USGS Science⌕ Search

SEARCH · USGS Science

Results for “Information Bulletin”

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 973 records · Page 54Linked to original sources

The potential impact of three-dimensional distributed slip models derived from real-time GNSS data on the performance of the ShakeAlert earthquake early warning system for slab interface earthquakes

The ShakeAlert® earthquake early warning (EEW) system is designed to warn users of imminent strong ground motion with sufficient time to take protective actions. ShakeAlert currently uses three algorithms to characterize the earthquake source. One estimates the location and magnitude using the first few seconds of the P wave and, while fast, tends to underestimate magnitude for M w 7.0+ earthquakes. A second estimates the location, orientation, length, and corresponding magnitude of a line source using observed peak ground acceleration and contributes primarily to M w 5.5+ earthquakes. The third infers earthquake magnitude from peak ground displacement measured using Global Navigation Satellite System (GNSS) data and offers nonsaturating magnitudes for M w 7.0+ earthquakes. Other EEW algorithms exist that infer temporally evolving spatially variable slip on a 3D fault surface from real‐time GNSS data, information that might enable more accurate and timely alerts in the event of large‐magnitude subduction interface earthquakes. Here, we evaluate the potential contribution of one such algorithm, BEFORES ( Minson et al. , 2014 ), to improve ShakeAlert performance through a simulated real‐time implementation of Bayesian evidence‐based fault orientation and real‐time earthquake slip (BEFORES) and other ShakeAlert algorithms using data for eight M w 7.6+ earthquakes. The test results demonstrate that BEFORES can produce well‐constrained and accurate magnitude estimates as soon as or sooner than other EEW algorithms, in turn enabling it to increase the amount of warning time users receive in many cases. However, with a modified Mercalli intensity (MMI) threshold of 3.5, which is commonly used for issuing alerts, BEFORES would tend to alert large geographic regions that did not feel strong shaking (MMI 6+). This effect can be mitigated using a higher alert threshold of MMI 4.5 without negative impact on the amount of warning time obtainable with BEFORES.

Bulletin of the Seismological Society of America↗

Salmon data mobilization

Despite substantial research and conservation efforts, many salmon populations are in decline. Globally, salmon research is not delivering effective decision support products to help managers apply research insights as informed management actions. Data Mobilization (DM) is a key step towards building the wider evidence base required to deliver accountable, reliable, and usable scientific advice to managers. Best practices for DM are being adopted throughout the scientific community but have not permeated deeply into the culture of salmon research and conservation. To address this, we present a strategy for Salmon Data Mobilization (SDM). This strategy defines three spheres of agencies and practitioners that must interact to advance SDM: (1) authoritative bodies that can create policies to support SDM uptake; (2) agencies that can promote, fund, and implement those policies; and (3) the broad salmon community of practice that can support uptake of SDM within focused interest groups. We sketch a future for SDM and propose functional changes required to improve it throughout the community.

North Pacific Anadromous Fish Commission Bulletin↗

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗

The USGS 2023 Conterminous U.S. time‐independent earthquake rupture forecast

We present the 2023 U.S. Geological Survey time‐independent earthquake rupture forecast for the conterminous United States, which gives authoritative estimates of the magnitude, location, and time‐averaged frequency of potentially damaging earthquakes throughout the region. In addition to updating virtually all model components, a major focus has been to provide a better representation of epistemic uncertainties. For example, we have improved the representation of multifault ruptures, both in terms of allowing more and less fault connectivity than in the previous models, and in sweeping over a broader range of viable models. An unprecedented level of diagnostic information has been provided for assessing the model, and the development was overseen by a 19‐member participatory review panel. Although we believe the new model embodies significant improvements and represents the best available science, we also discuss potential model limitations, including the applicability of logic tree branch weights with respect different types of hazard and risk metrics. Future improvements are also discussed, with deformation model enhancements being particularly worthy of pursuit, as well as better representation of sampling errors in the gridded seismicity components. We also plan to add time‐dependent components, and assess implications with a wider range of hazard and risk metrics.

Bulletin of the Seismological Society of America↗

Reevaluation of thermal maturity and stages of petroleum formation of the Mississippian Barnett Shale, Fort Worth Basin, Texas

New data including measured reflectance (% R o ), programmed open-system pyrolysis data, and kerogen elemental analyses obtained on the Mississippian Barnett Shale in the Fort Worth Basin, Texas, indicate that secondary-gas generation starts at 1.5% R o and not at the previously prescribed 1.1% R o . Oil-cracking kinetic parameters derived from pyrolysis experiments in the presence and absence of water indicate that secondary-gas generation will not occur at a thermal maturity as low as 1.1% R o and requires a minimum thermal maturity of 1.5% R o . This difference is especially important in using the Barnett Shale as an analog for evaluating other possible shale-gas plays. The new reflectance measurements have a good relationship with hydrogen indices (HIs) and compare well with other published data sets. However, the relationship does not compare well with the previously published data used to prescribe 1.1% R o as the start of secondary-gas generation in the Barnett Shale. This discrepancy is attributed to differences in measured % R o values and not attributed to differences in the HI values. Lack of publicly available information on the previously reported % R o values makes it difficult to ascertain the reason for their lower values. These lower % R o values also have impact on the previously prescribed relationship for estimating % R o from the temperature at maximum yield by programmed open-system pyrolysis ( T max ). As a result, the new data do not agree with a previously described relationship, and the considerable scatter makes the new relationship unreliable. However, the relationship between the HI and % R o has less scatter, which indicates that HI offers a better proxy in calculating % R o than T max for the Barnett Shale. Comparison of various programmed open-system pyrolysis methods (i.e., Rock-Eval II, Rock-Eval 6, Source Rock Analyzer, and Hawk) indicates that variations in HI are within ±10% of one another. An HI of at least 44 mg/g total organic carbon is prescribed as a more certain limit for the start of secondary-gas generation and prospective in situ gas-shale accumulations.

Texas↗

Near-real-time volcanic cloud monitoring: Insights into global explosive volcanic eruptive activity through analysis of Volcanic Ash Advisories

Understanding the location, intensity, and likely duration of volcanic hazards is key to reducing risk from volcanic eruptions. Here, we use a novel near-real-time dataset comprising Volcanic Ash Advisories (VAAs) issued over 10 years to investigate global rates and durations of explosive volcanic activity. The VAAs were collected from the nine Volcanic Ash Advisory Centres (VAACs) worldwide. Information extracted allowed analysis of the frequency and type of explosive behaviour, including analysis of key eruption source parameters (ESPs) such as volcanic cloud height and duration. The results reflect changes in the VAA reporting process, data sources, and volcanic activity through time. The data show an increase in the number of VAAs issued since 2015 that cannot be directly correlated to an increase in volcanic activity. Instead, many represent increased observations, including improved capability to detect low- to mid-level volcanic clouds (FL101–FL200, 3–6 km asl), by higher temporal, spatial, and spectral resolution satellite sensors. Comparison of ESP data extracted from the VAAs with the Mastin et al. (J Volcanol Geotherm Res 186:10–21, 2009a ) database shows that traditional assumptions used in the classification of volcanoes could be much simplified for operational use. The analysis highlights the VAA data as an exceptional resource documenting global volcanic activity on timescales that complement more widely used eruption datasets.

Bulletin of Volcanology↗

An adaptive management approach to controlling suburban deer

Distance sight-resight sampling has particular relevance to aerial surveys, in which height above ground and aircraft speed make the critical assumption of certain detection on the track-line unrealistic. Recent developments in distance sight-resight theory have left practical issues related to data collection as the major impediment to widespread use of distance sight-resight sampling in aerial surveys. We describe and evaluate a system to automatically log, store, and process data from distance sight-resight aerial surveys. The system has a primary digital system and a secondary audio system. The digital system comprises a sighting 'gun' and small keypad for each observer, a global positioning system (GPS) receiver, and an altimeter interface, all linked to a central laptop computer. The gun is used to record time and angle of declination from the horizon of sighted groups of animals as they pass the aircraft. The keypad is used to record information on species and group size. The altimeter interface records altitude from the aircraft's radar altimeter, and the GPS receiver provides location data at user-definable intervals. We wrote software to import data into a database and convert it into a form appropriate for distance sight-resight analyses. Perpendicular distance of sighted groups of animals from the flight path is calculated from altitude and angle of declination. Time, angle of declination, species, and group size of sightings by independent observers on the same side of the aircraft are used as criteria to classify single and duplicate sightings, allowing testing of the critical distance sampling assumption (g(0)=1) and estimation of g(0) if that assumption fails. An audio system comprising headphones for each observer and a 4-track tape recorder allows recording of data that are difficult to accommodate in the digital system and provides a backup to the digital system. We evaluated the system by conducting experimental surveys and reviewing results from actual surveys.

Wildlife Society Bulletin↗

Stratigraphy and conodont biostratigraphy of the uppermost Carboniferous and Lower Permian from the North American Midcontinent

Part A The uppermost Wabaunsee, Admire, Council Grove, and lower Chase Groups of Kansas, Oklahoma, and Nebraska are placed into three third-order depositional sequences: a Gzhelian late-highstand sequence set, a Council Grove transgressive and highstand sequence set, and a Chase transgressive sequence set. Sequences are defined by bounding maximum-exposure surfaces and are placed within the zone of exposure surfaces (typically, stacked paleosols). Conodonts are abundant in open-marine deposits and most marine units have a differing and characteristic faunal make-up. Eleven species are described as new: Streptognathodus binodosus , S. denticulatus , S. elongianus , S. florensis , S. lineatus , S. nevaensis , S. postconstrictus , S. postelongatus , S. robustus , S. translinearis , and S. trimilus . Part B Maximum-marine flooding levels and marine-condensed sections from uppermost Carboniferous and Lower Permian fourth-order (0.1-1 m.y.) depositional sequences of the North American midcontinent reveal a rich stratigraphic succession of species of Streptognathodus and Sweetognathus conodonts that permits high-precision correlation of the Carboniferous-Permian boundary as well as the Asselian-Sakmarian and Sakmarian-Artinskian boundaries. Eleven new species of Streptognathodus are described: Streptognathodus binodosus , S. denticulatus , S. elongianus , S. florensis , S. lineatus , S. nevaensis , S. postconstrictus , S. postelongatus , S. robustus , S. translinearis , and S. trimilus . Seventeen species are redescribed and clarified and include Streptognathodus alius , S. barskovi , S. bellus , S. brownvillensis , S. conjunctus , S. constrictus , S. elongatus , S. farmeri , S. flexuosus , S. fuchengensis , S. fusus , S. invaginatus , S. isolatus , S. longissimus , S. minacutus , S. nodulinearis , and S. wabaunsensis . The correlated level of the Carboniferous-Permian boundary is recognized in the lower part of the Red Eagle Depositional Sequence based on the introduction of Streptognathodus isolatus Chernykh, Ritter, and Wardlaw; Streptognathodus minacutus Barskov and Reimers; Streptognathodus invaginatus Reshetkova and Chernykh; Streptognathodus fuchengensis Zhao; and Streptognathodus nodulinearis Reshetkova and Chernykh. The correlated Carboniferous-Permian boundary occurs in the depositional sequence that represents the maximum-marine highstand of the Council Grove Composite Third Order Sequence. This level represents a significant marine-flooding event that should be correlatable in numerous shelfal sections throughout the world. Although the Asselian-Sakmarian boundary has not been rigorously defined, Sweetognathus merrilli has been informally utilized as a Sakmarian indicator. Due to the ecologically controlled distribution of species of Sweetognathus , we prefer to use a species of Streptognathodus as a defining species. We propose that Streptognathodus barskovi (Kozur) Reshetkova be considered as a potentially defining or ancillary defining species for the Sakmarian Stage. In the North American midcontinent, Streptognathodus barskovi appears in the same depositional sequence with Sweetognathus merrilli in the Eiss (Lower Bader) Depositional Sequence. Historically, Sweetognathus whitei has been used to mark the Sakmarian-Artinskian boundary. In our succession Sweetognathus whitei and Streptognathodus florensis appear in the basal part of the Barneston Depositional Sequence. We suggest that Streptognathodus florensis be further investigated as a possible defining or ancillary defining taxon for the base of the Artinskian Stage. This depositional sequence also forms the maximum-marine highstand of the Chase Third-Order Composite Depositional Sequence suggesting that this level is a significant marine-flooding event that should be widely traceable in numerous shelfal sections.

Kansas;Nebraska;Oklahoma↗

Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina

Population density is an important component of wildlife management decisions, but can be difficult to estimate directly for an itinerant, wide‐ranging species such as the American black bear ( Ursus americanus ). In South Carolina, USA, where there has been growth in black bear populations and bear–human‐conflict reports during the past several decades, managers need robust estimates of population size to inform management strategies. We used maximum‐likelihood capture–recapture models, using hair snares to collect DNA samples, to estimate density and abundance for a harvested population of black bear in northwestern South Carolina during 2013 to 2014. Models were tested in a spatially explicit framework using the secr package in Program R. Black bear density was estimated at 0.133 bears/km 2 (SE = 0.034) in 2013 and 0.179 bears/km 2 (SE = 0.043) in 2014. Black bear abundance in our study area was estimated to be 586 bears (SE = 95) in 2013 and 680 bears (SE = 128) in 2014, which are 2–3‐fold lower than previous estimates. We suggest that these estimates be considered a baseline for state biologists to employ in the population's management and in developing future harvest‐regulation strategies. Overall our study highlighted the potential for model choice to influence density estimates, and we concluded that spatially explicit models were appropriate for this study because geographic closure could not be assumed.

south Carolina↗

From field station to forecast: Managing data at the Alaska Volcano Observatory

The Alaska Volcano Observatory (AVO) uses multidisciplinary data to monitor and study dozens of active and potentially active volcanoes. Here, we provide an overview of internally and externally generated data types, tools and resources used in their management, and challenges faced. Data sources include the following: (1) a multiparameter (seismic, infrasound, GNSS, web cameras) ground-based monitoring network that spans 3000 km and transmits data in real time; (2) a variety of satellite-borne sensors that provide information about surface change and volcanic emissions; (3) geologic and gas field campaigns; and (4) other external data products that provide situation awareness. Each data type requires distinct acquisition, processing, storage, visualization, and archiving approaches. AVO uses a variety of externally and internally developed tools to handle individual data types as well as multidisciplinary volcanological data. A primary tool is the Geologic Database of Information on Volcanoes in Alaska (GeoDIVA), which stores detailed, searchable information on more than 140 volcanoes and over 1000 eruptions and unrest events, including images, eruption descriptions, and geologic station and sample data, metadata, and analyses. It interacts with other internal tools that store monitoring reports and other operational records. Additional data management resources used by AVO assist with alarms and alerts, state-of-health monitoring, and multiparameter visualization. Requirements for 24/7 accessibility, the ever-expanding portfolio of data, and transitioning new tools from development to operations are all challenges faced by AVO and other volcano observatories. AVO strives to meet FAIR data practices and ensure that data are available to national and international community efforts using external repositories as well as those hosted by AVO and its parent institutions.

Alaska↗

FLUXNET-CH4 synthesis activity: Objectives, observations, and future directions

This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH 4 ) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH 4 flux measurements globally, initial results comparing CH 4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH 4 fluxes across sites ranged from −0.2 ± 0.02 g C m –2 yr –1 for an upland forest site to 114.9 ± 13.4 g C m –2 yr –1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m –2 yr –1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH 4 flux across wetland sites globally. Water table position was positively correlated with annual CH 4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH 4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH 4 estimates due to gap-filling and random errors were on average ±1.6 g C m –2 yr –1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH 4 flux database, the controls on ecosystem CH 4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH 4 emissions.

Bulletin of the American Meteorological Society↗

A time-dependent probabilistic seismic-hazard model for California

For the purpose of sensitivity testing and illuminating nonconsensus components of time-dependent models, the California Department of Conservation, Division of Mines and Geology (CDMG) has assembled a time-dependent version of its statewide probabilistic seismic hazard (PSH) model for California. The model incorporates available consensus information from within the earth-science community, except for a few faults or fault segments where consensus information is not available. For these latter faults, published information has been incorporated into the model. As in the 1996 CDMG/U.S. Geological Survey (USGS) model, the time-dependent models incorporate three multisegment ruptures: a 1906, an 1857, and a southern San Andreas earthquake. Sensitivity tests are presented to show the effect on hazard and expected damage estimates of (1) intrinsic (aleatory) sigma, (2) multisegment (cascade) vs. independent segment (no cascade) ruptures, and (3) time-dependence vs. time-independence. Results indicate that (1) differences in hazard and expected damage estimates between time-dependent and independent models increase with decreasing intrinsic sigma, (2) differences in hazard and expected damage estimates between full cascading and not cascading are insensitive to intrinsic sigma, (3) differences in hazard increase with increasing return period (decreasing probability of occurrence), and (4) differences in moment-rate budgets increase with decreasing intrinsic sigma and with the degree of cascading, but are within the expected uncertainty in PSH time-dependent modeling and do not always significantly affect hazard and expected damage estimates.

California↗

Using Landsat imagery to detect, monitor, and project net landscape change

Detailed landscape information is a necessary component to bird habitat conservation planning. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has been providing information on the Earth’s surface for over 40 years via the continuous series of Landsat satellites. In addition to operating, processing, and disseminating satellite images, EROS is the home to nationwide and global landscape mapping, monitoring, and projection products, including: National Land Cover Database (NLCD) – the definitive land cover dataset for the U.S., with updates occurring at five-year intervals; Global Land Cover Monitoring – producing 30m resolution global land cover; LANDFIRE – Landscape Fire and Resource Management Planning Tools–EROS is a partner in this joint program between U.S. Department of Agriculture and Department of Interior that produces consistent, comprehensive, geospatial data and databases that describe vegetation, wildland fuel, and fire regimes across the U.S.; Land Cover Trends – a landscape monitoring and assessment effort to understand the rates, trends, causes, and consequences of contemporary U.S. land use and land cover change; and Land Use and Land Cover (LULC) Modeling – a project extending contemporary databases of landscape change forward and backward in time through moderate-resolution land cover projections.

All Bird Bulletin↗

Survival and harvest-related mortality of white-tailed deer in Massachusetts

We monitored 142 radiocollared adult (≥1.0 yr old) white-tailed deer ( Odocoileus virginianus ) in 3 study areas of Massachusetts, USA, to estimate annual survival and mortality due to legal hunting. We then applied these rates to deer harvest information to estimate deer population trends over time, and compared these to trends derived solely from harvest data estimates. Estimated adult female survival rates were similar (0.82–0.86), and uniformly high, across 3 management zones in Massachusetts that differed in landscape composition, human density, and harvest regulations. Legal hunting accounted for 16–29% of all adult female mortality. Estimated adult male survival rates varied from 0.55 to 0.79, and legal hunting accounted for 40–75% of all mortality. Use of composite hunting mortality rates produced realistic estimates for adult deer populations in 2 zones, but not for the third, where estimation was hindered by regulatory restrictions on antlerless deer harvest. In addition, the population estimates we calculated were generally higher than those derived from population reconstruction, likely due to relatively low harvest pressure. Legal harvest may not be the dominant form of deer mortality in developed landscapes; thus, estimates of populations or trends that rely solely on harvest data will likely be underestimates.

Massachusetts↗

Evaluation of a waistband for attaching external radiotransmitters to anurans

Radiotelemetry provides fine-scale temporal and spatial information about an individual's movements and habitat use; however, its use for monitoring amphibians has been restricted by transmitter mass and lack of suitable attachment techniques. We describe a novel waistband for attaching external radiotransmitters to anurans and evaluate the percentages of resulting abrasions, lacerations, and shed transmitters. We used radiotelemetry to monitor movements and habitat use of wood frogs ( Lithobates sylvaticus ) in 2006 and 2011–2013 in Maine, USA; American toads ( Anaxyrus americanus ) in 2012 in North Carolina, USA; and, wood frogs, southern leopard frogs ( L. sphenocephalus ), and green frogs ( L. clamitans ) in 2012 in South Carolina, USA. We monitored 172 anurans for 1–365 days (56.4 ± 59.4) in a single year and 1–691 days (60.5 ± 94.1) across years. Our waistband resulted in an injury percentage comparable to 7 alternative anuran waistband attachment techniques; however, 12.5% fewer anurans shed their waistband when attached with our technique. Waistband retention facilitates longer monitoring periods and, thus, provides a greater quantity of data per radiotagged individual.

Wildlife Society Bulletin↗

Structural geologic interpretations from radar imagery

Certain structural geologic features may be more readily recognized on sidelooking airborne radar (SLAR) images than on conventional aerial photographs, other remote sensor imagery, or by ground observations. SLAR systems look obliquely to one or both sides and their images resemble aerial photographs taken at low sun angle with the sun directly behind the camera. They differ from air photos in geometry, resolution, and information content. Radar operates at much lower frequencies than the human eye, camera, or infrared sensors, and thus "sees" differently. The lower frequency enables it to penetrate most clouds and some precipitation, haze, dust, and some vegetation. Radar provides its own illumination, which can be closely controlled in intensity and frequency. It is narrow band, or essentially monochromatic. Low relief and subdued features are accentuated when viewed from the proper direction. Runs over the same area in significantly different directions (more than 45° from each other), show that images taken in one direction may emphasize features that are not emphasized on those taken in the other direction; optimum direction is determined by those features which need to be emphasized for study purposes. Lineaments interpreted as faults stand out on radar imagery of central and western Nevada; folded sedimentary rocks cut by faults can be clearly seen on radar imagery of northern Alabama. In these areas, certain structural and stratigraphic features are more pronounced on radar images than on conventional photographs; thus radar imagery materially aids structural interpretation.

Alabama;Nevada↗

A revised ground-motion and intensity interpolation scheme for shakemap

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

Bulletin of the Seismological Society of America↗

Real-time earthquake detection and alerting behavior of PLUM ground-motion-based early warning in the United States

We examine the real‐time earthquake detection and alerting behavior of the Propagation of Local Undamped Motion (PLUM) earthquake early warning (EEW) algorithm and compare PLUM’s performance with the real‐time performance of the current source‐characterization‐based ShakeAlert System. In the United States (U.S.), PLUM uses a two‐station approach to detect earthquakes. Once a detection is confirmed, observed modified Mercalli intensity (MMI) distributions are forecast onto a regular grid, in which the preferred alert regions are grid cells with MMI 4.0+ forecasts. Although locations of dense station coverage allow PLUM to detect small ( M < 4.5) earthquakes typically not considered for EEW in the U.S., a PLUM detection on a small earthquake does not always generate an alert. This is because PLUM alerts are determined by current shaking distributions. If the MMI 4.0+ shaking subsides prior to detection confirmation by shaking at a second neighboring station, the prior MMI 4.0+ information will not be in the alert forecasts. Of the 432 M 3.0+ U.S. West Coast earthquakes in 2021, 33 produced ground motions large enough to be detected by PLUM. Twenty‐four generated MMI 4.0+ PLUM alerts, whereas ShakeAlert issued public EEW alerts for 13 of these earthquakes. We compare PLUM and ShakeAlert alert regions with ShakeMap and “Did You Feel It?” intensity distributions. Because PLUM alert regions surround stations observed to have strong ground motions (regardless of earthquake magnitude), PLUM alerts reliably include locations that experience significant shaking. This is not necessarily the case for ShakeAlert alert regions when there are large errors in magnitude or epicenter estimates. For two of the largest earthquakes in our real‐time dataset, the M 6.0 Antelope Valley and M 5.1 Petrolia earthquakes, the inclusion of PLUM would have improved real‐time ShakeAlert performance. Our results indicate that incorporation of PLUM into ShakeAlert will improve the robustness of the EEW system.

California, Oregon, Washington↗