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1,676 records · Page 88Linked to original sources
USGS2000

Storm impact scale for barrier islands

A new scale is proposed that categorizes impacts to natural barrier islands resulting from tropical and extra-tropical storms. The proposed scale is fundamentally different than existing storm-related scales in that the coupling between forcing processes and the geometry of the coast is explicitly included. Four regimes, representing different levels of impact, are defined. Within each regime, patterns and relative magnitudes of net erosion and accretion are argued to be unique. The borders between regimes represent thresholds defining where processes and magnitudes of impacts change dramatically. Impact level 1 is the 'swash' regime describing a storm where runup is confined to the foreshore. The foreshore typically erodes during the storm and recovers following the storm; hence, there is no net change. Impact level 2 is the 'collision' regime describing a storm where the wave runup exceeds the threshold of the base of the foredune ridge. Swash impacts the dune forcing net erosion. Impact level 3 is the 'overwash' regime describing a storm where wave runup overtops the berm or, if present, the foredune ridge. The associated net landward sand transport contributes to net migration of the barrier landward. Impact level 4 is the 'inundation' regime describing a storm where the storm surge is sufficient to completely and continuously submerge the barrier island. Sand undergoes net landward transport over the barrier island; limited evidence suggests the quantities and distance of transport are much greater than what occurs during the 'overwash' regime.

Journal of Coastal Research↗
USGS2025

Seismic intensities, ground motions and basin amplification from the 2022 Mw 6.4 Ferndale, California intraslab earthquake

On December 20, 2022, a Mw 6.4 earthquake occurred at a depth of 18 km within the subducting Gorda plate in the Mendocino Triple Junction (MTJ), one of the most seismically active regions of the contiguous United States, causing widespread damage to local communities. Here we document the seismic intensities, ground motions, and basin amplification effects recorded by this earthquake across Humboldt County as part of an ongoing scientific effort to understand subduction zone earthquake hazards. Modified Mercalli Intensity (MMI) values from our post-earthquake field survey report shaking intensities as high as VIII (Severe). Strong ground motion data from 54 seismic stations were processed to calculate amplitude and frequency content parameters across Northern California. The maximum calculated geometric mean PGA and PGV are 1053 cm/s 2 and 52 cm/s (respectively), both recorded within the 3 km deep Eel River sedimentary basin. Comparisons with four published Ground Motion Prediction Equations indicate that PGA and PGV measurements align with expected attenuation-distance patterns for intraslab earthquakes of this nature. Within the Eel River Basin, ground motions for frequencies above 1 Hz are amplified, with respect to reference stations, by factors greater than 2. Our findings suggest that peak ground motions were mainly caused by sedimentary basin site-effects within the Eel River basin, although rupture directivity may have also increased ground motion amplitudes locally. While the Ferndale area is primarily impacted by shallow intraslab earthquakes, our results also raise questions about site-response and basin amplification hazards from a potential megathrust earthquake. The high seismicity rates of the southernmost Cascades call for stronger regional preparedness and improved strategies to mitigate the effects of such a large-scale disaster.

California↗
USGS2024

Seismic tomography 2023

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early‐career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

Bulletin of the Seismological Society of America↗
USGS2024

Fairweather transform boundary Oligocene to present orogenesis: Fairweather Range vertical extrusion and rotation of the Yakutat microplate at ca. 3 Ma

Oblique-slip along transform fault boundaries is often partitioned between a strike-slip system and thrust faults that accommodate contraction. However, topography along the Yakutat-North American transform (Fairweather fault), is asymmetric with low-terrain above active thrusts on the western, Yakutat side of the transform and high topography on the continental side with peaks >4500 m (Mount Fairweather: 4671 m) to the west of the Border Ranges fault, limited recorded earthquakes >M4, and no apparent reverse faults to generate the highest terrain. In this study we compile, for the first time, published U-Pb zircon, 40 Ar/ 39 Ar and K-Ar (hornblende, muscovite, and biotite) and U-Th/He and fission-track (zircon and apatite) bedrock ages (109) from 75 samples to investigate the exhumation history of the Fairweather Range region, complemented by a published detrital sample (ZFT and AFT) and 13 new 40 Ar/ 39 Ar (hornblende, biotite, and K-feldspar) ages on 9 bedrock samples from both sides of the Fairweather fault. Additionally, we examined published seismicity and geodetic data of the Fairweather region and assessed if plate paleo-vectors correlate with the cooling history of the Fairweather Range. Cooling age, seismic, and block-motion patterns indicate the Fairweather Range has been vertically extruded between the Fairweather and the Border Ranges faults as a coherent block since ca. 25 Ma. The pre-6 Ma Pacific plate motion (N30°W) aligns with the N33°W strike of the Fairweather Fault whereas a hypothetical pre-6 Ma Yakutat microplate paleo-vector of (N39°W) does not: indicating a post-6 Ma timing for Yakutat microplate counter-clockwise rotation (9°). We infer that rotation and impingement of the Yakutat microplate along the Fairweather fault at ca. 3 Ma led to the development of the Fairweather restraining bend and increased cooling rates. The resultant thickened Fairweather welt and the ∼30 km thick southeast end of the Yakutat microplate compounded double-indenter tectonics into Alaska's southeast convergent corner

Tectonophysics↗
USGS2025

Dendroseismological investigation of redwood trees along the North Coast section of the San Andreas Fault

Sequoia sempervirens (coast redwood) tree rings have the potential to annually resolve late-Holocene earthquakes on the northern San Andreas Fault based on direct (e.g., physical damage) and indirect (e.g., co-seismic environmental change) impacts, but scarcity of suitable samples and challenges crossdating this long-lived species have limited progress. More precise dating of the pre-1906 (penultimate) earthquake can improve hazard assessment and understanding of rupture segmentation. We target old trees (maximum >815 yr) along the North Coast section of the fault (increment cores via rope-climbing, 11 living trees; plunge cuts, 23 stumps) and employ complementary disturbance detection methods including radial-growth averaging (tree- and series-level), cataloging anatomical indicators (e.g., traumatic resin ducts, TRD), and dating structural components (e.g., reiterated trunks, leans). Multi-centennial ring-width chronologies at Fort Ross (1569−2023) and Gualala (1397−2023) promote continued study with incomplete crossdating limiting utilization of some series. Growth pulses (reductions, releases) and TRD dispersed across the record reflect dynamic environments that obfuscate detection of earthquake signals. The 1906 earthquake did not leave strong signatures on most trees, and when it did, within-tree response varied from normal presentation to discoloration, TRD, and missing rings. Synchrony of indicators at both locations identified 1678−1680 (6 of 15 trees) and 1698−1700 (8 of 16 trees) as the strongest disturbances among dated rings in the time range of the penultimate earthquake, peaking at 1698 (15.7 % of possible growth and anatomical indicators), but the triggering mechanisms for these events are unknown.

California↗
USGS2025

Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa

From July to October 2022, a non-eruptive volcanic earthquake swarm occurred within ~15 km of Taʻū Island, located in eastern American Samoa. Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

American Somoa↗
USGS2024

Flood-inundation maps for the Cuyahoga River at Jaite, Ohio, 2024

Digital flood-inundation maps for a nearly 6-mile reach of the Cuyahoga River at Jaite, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees. The maps depict estimates of the extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 04206425 on the Cuyahoga River at Jaite, Ohio. Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The hydraulic model was calibrated to the current USGS streamgage data and then used to compute 15 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from 6 to 20 feet, which correspond to below “action stage” to “major flood stage” as reported by the National Weather Service. The simulated water-surface profiles were then used with a geographic information system digital elevation model derived from light detection and ranging data to delineate the areas flooded at each stage. These maps, along with current stage data from the USGS streamgage and forecasted high-flow stages from the National Weather Service, can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Ohio↗
USGS1976

Digital telemetry system network installation for the National Earthquake Information Service

A Digital Telemetry System Network, developed by the Albuquerque Seismological Laboratory, was installed for the USGS National Earthquake Information Service (NEIS) during January 1975. NEIS is located in Golden, Colorado. The initial Digital Telemetry System Network consists of four independent digital telemetry systems that provide wide area coverage over most of the United States. The four systems were installed between: Albuquerque, New Mexico to NEIS; St. Louis, Missouri to NEIS; Salt Lake City, Utah to NEIS; and Menlo Park, California to NEIS. Each digital telemetry system will transmit fourteen channels of high accuracy seismic data in a digital format over a standard C-1 grade telephone line. Digitized data words will have a resolution of eleven digital bits plus one sign bit. Each digital telemetry receiver, located at NEIS, will have the capacity to provide fourteen channels of seismic data in a digital format suitable for either on-line digital computer analysis or magnetic tape recording. In addition the data can be presented in an analog format suitable for recording on helicorders or develocorders. This network is the first large scale digital telemetry system used by the U.S. Geological Survey for the transmission of real time seismic data.

Open-File Report↗
USGS2025

Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA

The U.S. Geological Survey (USGS) is updating the 2008 assessment of conventional hydrothermal resources for the Great Basin in the western United States. As part of this work, the workflow for hydrothermal resource favorability maps is being modified to integrate modern data-driven machine learning (ML) methods. Improvements include: [1] using new and refined evidence layers (features); [2] using an order of magnitude more training sites (labeled examples); [3] utilizing simple but non-linear supervised ML algorithms; [4] representing positive training sites (wells with measured heat flow) with their ordinal value proportional to the magnitude of convective upflow (i.e., low, high, or very high convective signals instead of past strategies using positive-negative labels); [5] supplementing training sites with additional sites with low convective signals to represent diverse under-sampled areas where hydrothermal systems are unlikely to exist; [6] comparing with competing approaches; and [7] utilizing Monte Carlo cross-validation to estimate and evaluate prediction uncertainty. For the new favorability map, over half of the power-producing systems (i.e., 15 of 28) are predicted in the 99th percentile of most favorable locations (i.e., the highest 1 % of favorability, corresponding to 1 % of the map area), exceeding the performance of past models that have explicitly used power plants as training sites. Previous favorability maps predicted approximately half of the power-producing hydrothermal systems above the 80th percentile (i.e., 20 % of the map area). For the new favorability map, 93 % of power-producing systems (i.e., 26 of 28) are above the 80th percentile. The power-producing systems for which the new model does not perform well are either comparatively small, low-temperature systems or systems also not predicted well by prior modeling approaches, suggesting that these few systems are unusual when compared with most power-producing systems. Focusing research on these known, seemingly different systems may yield new insights and subsequent discovery of new prospects.

California, Idaho, Nevada, Oregon, Utah↗
USGS2025

Characterizing the scale of regional landslide triggering from storm hydrometeorology

Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A * , based on extremes of modeled soil water relative to its local climatology. We calibrate A * using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A * , along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.

California↗
USGS2024

Rock sample photogrammetry

This step-by-step protocol describes the photogrammetry process used by the U.S. Geological Survey Spokane Imaging Lab (SPIMG) lab to create 3D models of geologic samples. Steps related to photographing small objects are applicable to photogrammetry in general, however, SPIMG-specific steps involving lab hardware and software may not be.

Protocols.io↗
USGS2025

Statewide cumulative human health risk assessment of inorganics-contaminated groundwater wells, Montana, USA

Across the United States, rural residents rely on unregulated and generally unmonitored private wells for drinking water, which may pose serious health risks due to unrecognized contaminants. We assessed the nature, degree, and spatial distribution of cumulative health risks from inorganic contaminants in groundwater. Our analysis included nearly 84,000 data points from 6500+ wells, across 51 of Montana's 98 watersheds, using a public groundwater database. We compared a drinking water screening level cumulative risk assessment (CRA) for inorganics based on the U.S. Environmental Protection Agency (EPA) protective health thresholds (Maximum Contaminant Level Goals, Health Advisories [MCLG-HAs]) to a CRA based on EPA public supply enforceable Maximum Contaminant Levels (MCLs). Based on median concentrations of 19 inorganics (antimony, arsenic, barium, beryllium, boron, cadmium, chromium, copper, fluoride, manganese, molybdenum, nickel, nitrate, lead, selenium, strontium, thallium, uranium, zinc), 75% of watersheds had MCLG-HA-based cumulative risk values > 1.0; arsenic and uranium contributed the most risk, followed by strontium, fluoride, manganese and boron. Hence, this screening level (Tier I) CRA indicated widespread potential for unrecognized human health risk to private well users from inorganic contaminants considering both carcinogenic and non-carcinogenic risks. Sensitivity analysis showed that benchmarks applied (MCLG-HAs versus MCLs) exerted the largest control on results. Our findings identify priority regions for Tier 2 risk assessments to elucidate local sources and distributions of geogenic versus anthropomorphic contaminants. Our study is the first statewide assessment of cumulative health risk from groundwater that we are aware of, and results support increased statewide drinking water education and testing to reduce human health risks from contaminated private well water.

Montana↗
USGS2025

Prospectivity modeling of the NASA VIPER landing site at Mons Mouton near the Lunar South Pole

We use a high-resolution digital elevation model and a numerical thermal model to produce a variety of inputs for a water-ice prospectivity model for the Volatiles Investigating Polar Exploration Rover (VIPER) landing site. These input data are maps of topography, surface slope, surface aspect, surface curvature, maximum temperature, depth to ice stability, permanently shadowed regions (PSRs), distance to PSRs, and PSR density. This model predicts where water ice is most likely within the top meter of regolith, assuming plausible relationships between ice concentration and the various inputs. The model is designed to be adjusted in near-real time as data are collected during the VIPER mission. As such, it is a tool for both analyzing data from the mission as well as planning operations. Since the current model, at this point, relies only on orbital remote sensing, the final version will also be a tool to extrapolate the VIPER mission results across the lunar poles.

Planetary Science Journal↗
USGS2026

Precipitation-based flood-inundation maps for the East Fork Little Blue River and tributaries at Lee’s Summit, Missouri, 2024

The U.S. Geological Survey, in cooperation with the City of Lee’s Summit, Missouri, assessed flooding of the East Fork Little Blue River and tributaries for varying precipitation magnitudes and durations, varying antecedent runoff conditions, and projected climate-change conditions. The precipitation scenarios were used to develop a library of flood-inundation maps for a 2.95-mile reach of the East Fork Little Blue River and tributaries within the city. A two-dimensional U.S. Army Corps of Engineers Hydrologic Engineering Center–River Analysis System (HEC–RAS; ver. 6.5) rain-on-grid model was calibrated to selected runoff events representing a range of antecedent runoff conditions and hydrologic responses. Lowest adjacent grades for structures within the nearby study area were incorporated into the terrain, and depth grids and water-surface elevation grids were developed for the study area. Simulated velocities at selected bridge locations were also developed from the model. The model was calibrated using water-surface elevation data collected from water-level loggers (pressure transducers) and streamflow measurements and water-surface elevation measurements made at a reference point during runoff events. The calibrated HEC–RAS model was used to simulate streamflows from design rainfall events of 15-minute to 24-hour durations and ranging from a 100- to 0.1-percent annual exceedance probability (1-year to 1,000-year recurrence intervals). Flood-inundation maps were produced for depths at a reference location of 3 to 16 feet, or a depth exceeding the 0.1-percent annual exceedance probability interval precipitation. The results of each precipitation duration-frequency value were represented by a 1-foot-increment inundation map based on the generated peak streamflow from that rainfall event and the corresponding water-surface elevation at the East Fork Little Blue River reference location. Within the HEC–RAS model, 240 scenarios were developed from the design rainfall events with each of 3 antecedent conditions. Additional scenarios were created to simulate the effects of projected precipitation scenarios on the 100-year recurrence interval, 24-hour storm and the 100-year recurrence interval, 6-hour storm. All simulation results were assigned to a flood-inundation map condition based on the generated peak flow and corresponding water-surface elevation at the East Fork Little Blue River reference location. The flood-inundation maps are shown on a web mapping application made available to the public through the City of Lee’s Summit (hyperlink will be added when available). The flood-inundation maps are tied to real-time precipitation data obtained from the Automated Surface Observing System weather station at the Lee’s Summit Municipal Airport, accessible at https://mesonet.agron.iastate.edu/request/download.phtml?network=MO_ASOS . The availability of these maps, along with information regarding observed rainfall, could help provide emergency management personnel and residents with information that is critical for flood-response activities, such as evacuations and road closures, and for postflood recovery efforts.

Missouri↗
USGS2025

Component identification of solid biomass fuels using reflected light microscopy: Interlaboratory study 2

As nations transition toward sustainable energy systems , biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

International Journal of Coal Geology↗
USGS2026

Orientation dependence of probabilistic seismic hazard estimates from CyberShake physics-based simulations

Earthquake ground‐motion intensities, such as pseudospectral accelerations (SAs), can vary significantly with horizontal orientation. However, conducting probabilistic seismic hazard analysis (PSHA) for each horizontal orientation is challenging because current ground‐motion models used in PSHA consider only a single horizontal intensity value, usually the median across all orientations, known as RotD50. To address this limitation, we employ physics‐based simulations for PSHA, which contain full waveforms from which ground‐motion intensities can be computed for all horizontal orientations to study directional seismic hazard. We apply our approach to the latest CyberShake study of the Greater Los Angeles metropolitan area, developed by the Statewide California Earthquake Center, finding that seismic hazard at a 2475‐yr return period, a common value used for earthquake‐resistant design, varies significantly with horizontal orientation. For instance, for SAs at 3 s, the maximum seismic hazard across all horizontal orientations is, on average, 15% higher than the median RotD50 hazard, with these differences becoming more pronounced at longer periods. These observed variations can generally be attributed to physical mechanisms that polarize seismic waves, such as the radiation pattern of the earthquake source and the influence of the subsurface structure. These results may have important implications for earthquake engineering applications, particularly for long‐period structures in areas with substantial horizontal variations in seismic hazard.

California↗
USGS2026

U.S. Geological Survey Monitoring Milestones—Oe-151 at Woodgate, NY (433112075091501)

On July 9, 1926, monitoring well Oe-151 at Woodgate, New York (USGS ID 433112075091501) recorded its first groundwater data. Since then, the well has provided water data nearly continuously and has now reached a 100-year milestone for data collection. The well is part of the U.S. Geological Survey (USGS) Climate Response Network (CRN), which is a national network of wells selected to monitor natural groundwater conditions. Well Oe-151 is the first well in the network to reach a 100-year Centennial milestone.

New York↗