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1,694 records · Page 88Linked to original sources
USGS2026

Characterizing changes in postfire debris-flow hazard as burned areas recover

Emergency assessments of postfire debris-flow hazards that are performed by the U.S. Geological Survey (USGS) provide estimates of debris-flow likelihood and rainfall triggering conditions that are used for evaluating and managing runoff-generated debris-flow hazards in recently burned areas throughout the western United States. Although the immediate postfire period, within roughly one year after fire, is typically the most susceptible to runoff-generated debris flows, the hazard evolves in time and space as the burned area recovers. The recovery trajectory a given burned area will take depends on local climate and weather and can be difficult to predict. Some burned areas recover quickly, whereas others experience debris flows for multiple years after fire. As a result, extending our ability to update debris-flow likelihood estimates and rainfall thresholds based on observed recovery of the burned area would be beneficial. We present a method for multi-year runoff-generated debris-flow hazard assessment that leverages the USGS “M1” debris-flow likelihood model and integrates updated, satellite-derived, normalized burn ratio data to estimate vegetation recovery. We predict recovery-aware rainfall thresholds and validate them against a multi-year debris-flow hazard prediction and could be adapted for use with other debris-flow models that incorporate burn severity data.

Arizona, California, Colorado, New Mexico, Washing↗
USGS2026

Deformed submarine terraces in Puget Sound, Pacific Northwest, indicate only one M >~7.5 earthquake on the Seattle fault zone in the past 11,000 yr

Submerged marine terraces in Puget Sound, deformed across the Seattle fault zone (SFZ), indicate that only one earthquake as large as M~7.5 has occurred in at least the past 11 kyr. Previous paleoseismic studies document a M~7.5 earthquake between 923–4 CE, which uplifted coastal marine terraces by as much as 8 m. We demonstrate that this earthquake was the only such event since ~11 ka by mapping and quantifying deformation of older marine terraces, now submerged in Puget Sound. The submerged terraces, attributed to a late-glacial sea-level lowstand, record both glacial isostatic rebound and tectonic deformation. Vertical offset of the ~11 ka terraces within the SFZ is comparable to that of the marine terraces uplifted in 923 CE, implying no additional large (M>~7.5) earthquake on the SFZ since ~11 ka. This result implies a longer recurrence interval than current hazard estimates, which assumes recurrence of M>7.1 events every 5 kyr. Our mapping of SFZ deformation since ~11 ka also supports fault segmentation and contiguous block uplift between the Seattle and Tacoma fault zones.

Washington↗
USGS2026

Estimating aftershock risk for entry into earthquake-damaged buildings

We present a simple method to estimate the risk of experiencing strong shaking from aftershocks during entry into earthquake-damaged buildings. We compute wait times until the probability of strong ground shaking from aftershocks reaches a predefined risk threshold; for example, a 0.4 percent probability of experiencing Modified Mercalli Intensity 7 or greater shaking during the planned building entry. We also develop a relation between aftershock probability and the probability of strong shaking, so that users can reference the U.S. Geological Survey aftershock forecast during an ongoing aftershock sequence to determine if the risk threshold has been met. We apply our method to active continental regions (for example, the Western United States), stable continental regions (for example, the Central and Eastern United States), and subduction zones (for example, Cascadia or Alaska).

Open-File Report↗
USGS2025

Aftershocks in stress shadows are inconsistent with modeled static Coulomb stress changes

Aftershock triggering is commonly attributed to increases in static Coulomb stress. In some areas, termed "stress shadows", a decrease in Coulomb stress is predicted to suppress earthquake occurrence. However, aftershocks are often observed in the modeled stress shadows. We examine several hypotheses that attempt to reconcile these shadow aftershocks with the static Coulomb stress change model: (1) they appear to be in shadows because of inaccuracy in the stress change calculations, (2) they occur on faults of unusual orientation which actually experienced increased Coulomb stress, (3) they occur on faults with different frictional properties, not modeled well by Coulomb stress, and (4) they are secondary aftershocks triggered by prior aftershocks or afterslip. When tested on the 2016 Mw7.0 Kumamoto, Japan, and 2019 Mw7.1 Ridgecrest, California, aftershock sequences, none of these hypotheses can explain the majority of the shadow aftershocks, and taken together these hypotheses can explain only about half of these aftershocks. This implies that Coulomb stress modeling that lacks small-scale fault zone heterogeneity might be inadequate to fully capture the true static stress changes and/or that other physical triggering models are needed, for example transient processes such as delayed triggering by dynamic stress changes from the passing seismic waves.

California↗
USGS2024

Distinguishing natural sources from anthropogenic events in seismic data

As seismic data are increasingly used to investigate a diverse range of subsurface phenomena beyond regular fast-rupturing earthquakes (Peng and Gomberg, 2010; Beroza and Ide, 2011), it is important to acknowledge that human-generated ground vibrations may be mistaken for naturally generated subsurface processes (Larose et al., 2015; Li et al., 2018). Correct discrimination of natural processes from anthropogenic noise is especially pressing given the trend in seismic detection research toward automated algorithms and machine learning methods (Yoon et al., 2015; Kong et al., 2019;Mousavi and Beroza, 2022) and the growth in seismic data collection in new environments such as urban and industry settings (e.g., Díaz et al.,2017).

Seismological Research Letters↗
USGS2026

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters↗
USGS1976

Heat-flow data from southeastern Oregon

With the exception of values from two holes drilled within 2 km of Mickey Hot Springs, 17 new heat-flow values in southeastern Oregon are within or somewhat below the range one would normally expect in non-anomalous parts of the North American Cordillera. This is not surprising for a region in which most igneous rocks on the surface are 5 m.y. old or more. There is a suggestion of a thermal anomaly associated with the very young (late Pleistocene or Holocene) Diamond Craters lava field, and the thermal regime on both sides of Steens Mountain seems to be controlled, to some degree, by lateral and vertical movement of water.

Oregon↗
USGS2024

Uncertainty in ground-motion-to-intensity conversions significantly affects earthquake early warning alert regions

We examine how the choice of ground‐motion‐to‐intensity conversion equations (GMICEs) in earthquake early warning (EEW) systems affects resulting alert regions. We find that existing GMICEs can underestimate observed shaking at short rupture distances or overestimate the extent of low‐intensity shaking. Updated GMICEs that remove these biases would improve the accuracy of alert regions for the ShakeAlert EEW system for the West Coast of the United States. ShakeAlert uses ground‐motion prediction equations (GMPEs), which calculate spatial distributions of peak ground acceleration (PGA) and peak ground velocity (PGV) from earthquake source estimates, combined with GMICEs to translate GMPE output into modified Mercalli intensity (MMI). We find significant epistemic uncertainty in alert distances; near‐source MMI estimates from different GMICEs can differ by over 1 MMI unit, and MMI extents used for public EEW alerts can differ by hundreds of kilometers for larger magnitude earthquakes ( M ∼6.5+). We use a catalog of “Did You Feel It?” shaking reports to evaluate how well GMICEs predict observed shaking. Our preferred GMICE is the one that computes MMI using PGV for high intensities and transitions to using PGA for nondamaging intensities. These results motivate updating GMICE relationships more generally, including in ShakeMap applications.

The Seismic Record↗
USGS2025

A soil velocity model for improved ground motion simulations in the U. S. Pacific Northwest

Near-surface seismic velocity structure may significantly impact the intensity, duration, and frequency content of ground shaking during an earthquake. In this study, we compile 649 shear wave velocity (Vs) profiles throughout the U.S. Pacific Northwest and southern British Columbia (PNW) and use these measured profiles to develop a representative soil velocity model for four major Holocene soil provinces: Puget Lowlands, Willamette Valley, fill and alluvium, and `other' soils. The resulting soil velocity model shows good agreement to measured data for a wide range of site conditions, with variability between different geologic domains reflecting fundamental differences in depositional environments. We then show that using this regional soil velocity model in simulations of the 2001 M6.8 Nisqually, Washington earthquake improves the fit to observed high-frequency (≥ 0.5 Hz) ground motions in the Puget Sound region compared to simulations that do not incorporate shallow (≤ 200 m) seismic velocity structure. Overall, this work shows that incorporating localized soil velocity profiles into seismic velocity models is important for accurately estimating high-frequency ground motion and regional seismic hazard in earthquake simulations. Future earthquake simulations and hazard studies in the PNW could incorporate these soil velocity profiles to capture the region's distinct site response characteristics.

Washington↗
USGS2025

Climate-driven sulfate export in alpine watersheds may stimulate methylmercury production

Climate change is increasing sulfate export and changing wetland extent in mountain regions. These changes may increase microbially mediated production of the neurotoxic substance methylmercury due to enhanced sulfate metabolism in mountain environments. Here, we assess methylmercury concentrations and formation rates across high-elevation wetlands in the Colorado Rocky Mountains. We also investigate sulfate controls on methylmercury production within subalpine peatlands by amending soils with sulfate to mimic increased stream export of sulfate from the alpine zone and measuring methylmercury formation rates for different sulfate treatments. We found that subalpine peatlands have statistically significant higher methylmercury concentrations and formation rates compared to alpine, mineral-soil wetlands. Methylmercury production in subalpine peatlands also increased significantly ( p < 0.05) following sulfate additions; the highest rates occurred in sediments with intermediate extractable sulfate concentrations (∼0.60–1.4 mg sulfate g −1 dry soil). Our study is the first to identify soil sulfate-related thresholds for methylmercury production and sulfate-limitation of methylmercury production in subalpine peatlands. These findings highlight important linkages between climate-driven mineral weathering and mercury cycling in mountain regions globally.

Colorado↗
USGS2026

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota↗
USGS2025

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California↗
USGS2026

Effect of mineral deposit data on predictions from the three-part approach to quantitative mineral resource assessment—A study of 16 previous U.S. Geological Survey assessments

The three-part approach to quantitative mineral resource assessment requires information about the properties of undiscovered mineral deposits in an assessment area. These properties are unknown, so the properties of discovered mineral deposits of the same mineral deposit type are used instead. In the three-part approach, these discovered mineral deposits come from around the world, and their properties constitute the pooled data for that mineral deposit type. Alternatively, these discovered mineral deposits could come from the assessment area, and their properties constitute the tract data for that mineral deposit type. Tract data may be more representative of the undiscovered mineral deposits in the assessment area than the pooled data. The goal of this study was to determine whether resource predictions using pooled data are equivalent to resource predictions using tract data. To this end, 16 previous U.S Geological Survey assessments were studied. For each assessment, resources were predicted for one undiscovered mineral deposit in the assessment area. One set of predictions used pooled data, and another used tract data. The two sets of predictions were compared with an equivalence test, using the six assessment statistics that are commonly reported for mineral resource assessments. Practical equivalence is the condition that two corresponding assessment statistics are within a factor of 1.5 of one another. For each of 2 assessments, all 6 assessment statistics were practically equivalent. For both assessments, the assessment statistics from the pooled data, relative to the corresponding assessment statistics from the tract data, ranged from 1.30 times smaller to 1.03 times larger. For each of 14 assessments, 1 or more of the 6 assessment statistics were not practically equivalent. The assessment statistics from the pooled data, relative to the corresponding assessment statistics from the tract data, ranged from 26.6 times smaller to 5.53 times larger. The use of pooled data has been a standard procedure in the three-part approach since at least 1986. The 16 assessments in this study are not a representative sample of those prior assessments that used pooled data. So, it is inappropriate to use the study results to infer whether pooled data affected the resource predictions for those prior assessments.

Scientific Investigations Report↗
USGS2024

The U.S. Geological Survey National Water Quality Network—Groundwater—2023

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, eight of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,114 wells in the network.

conterminous United States↗
USGS2026

pySATSI: A Python package for computing focal mechanism stress inversions

We introduce pySATSI, a Python package for computing earthquake focal mechanism stress inversions. This algorithm can handle a wide variety of types of stress inversion problems with a single script and can duplicate many capabilities of preceding methodologies. We also add new capabilities that include spatiotemporally variable inversion grids, damped stress estimates for clusters with few or no focal mechanisms, and variable fault‐plane ambiguities that the user can assign to individual events. In addition, we added the ability to use damped stress inversions with fault‐plane ambiguity probabilities that are weighted by fault instabilities. Our algorithm is computationally efficient with faster runtimes than previous algorithms, scales well for large datasets, and can be easily parallelized.

Seismological Research Letters↗
USGS2024

Shallow lake, strong shake: Record of seismically triggered lacustrine sedimentation from the 1959 M7.3 Hebgen Lake earthquake within Henrys Lake, Idaho

We investigate a shallow lake basin for evidence of a large historic intraplate earthquake in western North America. Henrys Lake, Idaho is an atypical candidate for a lacustrine paleoseismic study given its shallow depth (~7 m) and low relief (≤2° slopes ). Here, we test the earthquake-recording capacity of this basin type by showing sedimentological evidence of the 1959 M7.3 Hebgen Lake earthquake within sediment cores, using anthropogenically produced 137 Cs activity to constrain timing. In addition to expanding the morphologic range of basins targeted for lacustrine paleoseismic studies, this work has implications for sediment response in dam-enhanced basins. Lack of sedimentological evidence for other earthquakes coupled with radiocarbon chronology reveals that the 1959 event is the only clearly recorded earthquake within Henrys Lake since the mid-Holocene. Henrys Lake offers a proxy for paleo-earthquake signatures within similar lacustrine environments and underscores the importance of further paleoseismic studies in the region.

Idaho↗
USGS1998

Satellite imagery of the north-central Gulf of Mexico, June 1993-May 1997

This CD contains imagery collected by the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar-orbiting weather satellites. The AVHRR provides almost daily coverage of a site at a resolution of approximately 1 km. The data types included are sea surface temperature (SST), water reflectance (REF), and a false-color infrared overview (FCI).

Alabama, Florida, Louisiana, Mississippi↗
USGS2026

Water table rise sustains carbon release from soils in wetland-dominated landscapes: An intact soil core study

Wetland-dominated landscapes influence carbon cycling through their potential to act as both carbon sinks and sources. Wetlands in low-relief landscapes have dynamic terrestrial-aquatic interfaces that change seasonally with variable surface water and groundwater levels. However, few studies have directly quantified dissolved organic matter (DOM) release and greenhouse gas (CO 2 , CH 4 ) fluxes from wetland soils along terrestrial-aquatic interfaces as they are seasonally re-saturated by groundwater. To estimate groundwater-mediated soil DOM and gas fluxes, we performed laboratory simulations of vertical groundwater rise on intact soil cores collected from four Delmarva bay wetlands located in the Mid-Atlantic United States. At each wetland, one core was collected from within the wetland basin and the other from the transitional zone at the basin edge. Cores were re-saturated with groundwater over 15 days and then kept fully saturated for an additional 25 days. Source groundwater, soil porewater, and exfiltrated surface water samples were collected and analyzed for pH, ORP, DOM concentration, and DOM optical indices. In both the wetland and transition zone cores, porewater DOM concentrations increased over the wet up and were sustained during prolonged saturation. Optical indices shifted from recently produced, microbial-like signatures towards aromatic, terrestrial-like signatures. Fluxes of CO 2 decreased as the duration of soil saturation increased and soil cores switched from CH 4 sinks to sources upon full soil core saturation. Results indicate that groundwater rise sustains carbon mobilization from soils in wetland-dominated landscapes, emphasizing the need to understand how climate-driven changes to groundwater dynamics may affect carbon fluxes along terrestrial-aquatic interfaces.

Delaware, Maryland↗