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

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At least 559 records · Page 31Linked to original sources
USGS2001

Seismic hazard in Hawaii: High rate of large earthquakes and probabilistics ground-motion maps

The seismic hazard and earthquake occurrence rates in Hawaii are locally as high as that near the most hazardous faults elsewhere in the United States. We have generated maps of peak ground acceleration (PGA) and spectral acceleration (SA) (at 0.2, 0.3 and 1.0 sec, 5% critical damping) at 2% and 10% exceedance probabilities in 50 years. The highest hazard is on the south side of Hawaii Island, as indicated by the MI 7.0, MS 7.2, and MI 7.9 earthquakes, which occurred there since 1868. Probabilistic values of horizontal PGA (2% in 50 years) on Hawaii's south coast exceed 1.75g. Because some large earthquake aftershock zones and the geometry of flank blocks slipping on subhorizontal decollement faults are known, we use a combination of spatially uniform sources in active flank blocks and smoothed seismicity in other areas to model seismicity. Rates of earthquakes are derived from magnitude distributions of the modem (1959-1997) catalog of the Hawaiian Volcano Observatory's seismic network supplemented by the historic (1868-1959) catalog. Modern magnitudes are ML measured on a Wood-Anderson seismograph or MS. Historic magnitudes may add ML measured on a Milne-Shaw or Bosch-Omori seismograph or MI derived from calibrated areas of MM intensities. Active flank areas, which by far account for the highest hazard, are characterized by distributions with b slopes of about 1.0 below M 5.0 and about 0.6 above M 5.0. The kinked distribution means that large earthquake rates would be grossly under-estimated by extrapolating small earthquake rates, and that longer catalogs are essential for estimating or verifying the rates of large earthquakes. Flank earthquakes thus follow a semicharacteristic model, which is a combination of background seismicity and an excess number of large earthquakes. Flank earthquakes are geometrically confined to rupture zones on the volcano flanks by barriers such as rift zones and the seaward edge of the volcano, which may be expressed by a magnitude distribution similar to that including characteristic earthquakes. The island chain northwest of Hawaii Island is seismically and volcanically much less active. We model its seismic hazard with a combination of a linearly decaying ramp fit to the cataloged seismicity and spatially smoothed seismicity with a smoothing half-width of 10 km. We use a combination of up to four attenuation relations for each map because for either PGA or SA, there is no single relation that represents ground motion for all distance and magnitude ranges. Great slumps and landslides visible on the ocean floor correspond to catastrophes with effective energy magnitudes ME above 8.0. A crude estimate of their frequency suggests that the probabilistic earthquake hazard is at least an order of magnitude higher for flank earthquakes than that from submarine slumps.

Bulletin of the Seismological Society of America↗
USGS2000

Earthquake stress triggers, stress shadows, and seismic hazard

Many aspects of earthquake mechanics remain an enigma at the beginning of the twenty-first century. One potential bright spot is the realization that simple calculations of stress changes may explain some earthquake interactions, just as previous and ongoing studies of stress changes have begun to explain human- induced seismicity. This paper, which is an update of Harris1, reviews many published works and presents a compilation of quantitative earthquake-interaction studies from a stress change perspective. This synthesis supplies some clues about certain aspects of earthquake mechanics. It also demonstrates that much work remains to be done before we have a complete story of how earthquakes work.

Current Science↗
USGS2020

Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard forecasts: Hawaii tectonic earthquakes and volcanic eruptions

The selection and weighting of ground‐motion models (GMMs) introduces a significant source of uncertainty in U.S. Geological Survey (USGS) National Seismic Hazard Modeling Project (NSHMP) forecasts. In this study, we evaluate 18 candidate GMMs using instrumental ground‐motion observations of horizontal peak ground acceleration (PGA) and 5%‐damped pseudospectral acceleration (0.02–10 s) for tectonic earthquakes and volcanic eruptions, to inform logic‐tree weights for the update of the USGS seismic hazard model for Hawaii. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function (PDF), mean and standard deviations σ "> σ ⁠ , of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Hawaii seismic hazard model logic trees. The total residual PDF approach provides additional information by preserving GMM over‐ and underprediction across a broad spectrum of periods that is not available from a single value LLH score. We apply these GMM evaluation methods to two different data sets: (1) a database of instrumental ground motions from historic earthquakes in Hawaii from 1973 to 2007 ( ⁠ M w "> M w 4–7.3) and (2) available ground motions from recent earthquakes ( ⁠ M w "> M w 4–6.9) associated with 2018 Kilauea eruptions. The 2018 Kilauea sequence contains both volcanic eruptions and tectonic earthquakes allowing for statistically significant GMM comparisons of the two event classes. The Kilauea ground observations provide an independent data set allowing us to evaluate the predictive power of GMMs implemented in the new USGS nshmp‐haz software system. We evaluate GMM performance as a function of earthquake depth and we demonstrate that short‐period volcanic eruption ground motions are not well predicted by any candidate GMMs. Nine of the initial 18 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the update of the Hawaii seismic hazard model. A weighted mean of four top performing GMMs in this study (NGAsubslab, NGAsubinter, ASK14, A10) is 50% lower for PGA than for GMMS used in the previous USGS seismic hazard model for Hawaii.

Hawaii↗
USGS2018

A physics-based earthquake simulator replicates seismic hazard statistics across California

Seismic hazard models are important for society, feeding into building codes and hazard mitigation efforts. These models, however, rest on many uncertain assumptions and are difficult to test observationally because of the long recurrence times of large earthquakes. Physics-based earthquake simulators offer a potentially helpful tool, but they face a vast range of fundamental scientific uncertainties. We compare a physics-based earthquake simulator against the latest seismic hazard model for California. Using only uniform parameters in the simulator, we find strikingly good agreement of the long-term shaking hazard compared with the California model. This ability to replicate statistically based seismic hazard estimates by a physics-based model cross-validates standard methods and provides a new alternative approach needing fewer inputs and assumptions for estimating hazard.

California↗
USGS2006

Urban seismic hazard mapping for Memphis, Shelby County, Tennessee

Earthquakes cannot be predicted, but scientists can forecast how strongly the ground is likely to shake as a result of an earthquake. Seismic hazard maps provide one way of conveying such forecasts. The U.S. Geological Survey (USGS), which produces seismic hazard maps for the Nation, is now engaged in developing more detailed maps for vulnerable urban areas. The first set of these maps is now available for Memphis, Tennessee.

Fact Sheet↗
USGS2013

Variability of displacement at a point: Implications for earthquake‐size distribution and rupture hazard on faults

To investigate the nature of earthquake‐magnitude distributions on faults, we compare the interevent variability of surface displacement at a point on a fault from a composite global data set of paleoseismic observations with the variability expected from two prevailing magnitude–frequency distributions: the truncated‐exponential model and the characteristic‐earthquake model. We use forward modeling to predict the coefficient of variation (CV) for the alternative earthquake distributions, incorporating factors that would effect observations of displacement at a site. The characteristic‐earthquake model (with a characteristic‐magnitude range of ±0.25) produces CV values consistent with the data (CV∼0.5) only if the variability for a given earthquake magnitude is small. This condition implies that rupture patterns on a fault are stable, in keeping with the concept behind the model. This constraint also bears upon fault‐rupture hazard analysis, which, for lack of point‐specific information, has used global scaling relations to infer variability in average displacement for a given‐size earthquake. Exponential distributions of earthquakes (from M 5 to the maximum magnitude) give rise to CV values that are significantly larger than the empirical constraint. A version of the model truncated at M 7, however, yields values consistent with a larger CV (∼0.6) determined for small‐displacement sites. Although this result allows for a difference in the magnitude distribution of smaller surface‐rupturing earthquakes, it may reflect, in part, less stability in the displacement profile of smaller ruptures and/or the tails of larger ruptures.

Bulletin of the Seismological Society of America↗
USGS2012

ShakeMap Atlas 2.0: an improved suite of recent historical earthquake ShakeMaps for global hazard analyses and loss model calibration

We introduce the second version of the U.S. Geological Survey ShakeMap Atlas, which is an openly-available compilation of nearly 8,000 ShakeMaps of the most significant global earthquakes between 1973 and 2011. This revision of the Atlas includes: (1) a new version of the ShakeMap software that improves data usage and uncertainty estimations; (2) an updated earthquake source catalogue that includes regional locations and finite fault models; (3) a refined strategy to select prediction and conversion equations based on a new seismotectonic regionalization scheme; and (4) vastly more macroseismic intensity and ground-motion data from regional agencies All these changes make the new Atlas a self-consistent, calibrated ShakeMap catalogue that constitutes an invaluable resource for investigating near-source strong ground-motion, as well as for seismic hazard, scenario, risk, and loss-model development. To this end, the Atlas will provide a hazard base layer for PAGER loss calibration and for the Earthquake Consequences Database within the Global Earthquake Model initiative.

Conference Paper↗
USGS2025

Capturing the uncertainty of seismicity observations in earthquake rate estimates: Implications for probabilistic seismic hazard analysis and the USGS National Seismic Hazard Model

The rate of earthquakes in a region is a fundamental input to Probabilistic Seismic Hazard Analysis. We present a Monte Carlo method for computing that rate from seismicity catalogs while including a range of data and analysis uncertainties. This method is applied to regions for which the b value is assumed to be spatially invariant. Each region is broken down into epochs for which each epoch is estimated to have a uniform magnitude of completeness ( ⁠⁠ M c ). The distribution of earthquake rates for M ≥ M c is determined for each epoch by considering the Poisson likelihood of rates given the number of observed earthquakes with M ≥ M c ⁠ . We use a Monte Carlo process to include the uncertainty in b , ⁠ M c , and individual event magnitudes. The result for each epoch is the joint distribution of the Poisson rate of earthquakes with magnitudes larger than the minimum value used to calculate hazard ( ⁠⁠ M 1 ) and the Gutenberg–Richter b values, which control the extrapolation to other magnitudes. The rate for each region is either the duration‐weighted average over the epochs or, to better capture temporal variations, we also consider mixture models. The mixture models also provide an avenue to allow temporal variations in b values. To implement this joint distribution in a logic tree, we use the mean and 95% confidence branches, each of which is parameterized with an M ≥ M 1 rate and b value. We explore different ways of defining those branches, as well as non‐Gutenberg–Richter branches, and their impact on hazard estimates. The mean hazard, but not the fractiles, is robust with respect to these choices. To illustrate these new methods, we use synthetic data and catalogs from recent U.S. Geological Survey National Seismic Hazard Models for the Central and Eastern United States and for Puerto Rico and the U.S. Virgin Islands.

central and eastern United States, Puerto Rico, U.↗
USGS2008

United States National Seismic Hazard Maps

The U.S. Geological Survey?s maps of earthquake shaking hazards provide information essential to creating and updating the seismic design provisions of building codes and insurance rates used in the United States. Periodic revisions of these maps incorporate the results of new research. Buildings, bridges, highways, and utilities built to meet modern seismic design provisions are better able to withstand earthquakes, not only saving lives but also enabling critical activities to continue with less disruption. These maps can also help people assess the hazard to their homes or places of work and can also inform insurance rates.

Fact Sheet↗
USGS2002

East Meets West: An Earthquake in India Helps Hazard Assessment in the Central United States

Although geographically distant, the State of Gujarat in India bears many geological similarities to the Mississippi Valley in the Central United States. The Mississippi Valley contains the New Madrid seismic zone that, during the winter of 1811-1812, produced the three largest historical earthquakes ever in the continental United States and remains the most seismically active region east of the Rocky Mountains. Large damaging earthquakes are rare in ‘intraplate’ settings like New Madrid and Gujarat, far from the boundaries of the world’s great tectonic plates. Long-lasting evidence left by these earthquakes is subtle (fig. 1). Thus, each intraplate earthquake provides unique opportunities to make huge advances in our ability to assess and understand the hazards posed by such events.

Fact Sheet↗
USGS2015

Geotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks

This article summarizes the geotechnical effects of the 25 April 2015 M 7.8 Gorkha, Nepal, earthquake and aftershocks, as documented by a reconnaissance team that undertook a broad engineering and scientific assessment of the damage and collected perishable data for future analysis. Brief descriptions are provided of ground shaking, surface fault rupture, landsliding, soil failure, and infrastructure performance. The goal of this reconnaissance effort, led by Geotechnical Extreme Events Reconnaissance, is to learn from earthquakes and mitigate hazards in future earthquakes.

Gorkha↗
USGS2016

2016 one-year seismic hazard forecast for the Central and Eastern United States from induced and natural earthquakes

The U.S. Geological Survey (USGS) has produced a 1-year seismic hazard forecast for 2016 for the Central and Eastern United States (CEUS) that includes contributions from both induced and natural earthquakes. The model assumes that earthquake rates calculated from several different time windows will remain relatively stationary and can be used to forecast earthquake hazard and damage intensity for the year 2016. This assessment is the first step in developing an operational earthquake forecast for the CEUS, and the analysis could be revised with updated seismicity and model parameters. Consensus input models consider alternative earthquake catalog durations, smoothing parameters, maximum magnitudes, and ground motion estimates, and represent uncertainties in earthquake occurrence and diversity of opinion in the science community. Ground shaking seismic hazard for 1-percent probability of exceedance in 1 year reaches 0.6 g (as a fraction of standard gravity [g]) in northern Oklahoma and southern Kansas, and about 0.2 g in the Raton Basin of Colorado and New Mexico, in central Arkansas, and in north-central Texas near Dallas. Near some areas of active induced earthquakes, hazard is higher than in the 2014 USGS National Seismic Hazard Model (NHSM) by more than a factor of 3; the 2014 NHSM did not consider induced earthquakes. In some areas, previously observed induced earthquakes have stopped, so the seismic hazard reverts back to the 2014 NSHM. Increased seismic activity, whether defined as induced or natural, produces high hazard. Conversion of ground shaking to seismic intensity indicates that some places in Oklahoma, Kansas, Colorado, New Mexico, Texas, and Arkansas may experience damage if the induced seismicity continues unabated. The chance of having Modified Mercalli Intensity (MMI) VI or greater (damaging earthquake shaking) is 5–12 percent per year in north-central Oklahoma and southern Kansas, similar to the chance of damage caused by natural earthquakes at sites in parts of California.

Open-File Report↗
USGS2023

ShakeMap Atlas 4.0 and AtlasCat: An archive of the recent and the historical earthquake ShakeMaps, and impacts for global hazard analyses and loss model calibration

Archival earthquake studies often focus on event and source characteristics for use in earthquake catalogs, seismotectonic understanding, and ground‐motion studies—many of these targeting better constraints for probabilistic seismic‐hazard analyses. The ShakeMap Atlas, in contrast, focuses on spatial distribution of shaking for the historical events, providing the best constraints at all locations that experienced significant shaking for each event, facilitating analyses of human experience, damage, and induced hazards (ground failure). The aim of the Atlas is to gain a general understanding and depiction of the shaking distribution for a suite of canonical earthquakes, and, coupled with loss data for each event, to provide a basis for earthquake loss model calibration, among other uses. Although the initial motivation for developing the ShakeMap Atlas was calibrating the U.S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response system, over time, the Atlas has proved to be a useful tool for its users, and, as such, its scope has been vastly expanded in this newest version. The fourth version of the USGS ShakeMap Atlas is an openly available compilation of over 14,000 ShakeMaps of significant global earthquakes between 1900 and 2020. This revision includes: (1) the latest version of the ShakeMap software that provides refined uncertainty estimations and improved methods to combine macroseismic observations with updated ground‐motion models; (2) an updated earthquake source catalog; (3) a refined strategy to select suites of prediction and conversion equations based on a new seismotectonic regionalization scheme; and (4) expanded macroseismic intensity and ground‐motion datasets. We also tabulate reported economic losses and fatalities for Atlas events where such data are openly available. These changes make the new ShakeMap Atlas a self‐consistent, calibrated catalog invaluable for investigating near‐source ground motions, as well as seismic hazard, scenario, risk, and loss‐model development and testing.

California↗
USGS2015

Assessment of existing and potential landslide hazards resulting from the April 25, 2015 Gorkha, Nepal earthquake sequence

Introduction On April 25, 2015, a large ( M 7.8) earthquake shook much of central Nepal and was followed by a series of M >6 aftershocks, including a M 7.3 event on May 12, 2015. This earthquake and aftershocks, referred to as the “Gorkha earthquake sequence,” caused thousands of fatalities, damaged and destroyed entire villages, and displaced millions of residents. The earthquakes also triggered thousands of landslides in the exceedingly steep topography of Nepal; these landslides were responsible for hundreds of fatalities, and blocked vital roads and trails to affected villages (fig. 1). Landslides caused by the Gorkha earthquake sequence continue to pose both immediate and long-term hazards to villages and infrastructure within the affected region. Some landslides blocked rivers and thus created another potential concern for villages located downstream. With the support of the United States Agency for International Development (USAID), Office of Foreign Disaster Assistance (OFDA), and in collaboration with earthquake-hazard organizations from both the United States (for example, U.S. National Science Foundation Geoengineering Extreme Event Reconnaissance [GEER] Team) and Nepal (International Centre for Integrated Mountain Development [ICIMOD]), the U.S. Geological Survey (USGS) responded to this crisis by providing landslide-hazard expertise to Nepalese agencies and affected villages. In addition to collaborating with an international group of remote-sensing scientists to document the spatial distribution of landsliding in the first few weeks following the earthquake, the USGS conducted in-country landslide hazard assessments for 10 days beginning May 24, 2015. Much of the information obtained by the USGS during their time in Nepal was conveyed directly to affected villages and government agencies as opportunities arose. Upon return to the United States, data organization, interpretation, and synthesis began immediately to provide a rapid assessment of landslide hazards for use by Nepalese agencies during the 2015 summer monsoon (typically occurring from June through September). This report provides a detailed account of assessments performed in May and June 2015 and focuses on valley-blocking landslides because they have the potential to pose considerable hazard to many villages in Nepal. First, we provide a seismological background of Nepal and then detail the methods used for both external and in-country data collection and interpretation. Our results consist of an overview of landsliding extent, a characterization of all valley-blocking landslides identified during our work, and a description of video resources that provide high resolution coverage of approximately 1,000 kilometers (km) of river valleys and surrounding terrain affected by the Gorkha earthquake sequence. This is followed by a description of site-specific landslide-hazard assessments conducted while in Nepal and includes detailed descriptions of five noteworthy case studies. Finally, we assess the expectation for additional landslide hazards during the 2015 summer monsoon season.

Open-File Report↗
USGS2016

Introduction to the special issue on the 25 April 2015 Mw 7.8 Gorkha(Nepal) earthquake

On April 25, 2015, a moment magnitude (M w ) 7.8 earthquake struck central Nepal, breaking a section of the broader Himalayan Front that had been largely quiescent in moderate-to-large earthquakes for much of the modern seismological era. Ground shaking associated with the event resulted in a broad distribution of triggered avalanches and landslides. The ensuing aftershock sequence was punctuated by a Mw 7.3 event 17 days after the mainshock. The combined effects of these earthquakes and secondary hazards have led to the Gorkha earthquake becoming the worst natural disaster in Nepal since the 1934 Nepal-Bihar earthquake, causing close to 9000 deaths and severely injuring over 21,000 people ( OCHA, 2015 ). Despite the devastating effects of this earthquake, the convergent margin that hosted it is thought to be capable of much larger ruptures—perhaps as large as Mw 9 ( Feldl and Bilham, 2006 ). The 2015 Gorkha rupture lies just to the west of the 1934 M 8.0–8.4 event ( Sapkota et al., 2013; Bollinger et al., 2014 ). Unlike the 1934 event, which has been documented in paleoseismic trenches along the Himalayan Front (e.g., Sapkota et al., 2013 ), and other large ruptures along the arc (e.g., Lavé et al., 2005; Kumar et al., 2006 ), the 2015 event did not rupture to the surface (e.g., Galetzka et al., 2015 ). As a result, some researchers have suggested that the Gorkha earthquake was not as large, or as damaging, as might have been expected based on our (albeit limited) understanding of historic earthquakes, seismic hazard and risk (e.g., Bilham, 2015; Hough, 2015 ). Important questions surrounding the earthquake and its regional setting thus arise. What were the detailed characteristics of the rupture and the aftershock sequence, and what is the relationship between mainshock slip and subsequent seismicity? Why did this event not rupture to the surface? Was damage less than should have been expected; and if so, why? What role did path effects, such as basin amplification, play? Do details of the earthquake sequence allow us to better understand regional seismotectonics, and in turn, future risk? Discussion of these and other issues has been ongoing since the earthquake; a large body of literature already exists that characterizes details of the earthquake sequence and its effects. This special issue attempts to gather a wide variety of detailed studies that wholly characterize this event to a degree that has not yet been possible. The studies herein provide an improved understanding of the Gorkha earthquake, its impact on the region, and its place in the broader seismotectonic history of the Himalayan Front.

Gorkha↗
USGS2008

Liquefaction hazard maps for three earthquake scenarios for the communities of San Jose, Campbell, Cupertino, Los Altos, Los Gatos, Milpitas, Mountain View, Palo Alto, Santa Clara, Saratoga, and Sunnyvale, Northern Santa Clara County, California

Maps showing the probability of surface manifestations of liquefaction in the northern Santa Clara Valley were prepared with liquefaction probability curves. The area includes the communities of San Jose, Campbell, Cupertino, Los Altos, Los Gatos Milpitas, Mountain View, Palo Alto, Santa Clara, Saratoga, and Sunnyvale. The probability curves were based on complementary cumulative frequency distributions of the liquefaction potential index (LPI) for surficial geologic units in the study area. LPI values were computed with extensive cone penetration test soundings. Maps were developed for three earthquake scenarios, an M7.8 on the San Andreas Fault comparable to the 1906 event, an M6.7 on the Hayward Fault comparable to the 1868 event, and an M6.9 on the Calaveras Fault. Ground motions were estimated with the Boore and Atkinson (2008) attenuation relation. Liquefaction is predicted for all three events in young Holocene levee deposits along the major creeks. Liquefaction probabilities are highest for the M7.8 earthquake, ranging from 0.33 to 0.37 if a 1.5-m deep water table is assumed, and 0.10 to 0.14 if a 5-m deep water table is assumed. Liquefaction probabilities of the other surficial geologic units are less than 0.05. Probabilities for the scenario earthquakes are generally consistent with observations during historical earthquakes.

Open-File Report↗