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At least 1,171 records · Page 65Linked to original sources
USGS2013

U.S. Geological Survey natural hazards science strategy— Promoting the safety, security, and economic well-being of the Nation

Executive Summary The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).

Circular↗
USGS2012

Natural hazards science strategy

The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).

Open-File Report↗
USGS2024

Why do seismic hazard models worldwide appear to overpredict historical intensity observations?

Probabilistic seismic hazard assessments (PSHAs) provide the scientific basis for building codes to reduce damage from earthquakes. Despite their substantial impact, little is known about how well PSHA predicts actual shaking. Recent PSHA for California, Japan, Italy, Nepal, and France appear to consistently overpredict historically observed earthquake shaking intensities. Numerical simulations show that observed shaking is equally likely to be above or below predictions. This result from independently developed models and datasets in different countries and tectonic settings indicates possible systematic bias in the hazard models, the observations, or both. Analysis of possible causes shows that much of the discrepancy is due to a subtle and rarely considered issue: the conversion equations used in comparing the models—which forecast shaking as peak ground acceleration or velocity—and observations—parameterizations of qualitative shaking reports. Historical shaking reports fill a crucial data gap, but more research is warranted on how qualitative observations relate to instrumental shaking measures for earthquakes.

Science Advances↗
USGS2004

Local amplification of seismic waves from the Denali earthquake and damaging seiches in Lake Union, Seattle, Washington

The Mw7.9 Denali, Alaska earthquake of 3 November, 2002, caused minor damage to at least 20 houseboats in Seattle, Washington by initiating water waves in Lake Union. These water waves were likely initiated during the large amplitude seismic surface waves from this earthquake. Maps of spectral amplification recorded during the Denali earthquake on the Pacific Northwest Seismic Network (PNSN) strong-motion instruments show substantially increased shear and surface wave amplitudes coincident with the Seattle sedimentary basin. Because Lake Union is situated on the Seattle basin, the size of the water waves may have been increased by local amplification of the seismic waves by the basin. Complete hazard assessments require understanding the causes of these water waves during future earthquakes.

Washington↗
USGS2020

Probabilistic seismic hazard analysis at regional and national scale: State of the art and future challenges

Seismic hazard modelling is a multi-disciplinary science that aims to forecast earthquake occurrence and its resultant ground shaking. Such models consist of a probabilistic framework that quantifies uncertainty across a complex system; typically, this includes at least two model components developed from Earth science: seismic-source and ground-motion models. Although there is no scientific prescription for the forecast length, the most common probabilistic seismic hazard analyses consider forecasting windows of 30 to 50 years, which are typically an engineering demand for building code purposes. These types of analyses are the topic of this review paper. Although the core methods and assumptions of seismic hazard modelling have largely remained unchanged for more than 50 years, we review the most recent initiatives which face the difficult task of meeting both the increasingly sophisticated demands of society and keeping pace with advances in scientific understanding. A need for more accurate and spatially precise hazard forecasting must be balanced with increased quantification of uncertainty and new challenges such as moving from time-independent hazard to forecasts that are time-dependent and specific to the time-period of interest. Meeting these challenges requires the development of science-driven models which integrate all information available, the adoption of proper mathematical frameworks to quantify the different types of uncertainties in the hazard model, and the development of a proper testing phase of the model to quantify its consistency and skill. We review the state-of-the-art of the national seismic hazard modeling, and how the most innovative approaches try to address future challenges.

Reviews of Geophysics↗
USGS2016

Maximum magnitude ( M max ) in the central and eastern United States for the 2014 U.S. Geological Survey Hazard Model

Probabilistic seismic‐hazard assessment (PSHA) requires an estimate of M max , the moment magnitude M of the largest earthquake that could occur within a specified area. Sparse seismicity hinders M max estimation in the central and eastern United States (CEUS) and tectonically similar regions worldwide (stable continental regions [SCRs]). A new global catalog of moderate‐to‐large SCR earthquakes is analyzed with minimal assumptions about enigmatic geologic controls on SCR M max . An earlier observation that SCR earthquakes of M 7.0 and larger occur in young (250–23 Ma) passive continental margins and associated rifts but not in cratons is not strongly supported by the new catalog. SCR earthquakes of M 7.5 and larger are slightly more numerous and reach slightly higher M in young passive margins and rifts than in cratons. However, overall histograms of M from young margins and rifts and from cratons are statistically indistinguishable. This conclusion is robust under uncertainties in M , the locations of SCR boundaries, and which of two available global SCR catalogs is used. The conclusion stems largely from recent findings that (1) large southeast Asian earthquakes once thought to be SCR were in actively deforming crust and (2) long escarpments in cratonic Australia were formed by prehistoric faulting. The 2014 seismic‐hazard model of the U.S. Geological Survey represents CEUS M max as four‐point probability distributions. The distributions have weighted averages of M 7.0 in cratons and M 7.4 in passive margins and rifts. These weighted averages are consistent with M max estimates of other SCR PSHAs of the CEUS, southeastern Canada, Australia, and India.

Bulletin of the Seismological Society of America↗
USGS2013

Seismicity of the Earth 1900–2010 Himalaya and vicinity

Seismicity in the Himalaya region predominantly results from the collision of the India and Eurasia continental plates, which are converging at a relative rate of 40–50 mm/yr. Northward underthrusting of India beneath Eurasia generates numerous earthquakes and consequently makes this area one of the most seismically hazardous regions on Earth. The surface expression of the plate boundary is marked by the foothills of the north-south trending Sulaiman Range in the west, the Indo-Burmese Arc in the east, and the east-west trending Himalaya Front in the north of India. Along the western margin of the India plate, relative motions between India and Eurasia are accommodated by strike-slip, reverse, and oblique-slip faulting resulting in the complex Sulaiman Range fold and thrust belt, and the major translational Chaman Fault in Afghanistan. Beneath the Pamir‒Hindu Kush Mountains of northern Afghanistan, earthquakes occur to depths as great as 200 km as a result of remnant lithospheric subduction. Further north again, the Tian Shan is a seismically active intra-continental mountain belt defined by a series of east-west trending thrust faults thought to be related to the broad footprint of the India-Eurasia collision. Tectonics in northern India are dominated by motion along the Main Frontal Thrust and associated thrust faults of the India-Eurasia plate boundary, which have resulted in a series of large and devastating earthquakes in (and prior to) the 20th century. The Tibetan Plateau to the north of the main plate boundary is a broad region of uplift associated with the India-Eurasia collision, and is cut by a series of generally east-west trending strike-slip faults. These include the Kunlun, Haiyuan, and the Altyn Tagh faults, all of which are left-lateral structures, and the Kara-Koram right-lateral fault. Throughout the plateau, thrust faults accommodate the north-south compressional component of crustal shortening associated with the ongoing collision of India and Eurasia, while strike-slip and normal faults accommodate east-west extension. To the east, The Longmen Shan thrust belt marks the eastern margin of the Tibetan Plateau separating the complex tectonics of the plateau region from the relatively undeformed Sichuan Basin. Further south, the left-lateral Xiangshuihe-Xiaojiiang, right-lateral Red River and right-lateral Sagaing strike-slip fault systems accommodate deformation along the eastern margin of the India plate. Deep earthquakes have also occurred in the Indo-Burmese Arc region, thought to be an expression of eastward-directed subduction of the India plate, though whether subduction is ongoing is still debated.

Himalaya and vicinity↗
USGS1975

Hydrocarbon potential, geologic hazards, and the technology, time-frame and infrastructure for exploration and development of the lower Cook Inlet, Alaska; a preliminary assessment

The Lower Cook Inlet Outer Continental Shelf (OCS) contains 5600 km 2 of submerged land in less than 200 m of water 150 to 350 km southwest of Anchorage, Alaska. This area could contain from 0.3 to 1.4 billion barrels of oil and from 0.6 to 2.7 trillion cubic feet of natural gas depending upon the statistical confidence level indicated. The known geology of this submerged area, is extrapolated to the offshore from onshore data. The sedimentary rocks are as old as Triassic and as young as Pleistocene. The Mesozoic strata include volcanic rocks, volcanoclastic and marine clastic sediments. Tertiary, rocks from which the oil and gas in Upper Cook Inlet are produced, consist of nonmarine conglomerate, sandstone, siltstone and coal. The potential objective section for oil and gas in this OCS area ranges from Middle Jurassic through the Tertiary. The present structural configuration of this area is a northeast trending trough filled with Tertiary sediments. The trough is flanked by two major faults, the Bruin Bay fault on the northwest and the Border Ranges fault on the southeast. Between these faults is the OCS area containing anticlinal structures and faults which may be traps for hydrocarbons. Potential geologic hazards are present in this area. It is an area of intense tectonism expressed as seismic activity (earthquakes) and volcanic eruptions which produce many natural disturbances including tsunamis. This distribution of soft sediment and other submarine features which relate to geologic hazards are only generally known.

Alaska↗
USGS2018

Testing for the ‘predictability’ of dynamically triggered earthquakes in Geysers Geothermal Field

The Geysers geothermal field is well known for being susceptible to dynamic triggering of earthquakes by large distant earthquakes, owing to the introduction of fluids for energy production. Yet, it is unknown if dynamic triggering of earthquakes is ‘predictable’ or whether dynamic triggering could lead to a potential hazard for energy production. In this paper, our goal is to investigate the characteristics of triggering and the physical conditions that promote triggering to determine whether or not triggering is in anyway foreseeable. We find that, at present, triggering in The Geysers is not easily ‘predictable’ in terms of when and where based on observable physical conditions. However, triggered earthquake magnitude positively correlates with peak imparted dynamic stress, and larger dynamic stresses tend to trigger sequences similar to mainshock–aftershock sequences. Thus, we may be able to ‘predict’ what size earthquakes to expect at The Geysers following a large distant earthquake.

California↗
USGS2026

Suitability of ground-motion models for seismic hazard assessment in Puerto Rico and the U.S. Virgin Islands

We perform linear mixed-effects analyses with a ground-motion dataset to evaluate how well ground-motion models (GMMs) fit active crustal, subduction interface, and subduction intraslab earthquakes in Puerto Rico and the US Virgin Islands. Most of the GMMs reproduce the spatial variation in peak ground motions with earthquake magnitude and rupture distance but predict ground motions 0.3–1.0 natural log units (35%–270%) greater than observations. Two GMMs developed for Puerto Rico that are based on ground-motion records from mostly magnitude 4–5 earthquakes do not perform as well. We attribute the period-dependent overprediction in observed ground motions to differences between the observed site response and the linear site response in the GMMs. Consequently, we developed region-specific GMMs by adjusting the period-dependent linear site response coefficients and period-dependent constant coefficients to remove most of the bias between predicted ground motions and observations. For the analysis, we compile ground-motion records and process waveforms to build a dataset with 10,127 records at 72 stations from 849 magnitude 4.0–6.4 earthquakes between 1 January 2006 and 31 March 2024. The earthquakes include active crustal, subduction interface, and subduction intraslab events. We evaluate the GMMs using the time-averaged shear wave speed in the top 30 m ( ), which we compile from site surveys and proxy values computed from horizontal to vertical spectral ratios. Site terms exhibit strong consistency across GMMs and crustal and subduction earthquakes, indicating that the linear mixed-effects analysis successfully isolates the effects of local site response. The event terms show little spatial correlation and more substantial variability than in other regions, which we attribute to uncertainties in the earthquake magnitudes. This analysis guides the selection of the GMMs for the 2025 update of the National Seismic Hazard Model for Puerto Rico and the US Virgin Islands.

Puerto Rico, U.S. Virgin Islands↗
USGS2014

Time-averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM-X interferometry: Implications for magma supply and storage during 2011-2013

Differencing digital elevation models (DEMs) derived from TerraSAR add-on for Digital Elevation Measurements (TanDEM-X) synthetic aperture radar imagery provides a measurement of elevation change over time. On the East Rift Zone (EZR) of Kīlauea Volcano, Hawai‘i, the effusion of lava causes changes in topography. When these elevation changes are summed over the area of an active lava flow, it is possible to quantify the volume of lava emplaced at the surface during the time spanned by the TanDEM-X data—a parameter that can be difficult to measure across the entirety of an ~100 km 2 lava flow field using ground-based techniques or optical remote sensing data. Based on the differences between multiple TanDEM-X-derived DEMs collected days to weeks apart, the mean dense-rock equivalent time-averaged discharge rate of lava at Kīlauea between mid-2011 and mid-2013 was approximately 2 m 3 /s, which is about half the long-term average rate over the course of Kīlauea's 1983–present ERZ eruption. This result implies that there was an increase in the proportion of lava stored versus erupted, a decrease in the rate of magma supply to the volcano, or some combination of both during this time period. In addition to constraining the time-averaged discharge rate of lava and the rates of magma supply and storage, topographic change maps derived from space-based TanDEM-X data provide insights into the four-dimensional evolution of Kīlauea's ERZ lava flow field. TanDEM-X data are a valuable complement to other space-, air-, and ground-based observations of eruptive activity at Kīlauea and offer great promise at locations around the world for aiding with monitoring not just volcanic eruptions but any hazardous activity that results in surface change, including landslides, floods, earthquakes, and other natural and anthropogenic processes.

Hawai'i↗
USGS2010

Field survey of the March 28, 2005 Nias-Simeulue earthquake and Tsunami

On the evening of March 28, 2005 at 11:09 p.m. local time (16:09 UTC), a large earthquake occurred offshore of West Sumatra, Indonesia. With a moment magnitude (Mw) of 8.6, the event caused substantial shaking damage and land level changes between Simeulue Island in the north and the Batu Islands in the south. The earthquake also generated a tsunami, which was observed throughout the source region as well as on distant tide gauges. While the tsunami was not as extreme as the tsunami of December 26th, 2004, it did cause significant flooding and damage at some locations. The spatial and temporal proximity of the two events led to a unique set of observational data from the earthquake and tsunami as well as insights relevant to tsunami hazard planning and education efforts. ?? 2010 Springer Basel AG.

Pure and Applied Geophysics↗
USGS2023

Preliminary documentation of coseismic ground failure triggered by the February 6, 2023 Türkiye earthquake sequence

The devastating Kahramanmaraş earthquake sequence occurred on February 6, 2023. Two main events, M w 7.8 and M w 7.5 occurred 9 hours apart, affected 11 cities in Turkey, and subjected an area of ∼90,000 km 2 to shaking levels known to trigger landslides (peak ground acceleration > 0.08 g). Extensive landsliding was expected given the hilly terrain affected by this significant ground shaking—about 15% of the topography is steeper than 20°—but was not initially apparent in early satellite imagery, mostly because of obscuring snow that fell just after the earthquakes. However, after a more detailed investigation using high-resolution satellite images, aerial photos, and a field survey, we confirmed that this earthquake sequence did, indeed, trigger numerous landslides. In this study, we present those findings and provide a preliminary characterization of the spatial distribution, general characteristics, and dominant types of landslides and hillslope deformation triggered by the earthquake sequence. We mapped 3673 coseismic landslides, mostly concentrated in the northern half of the impacted area. Rock falls are the most abundant landslide type, but bedrock rotational landslides, translational slides and lateral spreads are also numerous. Surface rupture through mountainous terrain caused several large, and in some cases fatal, landslides. Incipient landslides and ground cracks are also widespread, especially in the north. Lithology, spatial variability of ground shaking, and topographic relief appear to be the main variables controlling the spatial distribution of coseismic landslides. There are few detailed studies of earthquake-triggered landslides in arid and semi-arid regions such as this one, nor for such complex earthquake sequences. Therefore, this contribution provides valuable information for future hazard and modeling efforts in arid and semi-arid regions.

Engineering Geology↗
USGS2011

Tectono-magmatic processes investigated at deep-water flanks of Hawaiian volcanoes

Hawaiian volcanoes are exceptional examples of intraplate hotspot volcanism. Hotspot volcanoes, which frequently host large eruptions and related earthquakes, flank‐failure landslides, and associated tsunamis, can present severe hazards to populated regions. Many studies have focused on subaerial parts of Hawaiian volcanoes, but the deep‐water flanks of the edifices, which can reach 5700 m below sea level, remain poorly understood because they are so inaccessible. In 1998 a collaborative program between Japan and the United States was initiated to explore the evolution of Hawaiian volcanoes, including their growth and degradation

Hawaii↗
USGS2022

Detection of aseismic slip and poroelastic reservoir deformation at the North Brawley Geothermal Field from 2009 to 2019

The North Brawley Geothermal Field, located within the Brawley Seismic Zone of Southern California, presents a case study for understanding seismic hazards linked to fluid injection and geothermal energy extraction. An earthquake swarm near the geothermal field in 2012 included two earthquakes with magnitudes greater than 5 and was potentially preceded by a years-long aseismic slip transient. To better understand ground deformation around the geothermal field, including its evolution with time and its physical mechanisms, we analyze deformation before, during, and after the swarm using ground- and satellite-based geodetic techniques between 2009 and 2019. We integrate observations from GNSS, Sentinel-1, TerraSAR-X, UAVSAR, and leveling surveys into a single deformation history. Modeling of this new collection of observations at the North Brawley Geothermal Field provides evidence for 80% more pre-swarm aseismic slip than previously recognized from 2009 to 2012. During the 2012 Brawley swarm, our geodetic slip inversions closely match the results of seismic waveform inversions from the swarm events. After the 2012 swarm, surface deformation is dominated by poroelastic deformation of a shallow fluid reservoir at <1 km depth rather than fault slip. The deformation history and seismicity catalogs at North Brawley suggest a cessation of fault-related slip during the ∼7 years after the 2012 earthquake swarm.

California↗
USGS2026

Dimensionality reduction techniques for analyzing tsunami simulations in hazard assessment and forecasting applications

A wide selection of linear and non-linear dimensionality reduction techniques is evaluated on synthetic tsunami data that is the basis for tsunami hazard assessment and computational forecasting. The data were computed from earthquake rupture forecasts (ERFs) supplying initial generation conditions and a linear long-wave Green's function approach to efficiently calculate tsunami propagation. The dimensionality reduction techniques include various forms of principal component analysis, manifold learning, and neural networks. Both external (e.g., mutual information) and internal (silhouette) metrics are used to evaluate clustering in the reduced dimension, focusing on peak-nearshore tsunami amplitudes (PNTA) along a nearshore isobath and time-series (marigrams) at specific nearshore locations. This evaluation is intentionally scoped to cluster-based downsampling to produce probabilistic inundation maps. For our test case along the Nankai subduction zone, manifold learning methods produced the highest clustering metric scores for PNTA profiles among the examined dimensionality reduction techniques. The marigram results are less consistent, owing primarily to uncertainty in defining appropriate clusters in the original high-dimensional (ambient) space to establish a “ground truth.” A novel application of using the integrative ERF-tsunami approach is that features extracted in the reduced domain, particularly from manifold learning, can be mapped back to rupture zones along the fault. This yields targeted fault information associated with unique PNTA profiles and marigram characteristics, such as late-arriving waves. Further testing would be needed for application-specific workflows and more complex fault systems, but results from this single subduction zone case study support the consideration of non-linear techniques (e.g., manifold learning) as alternatives to linear methods.

Nankai megathrust↗
USGS2001

Geologic map and map database of the Spreckels 7.5-minute Quadrangle, Monterey County, California

Introduction The Spreckels quadrangle lies at the north end of the Sierra de Salinas and extends from the Salinas Valley on the northeast across Los Laurelles Ridge south to Carmel Valley, an intermontane valley that separates the Santa Lucia Range from the Sierra de Salinas (fig. 1). The Toro Regional Park occupies the east-central part of the quadrangle, whereas the former Fort Ord Military Reservation covers the northwestern part of the area and is the probable locus of future development. Subdivisions largely occupy the older floodplain of Toro Creek and the adjacent foothills, with less dense development along the narrower canyons of Corral de Tierra and San Benancio Gulch to the south. The foothills southwest of the Salinas River are the site of active residential development. Geologically, the study area has a crystalline basement of Upper Cretaceous granitic rocks of the Salinian block and older metasedimentary rocks of the schist of the Sierra de Salinas of probable Cretaceous age. Resting nonconformably upon these basement rocks is a sedimentary section that ranges in age from middle Miocene to Holocene and has a composite thickness of as much as 1,200 m. One of the purposes of the present study was to investigate the apparent lateral variation of the middle to upper Miocene sections from the typical porcelaneous and diatomaceous Monterey Formation of the Monterey and Seaside quadrangles to the west (Clark and others, 1997) to a thick marine sandstone section in the eastern part of the Spreckels quadrangle. Liquefaction, which seriously affected the Spreckels area in the 1906 San Francisco earthquake (Lawson, 1908), and landsliding are the two major geological hazards of the area. The landslides consist mainly of older large slides in the southern and younger debris flows in the northern part of the quadrangle. This digital map database, compiled from previously published and unpublished data, and new mapping by the authors, represents the general distribution of bedrock and surficial deposits in the mapped area. Together with the accompanying text file (skmf.txt, skmf.pdf, or skmf.ps), it provides current information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:24,000 or smaller.

Miscellaneous Field Studies Map↗