Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Seismological Research Letters”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources
USGS2015

Preface to the focus section on injection-induced seismicity

The ongoing, dramatic increase in seismicity in the central United States that began in 2009 is believed to be the result of injection‐induced seismicity ( Ellsworth, 2013 ). Although the basic mechanism for activation of slip on a fault by subsurface fluid injection is well established ( Healy et al. , 1968 ; Raleigh et al. , 1976 ; Nicholson and Wesson, 1992 ; McGarr et al. , 2002 ; Ellsworth, 2013 ), the occurrence of damaging M ≥5 earthquakes and the dramatic increase in seismicity in the central United States has brought heightened attention to this issue. The elevated seismicity is confined to a limited number of areas, and accumulating evidence indicates that the seismicity in these locations is directly linked to nearby industrial operations. This Seismological Research Letters ( SRL ) focus section presents a selected set of seven technical papers that cover various aspects of this topic, including basic seismological and ground‐motion observations, case studies, numerical simulation of fault activation, and risk mitigation.

Seismological Research Letters↗
USGS2011

Preface to the Focused Issue on the 22 February 2011 Magnitude 6.2 Christchurch Earthquake

The 22 February 2011 magnitude 6.2 Christchurch earthquake, centered southeast of Christchurch, was part of the aftershock sequence that has been occurring since the September 2010 magnitude 7.1 quake near Darfield, 40 km west of the city. The Christchurch earthquake killed more than 180 people, damaged or destroyed more than 100,000 buildings, and is New Zealand's most deadly disaster since the earthquake that struck the Napier and Hastings area on 3 February 1931. This special focused issue of Seismological Research Letters , which I had the fortune to edit, contains a selected set of 19 original technical papers. These papers cover different aspects of the 2011 Christchurch earthquake from seismological, geodetic, geological, and engineering perspectives.

Christchurch↗
USGS2012

A comparison among observations and earthquake simulator results for the allcal2 California fault model

In order to understand earthquake hazards we would ideally have a statistical description of earthquakes for tens of thousands of years. Unfortunately the ∼100‐year instrumental, several 100‐year historical, and few 1000‐year paleoseismological records are woefully inadequate to provide a statistically significant record. Physics‐based earthquake simulators can generate arbitrarily long histories of earthquakes; thus they can provide a statistically meaningful history of simulated earthquakes. The question is, how realistic are these simulated histories? This purpose of this paper is to begin to answer that question. We compare the results between different simulators and with information that is known from the limited instrumental, historic, and paleoseismological data. As expected, the results from all the simulators show that the observational record is too short to properly represent the system behavior; therefore, although tests of the simulators against the limited observations are necessary, they are not a sufficient test of the simulators’ realism. The simulators appear to pass this necessary test. In addition, the physics‐based simulators show similar behavior even though there are large differences in the methodology. This suggests that they represent realistic behavior. Different assumptions concerning the constitutive properties of the faults do result in enhanced capabilities of some simulators. However, it appears that the similar behavior of the different simulators may result from the fault‐system geometry, slip rates, and assumed strength drops, along with the shared physics of stress transfer. This paper describes the results of running four earthquake simulators that are described elsewhere in this issue of Seismological Research Letters. The simulators ALLCAL (Ward, 2012), VIRTCAL (Sachs et al., 2012), RSQSim (Richards‐Dinger and Dieterich, 2012), and ViscoSim (Pollitz, 2012) were run on our most recent all‐California fault model, allcal2. With the exception of ViscoSim, which ran for 10,000 years, all the simulators ran for 30,000 years. Presentations containing content similar to this paper can be found at http://scec.usc.edu/research/eqsims/.

Seismological Research Letters↗
USGS2005

Comment on "How can seismic hazard around the New Madrid seismic zone be similar to that in California?" by Arthur Frankel

A recent paper in the September/October 2004 issue of Seismological Research Letters, “How Can Seismic Hazard around the New Madrid Seismic Zone Be Similar to That in California?”, by Arthur Frankel, concludes “I have demonstrated how probabilistic seismic hazard for New Madrid can be greater than that at San Francisco at low probabilities for PGA and similar at low probabilities for 5 Hz S.A. By low probabilities, I mean annual probabilities less than the reciprocal of the return time of the New Madrid characteristic source, that is, 1/500. This is a consequence of the higher ground motions, for PGA and 5 Hz S.A. (and other high-frequency measures), expected for large New Madrid characteristic earthquakes compared to San Andreas earthquakes with similar magnitudes.” His conclusion is confusing and not necessarily true. The fundamental differences in assessing seismic hazard between San Francisco and the New Madrid seismic zone are the uncertainties, especially the uncertainties associated with the ground-motion attenuation relationship. The larger ground-motion uncertainties in both the median and its standard deviation derive a higher hazard in the New Madrid area. The larger standard deviation, in particular, derives a higher hazard at low annual probabilities of exceedance. Moreover, Frankel also equated the hazard (annual probability of exceedance) defined in probabilistic seismic hazard analysis (PSHA) with the average recurrence rate defined in engineering risk analysis. There is a fundamental difference in defining risk between PSHA and the engineering risk analysis. The risks—10%, 5%, and 2% probability of exceedance (PE) in 50 years—defined in PSHA are not interchangeable with those defined in engineering risk analysis. Hence, though Frankel's stated intention was to improve understanding of PSHA among nonpractitioners, the paper may cause more confusion and problems for users of the U.S. Geological Survey national seismic hazard maps.

Seismological Research Letters↗
USGS2000

A volcano in North Carolina? A closer look at a tall tale

The legacy of the 1811-1812 New Madrid, Central United States, earthquakes is one of tremendous enigma. We are left with just enough contemporary information to provide a measure of constraint on the isoseismal contours and therefore magnitudes of the three principal events ( Nuttli, 1973 ; Street, 1982 ; Johnston, 1996 ; Hough et al., 2000 ), yet given the sparse population density and limited documentation of effects, our interpretations will always be plagued by a significant degree of uncertainty. Although the magnitudes of the three principal New Madrid main shocks will likely never be established with precision, all contemporary analyses (see above references) obtain magnitudes upward of 7 for all three events—large enough to produce perceptible ground motions as far away as the Atlantic seaboard. One enduring and interesting bit of folklore concerning the New Madrid earthquakes of 1811-1812 involves the tale of a volcanic eruption in North Carolina at the time of the first main shock on 16 December 1811. The site of this supposed volcano was approximately 750 km east of the main shock and 40 km northwest of Asheville, North Carolina, at an area known in the early 1800's as “the springs” or “the warm springs” ( Figure 1 ). I will henceforth refer to the location by the name of the town that exists there now: Hot Springs. The tale has merited a brief mention in some modern treatises on the New Madrid sequence. For example, Penick ( 1981 ) mentions the 1812 letter by Asheville, North Carolina resident John Clarke Edwards that described the supposed eruption. Penick ( 1981 ) goes on to note that the letter was quickly discredited as a hoax.

North Carolina↗
USGS2022

An assessment of uncertainties in VS profiles obtained from microtremor observations in the phased 2018 COSMOS blind trials

Site response is a critical consideration when assessing earthquake hazards. Site characterization is key to understanding site effects as influenced by seismic site conditions of the local geology. Thus, a number of geophysical site characterization methods were developed to meet the demand for accurate and cost-effective results. As a consequence, a number of studies have been administered periodically as blind trials to evaluate the state-of-practice on-site characterization. We present results from the Consortium of Organizations for Strong Motion Observation Systems (COSMOS) blind trials, which used data recorded from surface-based microtremor array methods (MAM) at four sites where geomorphic conditions vary from deep alluvial basins to an alpine valley. Thirty-four invited analysts participated. Data were incrementally released to 17 available analysts who participated in all four phases: (1) two-station arrays, (2) sparse triangular arrays, (3) complex nested triangular or circular arrays, and (4) all available geological control site information including drill hole data. Another set of 17 analysts provided results from two sites and two phases only. Although data from one site consisted of recordings from three-component sensors, the other three sites consisted of data recorded only by vertical-component sensors. The sites cover a range of noise source distributions, ranging from one site with a highly directional microtremor wave field to others with omni-directional (azimuthally distributed) wave fields. We review results from different processing techniques (e.g., beam-forming, spatial autocorrelation, cross-correlation, or seismic interferometry) applied by the analysts and compare the effectiveness between the differing wave field distributions. We define the M index as a quality index based on estimates of the time-averaged shear-wave velocity of the upper 10 ( V S10 ), 30 ( V S30 ), 100 ( V S100 ), and 300 ( V S300 ) meters and show its usefulness in quantitative comparisons of V S profiles from multiple analysts. Our findings are expected to aid in building an evidence-based consensus on preferred cost-effective arrays and processing methodology for future studies of seismic site effects.

Seismological Research Letters↗
USGS2022

Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults

Widespread surface creep is observed across a number of active faults included in the United States (US) National Seismic Hazard Model (NSHM). In northern California, creep occurs on the central section of the San Andreas fault, along the Hayward and Calaveras faults through the San Francisco Bay Area, and to the north coast region along the Maacama and Bartlett Springs faults. In southern California, creep is observed across the Coachella segment of the San Andreas fault, through the Brawley Seismic Zone, and along the Imperial and Superstition Hills faults. Seismic hazard assessments for California have accounted for creep using various data and methods, including the most recent Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3) in 2013. The purpose of this study is to expand and update the UCERF3 creep rate data set for the 2023 release of the US NSHM and to invert geodetic data and the surface creep rate data for the spatial distribution of interseismic fault creep on California faults using an elastic model with physical creep constraints. The updated surface creep rate compilation consists of a variety of data types including alignment arrays, offset cultural markers, creepmeters, Interferometric Synthetic Aperture Radar, and Global Positioning System data. We compile a total of 497 surface creep rate measurements, 400 of which are new and 97 of which appear in the UCERF3 compilation. We compute creep rate distributions for each of the five 2023 NSHM geodetic‐based and geologic‐based deformation models. Computed creep rates are used to reduce the total fault moment rate available for earthquake sequences in the NSHM model. We find that, despite relatively large variability in model long‐term slip rates across all five deformation models, the variability in depth‐averaged creep rate across all models is relatively small, typically 5–10 mm/yr along the creeping San Andreas fault section and only 2–4 mm/yr along the Maacama and Rodgers Creek‐Hayward faults.

California↗
USGS2012

Initial assessment of the intensity distribution of the 2011 M w 5.8 Mineral, Virginia, earthquake

The intensity data collected by the U.S. Geological Survey (USGS) "Did You Feel It?" (DYFI) Website (USGS, DYFI; http://earthquake.usgs.gov/earthquakes/dyfi/events/se/082311a/us/index.html, last accessed Sept 2011) for the M w 5.8 Mineral, Virginia, earthquake, are unprecedented in their spatial richness and geographical extent. More than 133,000 responses were received during the first week following the earthquake. Although intensity data have traditionally been regarded as imprecise and generally suspect (e.g., Hough 2000), there is a growing appreciation for the potential utility of spatially rich, systematically determined DYFI data to address key questions in earthquake ground-motions science (Atkinson and Wald, 2007; Hauksson et al., 2008).

Virginia↗
USGS2012

Trimming the UCERF2 hazard logic tree

The Uniform California Earthquake Rupture Forecast 2 (UCERF2) is a fully time‐dependent earthquake rupture forecast developed with sponsorship of the California Earthquake Authority (Working Group on California Earthquake Probabilities [WGCEP], 2007; Field et al., 2009). UCERF2 contains 480 logic‐tree branches reflecting choices among nine modeling uncertainties in the earthquake rate model shown in Figure 1. For seismic hazard analysis, it is also necessary to choose a ground‐motion‐prediction equation (GMPE) and set its parameters. Choosing among four next‐generation attenuation (NGA) relationships results in a total of 1920 hazard calculations per site. The present work is motivated by a desire to reduce the computational effort involved in a hazard analysis without understating uncertainty. We set out to assess which branching points of the UCERF2 logic tree contribute most to overall uncertainty, and which might be safely ignored (set to only one branch) without significantly biasing results or affecting some useful measure of uncertainty. The trimmed logic tree will have all of the original choices from the branching points that contribute significantly to uncertainty, but only one arbitrarily selected choice from the branching points that do not.

Seismological Research Letters↗
USGS2012

Casual instrument corrections for short-period and broadband seismometers

Of all the filters applied to recordings of seismic waves, which include source, path, and site effects, the one we know most precisely is the instrument filter. Therefore, it behooves seismologists to accurately remove the effect of the instrument from raw seismograms. Applying instrument corrections allows analysis of the seismogram in terms of physical units (e.g., displacement or particle velocity of the Earth’s surface) instead of the output of the instrument (e.g., digital counts). The instrument correction can be considered the most fundamental processing step in seismology since it relates the raw data to an observable quantity of interest to seismologists. Complicating matters is the fact that, in practice, the term “instrument correction” refers to more than simply the seismometer. The instrument correction compensates for the complete recording system including the seismometer, telemetry, digitizer, and any anti‐alias filters. Knowledge of all these components is necessary to perform an accurate instrument correction. The subject of instrument corrections has been covered extensively in the literature (Seidl, 1980; Scherbaum, 1996). However, the prospect of applying instrument corrections still evokes angst among many seismologists—the authors of this paper included. There may be several reasons for this. For instance, the seminal paper by Seidl (1980) exists in a journal that is not currently available in electronic format and cannot be accessed online. Also, a standard method for applying instrument corrections involves the programs TRANSFER and EVALRESP in the Seismic Analysis Code (SAC) package (Goldstein et al. , 2003). The exact mathematical methods implemented in these codes are not thoroughly described in the documentation accompanying SAC.

Seismological Research Letters↗
USGS2012

Have recent earthquakes exposed flaws in or misunderstandings of probabilistic seismic hazard analysis?

In a recent Opinion piece in these pages, Stein et al. (2011) offer a remarkable indictment of the methods, models, and results of probabilistic seismic hazard analysis (PSHA). The principal object of their concern is the PSHA map for Japan released by the Japan Headquarters for Earthquake Research Promotion (HERP), which is reproduced by Stein et al. (2011) as their Figure 1 and also here as our Figure 1. It shows the probability of exceedance (also referred to as the “hazard”) of the Japan Meteorological Agency (JMA) intensity 6–lower (JMA 6–) in Japan for the 30-year period beginning in January 2010. JMA 6– is an earthquake-damage intensity measure that is associated with fairly strong ground motion that can be damaging to well-built structures and is potentially destructive to poor construction (HERP, 2005, appendix 5). Reiterating Geller (2011, p. 408), Stein et al. (2011, p. 623) have this to say about Figure 1: The regions assessed as most dangerous are the zones of three hypothetical “scenario earthquakes” (Tokai, Tonankai, and Nankai; see map). However, since 1979, earthquakes that caused 10 or more fatalities in Japan actually occurred in places assigned a relatively low probability. This discrepancy—the latest in a string of negative results for the characteristic model and its cousin the seismic-gap model—strongly suggest that the hazard map and the methods used to produce it are flawed and should be discarded. Given the central role that PSHA now plays in seismic risk analysis, performance-based engineering, and design-basis ground motions, discarding PSHA would have important consequences. We are not persuaded by the arguments of Geller (2011) and Stein et al. (2011) for doing so because important misunderstandings about PSHA seem to have conditioned them. In the quotation above, for example, they have confused important differences between earthquake-occurrence observations and ground-motion hazard calculations.

Seismological Research Letters↗
USGS2012

ViscoSim Earthquake Simulator

Synthetic seismicity simulations have been explored by the Southern California Earthquake Center (SCEC) Earthquake Simulators Group in order to guide long‐term forecasting efforts related to the Unified California Earthquake Rupture Forecast ( Tullis et al. , 2012a ). In this study I describe the viscoelastic earthquake simulator (ViscoSim) of Pollitz, 2009 . Recapitulating to a large extent material previously presented by Pollitz (2009 , 2011 ) I describe its implementation of synthetic ruptures and how it differs from other simulators being used by the group.

Seismological Research Letters↗
USGS2012

Do aftershock probabilities decay with time?

So, do aftershock probabilities decay with time? Consider a thought experiment in which we are at the time of the mainshock and ask how many aftershocks will occur a day, week, month, year, or even a century from now. First we must decide how large a window to use around each point in time. Let's assume that, as we go further into the future, we are asking a less precise question. Perhaps a day from now means 1 day 10% of a day, a week from now means 1 week 10% of a week, and so on. If we ignore c because it is a small fraction of a day (e.g., Reasenberg and Jones, 1989, hereafter RJ89), and set p = 1 because it is usually close to 1 (its value in the original Omori law), then the rate of earthquakes (K=t) decays at 1=t. If the length of the windows being considered increases proportionally to t, then the number of earthquakes at any time from now is the same because the rate decrease is canceled by the increase in the window duration. Under these conditions we should never think "It's a bit late for this to be an aftershock."

Seismological Research Letters↗
USGS2013

The northwest trending north Boquerón Bay-Punta Montalva Fault Zone; A through going active fault system in southwestern Puerto Rico

The North Boquerón Bay–Punta Montalva fault zone has been mapped crossing the Lajas Valley in southwest Puerto Rico. Identification of the fault was based upon detailed analysis of geophysical data, satellite images, and field mapping. The fault zone consists of a series of Cretaceous bedrock faults that reactivated and deformed Miocene limestone and Quaternary alluvial fan sediments. The fault zone is seismically active (local magnitude greater than 5.0) with numerous locally felt earthquakes. Focal mechanism solutions suggest strain partitioning with predominantly east–west left-lateral displacements with small normal faults striking mostly toward the northeast. Northeast-trending fractures and normal faults can be found in intermittent streams that cut through the Quaternary alluvial fan deposits along the southern margin of the Lajas Valley, an east–west-trending 30-km-long fault-controlled depression. Areas of preferred erosion within the alluvial fan trend toward the west-northwest parallel to the onland projection of the North Boquerón Bay fault. The North Boquerón Bay fault aligns with the Punta Montalva fault southeast of the Lajas Valley. Both faults show strong southward tilting of Miocene strata. On the western end, the Northern Boquerón Bay fault is covered with flat-lying Holocene sediments, whereas at the southern end the Punta Montalva fault shows left-lateral displacement of stream drainage on the order of a few hundred meters.

Puerto Rico↗
USGS2013

Reverberations on the watery element: A significant tsunamigenic historical earthquake offshore the Carolina coast

We investigate an early nineteenth-century earthquake that has been previously cataloged but not previously investigated in detail or recognized as a significant event. The earthquake struck at approximately 4:30 a.m. LT on 8 January 1817 and was widely felt throughout the southeastern and mid-Atlantic United States. Around 11:00 a.m. the same day, an eyewitness described a 12-inch tide that rose abruptly and agitated boats on the Delaware River near Philadelphia. We show that the timing of this tide is consistent with the predicted travel time for a tsunami generated by an offshore earthquake 6–7 hours earlier. By combining constraints provided by the shaking intensity distribution and the tsunami observation, we conclude that the 1817 earthquake had a magnitude of low- to mid-M 7 and a location 800–1000 km offshore of South Carolina. Our results suggest that poorly understood offshore source zones might represent a previously unrecognized hazard to the southern and mid-Atlantic coast. Both observational and modeling results indicate that potential tsunami hazard within Delaware Bay merits consideration: the simple geometry of the bay appears to catch and focus tsunami waves. Our preferred location for the 1817 earthquake is along a diffuse northeast-trending zone defined by instrumentally recorded and historical earthquakes. The seismotectonic framework for this region remains enigmatic.

South Carolina↗
USGS2013

Seismicity associated with the May 2010 eruption of South Sarigan Seamount, Northern Mariana Islands

On 29 May 2010, at approximately 11:48 UTC, an undersea volcano south of Sarigan in the Northern Mariana Islands (Figs. 1 and 2) erupted sending a cloud of volcanic ash and water vapor to 40,000 feet (12 km; Washington Volcanic Ash Advisory Center). Bathymetric data ( Stern and Smoot, 1998 ; Embley et al. , 2007 ) indicate an undersea vent exists at approximately 16.582° N and 145.821° E or about 12 km southwest of Sarigan and about 30 km northeast of Anatahan (Fig. 3). The vent depth is estimated to be 184 m below sea level. Based on physical observations of water discoloration (Juan Camacho, personal comm., 2010) and satellite imagery, the eruption plume is attributed to this undersea seamount.

South Sarigan Seamount↗
USGS2013

Public release of the ISC-GEM Global Instrumental Earthquake Catalogue (1900-2009)

The International Seismological Centre–Global Earthquake Model (ISC–GEM) Global Instrumental Earthquake Catalogue (1900–2009) is the result of a special effort to substantially extend and improve currently existing global catalogs to serve the requirements of specific user groups who assess and model seismic hazard and risk. The data from the ISC–GEM Catalogue would be used worldwide yet will prove absolutely essential in those regions where a high seismicity level strongly correlates with a high population density.

Seismological Research Letters↗
USGS2013

The SCEC geodetic transient detection validation exercise

Over the past decade the number and size of continuously operating Global Positioning System (GPS) networks has grown substantially worldwide. A steadily increasing volume of freely available GPS measurements, combined with the application of new approaches for mining these data for signals of interest, has led to the identification of a large and diverse collection of time‐varying Earth processes. One phenomenon that has been observed is transient fault slip (also termed slow slip events or silent earthquakes) occurring over time spans of days to years (e.g., Linde et al., 1996; Hirose et al., 1999; Dragert et al., 2001; Miller et al., 2002; Kostoglodov et al., 2003; Douglas et al., 2005; Shelly et al., 2006; Ide et al., 2007; Lohman and McGuire, 2007; Schwartz and Rokosky, 2007; Szeliga et al., 2008). Such events have been widely observed in subduction zones but are also found in other tectonic settings (Linde et al., 1996; Cervelli et al., 2002; Murray and Segall, 2005; Lohman and McGuire, 2007; Montgomery‐Brown et al., 2009; Shelly, 2010; and references therein). Although retrospective study of slow‐slip events using geodetic observations is driving the formulation of new models for fault‐zone behavior and constitutive laws (e.g., Lapusta et al., 2000; Liu and Rice, 2007; Lapusta and Liu, 2009; Segall and Bradley, 2012a), much of the research on near‐real‐time detection and characterization of anomalous behaviors along fault zones has focused solely on the use of seismic tremor (e.g., Rogers and Dragert, 2003; Shelly et al., 2006; Ito et al., 2007).

California↗