled for the primary purpose of supporting seismic hazard calculations by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and the U.S. Geological Survey (USGS); hereinafter we refer to the two seismogenic source models as INGV and USGS, respectively. This comparison is timely because new initiatives are emerging to characterize seismogenic sources at the continental scale (e.g., SHARE in the Euro-Mediterranean, http://www.share-eu.org/; EMME in the Middle East, http://www.emme-gem.org/) and global scale (e.g., GEM, http://www.globalquakemodel.org/; Anonymous 2008). To some extent, each of these efforts is still trying to resolve the level of optimal detail required for this type of compilation. The comparison we provide defines a common standard for consideration by the international community for future regional and global seismogenic source models by identifying the necessary parameters that capture the essence of geological fault data in order to characterize seismogenic sources. In addition, we inform potential users of differences in our usage of common geological/seismological terms to avoid inappropriate use of the data in our models and provide guidance to convert the data from one model to the other (for detailed instructions, see the electronic supplement to this article). Applying our recommendations will permit probabilistic seismic hazard assessment codes to run seamlessly using either seismogenic source input. The USGS and INGV database schema compare well at a first-level inspection. Both databases contain a set of fields representing generalized fault three-dimensional geometry and additional fields that capture the essence of past earthquake occurrences. Nevertheless, there are important differences. When we further analyze supposedly comparable fields, many are defined differently. These differences would cause anomalous results in hazard prediction if one assumes the values are similarly defined. The data, however, can be made fully compatible using simple transformations.

Seismological Research Letters↗