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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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1,687 records · Page 66Linked to original sources
USGS2021

Virginia and Landsat

From the shores of Jamestown and spreading north, south, and west, the lands that became the State of Virginia were some of the first in North America top experience rapid landscape change from European settlement. Imagery and data from the USGS Landsat series of satellites offer an unparalleled resource for the study, understanding, and preservation of Virginia’s land and water resources. From monitoring the health of water bodies to managing invasive species to planning for a range of climate change effects, the USGS National Land Imaging Program’s stewardship and public delivery of Landsat data have benefitted Virginians in myriad ways.

Virginia↗
USGS1976

Results of phytoplankton sampling at National Stream Quality Accounting Network stations in Montana, 1975 water year

Twelve National Stream Quality Accounting Network stations were operated in Montana during the 1975 water year. The network was established for the purpose of acquiring a base of hydrologic data for use by agencies engaged in water-resources planning on a national or regional scale. Among the characteristics analyzed were phytoplankton identification and cell counts. Samples consisted of composites of equal aliquots, collected at the center of each quartile of flow, using modified suspended-sediment samplers and sediment collection techniques. Identification and counting were done using the Sedgwick-Rafter cell method. Cell counts ranged from 21 cells per millilitre at Flathead River at Flathead, British Columbia to 27,000 cells per millilitre at Yellowstone River near Sidney. The class Bacillariophyceae was most abundant in both number and variety at all sampling sites. Anabaena and Aphanizomenon of the phyllum Cyanophyta were found at six stations and two stations respectively. These two genera of blue-green algae often become abundant in enriched waters resulting in nuisance conditions.

Montana↗
USGS1997

An optimized network for phosphorus load monitoring for Lake Okeechobee, Florida

Phosphorus load data were evaluated for Lake Okeechobee, Florida, for water years 1982 through 1991. Standard errors for load estimates were computed from available phosphorus concentration and daily discharge data. Components of error were associated with uncertainty in concentration and discharge data and were calculated for existing conditions and for 6 alternative load-monitoring scenarios for each of 48 distinct inflows. Benefit-cost ratios were computed for each alternative monitoring scenario at each site by dividing estimated reductions in load uncertainty by the 5-year average costs of each scenario in 1992 dollars. Absolute and marginal benefit-cost ratios were compared in an iterative optimization scheme to determine the most cost-effective combination of discharge and concentration monitoring scenarios for the lake. If the current (1992) discharge-monitoring network around the lake is maintained, the water-quality sampling at each inflow site twice each year is continued, and the nature of loading remains the same, the standard error of computed mean-annual load is estimated at about 98 metric tons per year compared to an absolute loading rate (inflows and outflows) of 530 metric tons per year. This produces a relative uncertainty of nearly 20 percent. The standard error in load can be reduced to about 20 metric tons per year (4 percent) by adopting an optimized set of monitoring alternatives at a cost of an additional $200,000 per year. The final optimized network prescribes changes to improve both concentration and discharge monitoring. These changes include the addition of intensive sampling with automatic samplers at 11 sites, the initiation of event-based sampling by observers at another 5 sites, the continuation of periodic sampling 12 times per year at 1 site, the installation of acoustic velocity meters to improve discharge gaging at 9 sites, and the improvement of a discharge rating at 1 site.

Florida↗
USGS2026

Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software

Models of the spatiotemporal evolution of earthquake slip, termed finite-fault models, are a critical component of rapid earthquake and tsunami response, earthquake forecasting, seismic ground-motion estimates, and studies of earthquake kinematics. Here, we detail a newly released finite-fault modeling software, Wavelet Inversion for SliP (WISP), in use at the U.S. Geological Survey’s National Earthquake Information Center (NEIC) and available to the public. WISP version 1.1.0 allows inversion of teleseismic body and surface waves, as well as local strong-motion, static and dynamic Global Navigation Satellite System, and satellite imagery (e.g., Interferometric Synthetic Aperture Radar) observations on single or multiple planar fault segments. The software is used in NEIC rapid response of earthquakes M w ≥ 7, generally resulting in a published model within the first few hours after the event origin time. The rupture location and dimensions are then used as inputs to downstream products to estimate earthquake shaking, predict loss, and model the likelihood of secondary hazards, namely landslides and liquefaction. WISP is also used in research studies to evaluate the characteristics of complex ruptures including multifault ruptures and earthquake doublets, among others. The WISP version 1.1.0 software release is composed of Python-wrapped FORTRAN code to accomplish the inversion procedure. A simple command line interface facilitates ease of use even for those with only a cursory knowledge of Python scripting. WISP version 1.1.0 includes a Jupyter Notebook tutorial demonstrating use of the software for modeling the 2015 M w 8.3 Illapel, Chile, earthquake. In parallel with the tutorial, we demonstrate the typical usage of the WISP software using the M w 8.3 Illapel earthquake example here.

Seismological Research Letters↗
USGS2025

Structural setting and geothermal potential of northeastern Reese River Valley, north-central Nevada: Highly prospective detailed study site for the INGENIOUS project

The northeastern part of the Reese River basin situated ~15 km southeast of Battle Mountain, Nevada, scored highly in the Nevada geothermal play fairway analysis (PFA) for hosting potential hidden geothermal systems. This site (also referred to as Argenta Rise) was therefore chosen for detailed study in the INGENIOUS project (INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems). The high PFA scores resulted primarily from favorable structural settings (e.g., fault intersections and pull aparts) with relatively high slip rates on Quaternary faults. The INGENIOUS project is utilizing additional parameters and more rigorous analytical techniques to further advance exploration at this site. This includes integration of geological (e.g., Quaternary fault mapping) and new geophysical datasets (e.g., gravity, magnetics, MT data, and five reprocessed seismic reflection profiles) to build a structural model and to identify specific favorable sites for potential geothermal upwellings. Two-meter temperature surveys were also conducted in the area (139 measurements). This part of north-central Nevada is characterized by systems of intersecting northerly and ENE-striking faults within the broader Humboldt structural zone, a poorly understood belt of ENE-striking faults and relatively high heat flow extending across northern Nevada. Kinematic analysis of exposed fault surfaces shows that ENE-striking faults have accommodated sinistral-normal slip, and normal slip characterizes N- to NNE-striking faults. Northeastern Reese River Valley lies within a broad left step between major ENE-striking fault zones on the northern flanks of the Argenta Rim and Shoshone Range and thus corresponds to a broad pull-apart in the ENE-striking sinistral-normal fault system. Notably, the nearby Beowawe geothermal system in Whirlwind Valley (with abundant sinter, hot springs, and a geothermal power plant) occupies a fault intersection in a relatively small left step in a major ENE-striking sinistral-normal fault and may serve as an analogue for a potential hidden system in northeastern Reese River Valley. Existing geological maps, high-resolution lidar, and seismic reflection data demonstrate that northeastern Reese River Valley is structurally complex with multiple intersections between the ENE- and N- to NNE-striking fault systems. Some of these fault intersections correspond to low resistivity anomalies, magnetic lows, and/or very subtle 2-m temperature anomalies, which may indicate hidden geothermal upwellings. Three-dimensional modeling and temperature-gradient drilling are planned to further evaluate these sites for geothermal activity.

Nevada↗
USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗
USGS2026

Groundwater budget for the Mountain Home area, southern Idaho, 2022–23

The U.S. Geological Survey, with funding from the Idaho Department of Water Resources, developed a groundwater budget for the Mountain Home area in southern Idaho for irrigation year 2023 (November 1, 2022–October 31, 2023). This study focused on the water balance across the Cinder Cone Butte Critical Groundwater Area (CGWA), Mountain Home Groundwater Management Area (GWMA), and the rest of the study area (RoSA), compiling data from various sources, including precipitation records, groundwater level measurements, metered groundwater pumpage data, surface water diversions and evapotranspiration (ET) estimates derived from remote sensing satellite imagery, and ground-based reference data. Key inflow components included recharge from applied surface water irrigation (which incorporates incidental recharge from irrigation practices and conveyance losses), estimated tributary streamflow, and estimated mountain block recharge. The key outflow components were groundwater pumpage for irrigation, municipal, industrial, and domestic uses, and ET. Recharge from applied irrigation and mountain block recharge were the largest inflows, and groundwater pumpage for irrigation was the largest outflow. The CGWA had a positive groundwater budget residual of 2,170 acre-feet (acre-ft), which contrasts with observed long-term groundwater level declines and historical trends of storage depletion. This positive residual is likely associated with unquantified outflows, including lateral groundwater flow out of the subregion, or other complexities, such as overestimated tributary contributions relative to the actual recharge for the 2023 water budget. The GWMA exhibited a positive residual of 56,563 acre-ft, primarily owing to recharge from applied surface water irrigation and areal recharge during a wetter-than-average year, which allowed irrigation entities to deliver more water from in-basin and out-of-basin reservoirs. The RoSA showed a large positive residual of 124,933 acre-ft. The interpretation of these positive residuals must account for significant uncertainties, including estimations of areal recharge, tributary streamflow (particularly losses and diversions), ET, the volume of surface water loss to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and the unquantified groundwater discharge to the Snake River. These uncertainties, in combination with the complex hydrogeologic controls on water movement and limitations of remotely sensed data, directly affect the accuracy of water availability assessments. Future data collection efforts would help reduce these uncertainties and support water resource management decisions in the Mountain Home area. Key efforts could include installing additional streamflow gaging stations (particularly to quantify tributary losses and gains and surface water losses to the Snake River), improving groundwater pumpage metering, and validating remotely sensed ET data with ground-based measurements. Furthermore, to better quantify unrepresented or highly uncertain fluxes, focused investigations on groundwater discharge to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and a more robust determination of the actual influence and volume of mountain block recharge would help refine future water availability assessments for the Mountain Home area.

Idaho↗
USGS2026

Ground-motion simulations for the 2024 Mw 4.8 Tewksbury, New Jersey, earthquake

Ground-motion simulations of notable earthquakes in the central and eastern United States are limited and typically assume one-dimensional (1D) Earth structure. In this study, we use a three-dimensional (3D) seismic velocity model to better constrain the depth and focal mechanism of the April 5th, 2024, moment magnitude 4.8 Tewksbury earthquake and investigate the spatial variability of earthquake ground motions and the effects of nearby sedimentary basins. We perform earthquake ground-motion simulations up to 0.5 Hz using the 3D spectral-element wave-propagation solver SPECFEM3D over a region 280-km wide by 260-km long by 77-km deep. Topography and subsurface geophysical structure are assigned using the U.S. Geological Survey National Crustal Model with a minimum shear-wave velocity of 200 m/s. We use earthquake time series from 13 broadband seismic stations in the region that have a uniform azimuthal distribution and epicentral distances ranging from 76 to 131 km to compare with synthetics and explore the effects of 1D versus 3D seismic structure on focal mechanism and depth solutions. Ground-motion intensity metrics are also presented relative to the NGA-East ground-motion models (GMMs) currently used in seismic hazard assessments for the region. We find that the 3D model, which reveals a wide spatial variability of period-dependent ground motions, yields better predictions of earthquake ground motions relative to the 1D model and the NGA-East ergodic ground-motion model, with 76 percent reduction of residual variance in observed ground motions averaged over 3-, 5-, 7-, and 10-second periods. Use of the 3D model to solve for a focal mechanism yields a shallower focal depth at 4 km and a shallower east-dipping focal plane relative to the U.S. Geological Survey regional moment tensor and Global Centroid Moment Tensor. Our study demonstrates that use of 3D seismic velocity models can improve estimates of earthquake focal mechanisms, ground motions, and seismic hazard.

New Jersey↗
USGS2026

Efficient physics‐informed ground‐motion simulations with reduced‐order models: CyberShake implications and high‐resolution site terms for southern San Andreas fault earthquakes

Recent advances in Probabilistic Seismic Hazard Analysis (PSHA) leverage physics‐based ground‐motion simulations to estimate seismic hazard, such as the CyberShake project. However, computational costs quickly escalate when performing PSHA for numerous faults or sites and can become prohibitively expensive. To reduce computational demands, CyberShake uses reciprocity and interpolates physics‐informed corrections from simulations conducted at fewer locations, but the accuracy of these interpolations remains poorly quantified. To quantify the interpolation accuracy, we derive high‐resolution, frequency‐dependent site terms for southern California and compare them with interpolated site terms using the CyberShake approach. We accomplish this by performing a set of earthquake point‐source simulations distributed along the nonplanar fault geometry for the southern San Andreas fault (SSAF) extending from Bombay Beach to Lake Hughes. Using SeisSol, we simulate three minutes of viscoelastic seismic wave propagation for these sources and store the horizontal‐component Green’s functions for 480,000 sites. We then use a scientific machine learning approach based on interpolated proper orthogonal decomposition to construct an accurate reduced‐order model of the Green’s functions to efficiently predict effective amplitude spectra (EAS) for finite‐source rupture models of SSAF earthquakes. Using minimum curvature interpolation with tension, as used in CyberShake, we compare the interpolated site terms against our high‐resolution site terms. We identify local discrepancies with EAS differing by up to a factor of approximately three. Furthermore, we identify locations where unexpectedly high or low ground motions are missed when using the interpolated dataset for these earthquakes. We estimate that our approach may be used within CyberShake to reduce the time‐to‐solution by a factor of 336 for the entire earthquake rupture forecast. Our analysis of physics‐based site terms provides more insight into the seismic hazard due to SSAF ruptures and guides future developments by combining high‐performance computing and reduced‐order modeling techniques for PSHA.

California↗
USGS2026

Using a temporary emigration model to estimate abundance of stream fishes from hybrid removal surveys with and without block nets

Monitoring programs are often faced with a decision to allocate resources into either robust spatiotemporal coverage to estimate a population index (e.g., not true abundance) or confirming closed sampling conditions (e.g., with block nets) for an unbiased population estimate at the cost of spatiotemporal coverage. However, making accurate and precise abundance estimates at robust spatiotemporal scales is possible when combining open and closed sampling designs with integrated modeling techniques. We used simulations and a case study of backpack electrofishing surveys in the Santa Ana River, California to test the efficacy of an integrated abundance model (temporary emigration model, TE) to estimate abundance of fishes using removal sampling methods with a hybrid sampling design (sampling with and without block nets during removal sampling). We found that the TE model performed well under most modeling scenarios (sample size, amount of closure violation, number of samples collected during closure), although at least a few samples with block nets were necessary for all parameters to be estimable. When applied to fish surveys in the Santa Ana River, we found that catch of the fishes fit to the TE model (Santa Ana Sucker, Arroyo Chub, Channel Catfish, Largemouth Bass, Yellow Bullhead) showed little evidence that the closure assumption was violated when block nets were not used. Additionally, we found that the abundance of non-native fishes negatively affected the abundance of the native Santa Ana Sucker, which was also found to adversely affect the native fish’s access to critical habitat consisting of gravel and cobble substrate. Our results indicate that the TE model presents a viable solution to common sampling problems that impact many monitoring programs, where precise and accurate population estimates can be made at large spatiotemporal scales even when most samples violate the closure assumption.

California↗
USGS2024

Interactive effects of salinity and hydrology on radial growth of bald cypress (Taxodium distichum (L.) Rich.) in coastal Louisiana, USA

Tidal freshwater forests are usually located at or above the level of mean high water. Some Louisiana coastal forests are below mean high water, especially bald cypress ( Taxodium distichum (L.) Rich.) forests because flooding has increased due to the combined effects of global sea level rise and local subsidence. In addition, constructed channels from the coast inland act as conduits for saltwater. As a result, saltwater intrusion affects the productivity of Louisiana’s coastal bald cypress forests. To study the long-term effects of hydrology and salinity on the health of these systems, we fitted dendrometer bands on selected trees to record basal area increment as a measure of growth in permanent forest productivity plots established within six bald cypress stands. Three stands were in freshwater sites with low salinity rooting zone groundwater (0.1–1.3 ppt), while the other three had higher salinity rooting zone groundwater (0.2–4.9 ppt). Water level was logged continuously, and salinity was measured monthly to quarterly on the surface and in groundwater wells. Higher groundwater salinity levels were related to decreased bald cypress radial growth, while higher freshwater flooding increased radial growth. With these data, coastal managers can model rates of bald cypress forest change as a function of salinity and flooding.

Louisiana↗
USGS2025

Airborne geophysical efforts for critical mineral systems mapping in the southern Midcontinent, USA

The increasing global demand for critical minerals to support energy and technological advancement has accelerated exploration and research efforts for these essential resources. Since 2019, the United States Geological Survey (USGS) Earth Mapping Resources Initiative (EMRI) has worked to modernize geologic mapping of the Nation to better understand its critical mineral resources. To further this initiative, the USGS has flown a series of high-resolution airborne magnetic and radiometric surveys over large areas of the southern Midcontinent. The surveys cover known critical mineral deposits and areas with the potential to host additional critical minerals based on the presence of one or more overlapping mineral systems. One aspect of EMRI emphasizes close collaboration between the USGS and the Association of American State Geologists, as well as other government and industry partners to leverage geophysical, geological, and geochemical expertise on both regional and local scales. The EMRI high-resolution airborne survey data provide new insights into the geophysical framework of the southern Midcontinent and its critical mineral endowment. Additionally, discoveries made from the data have directed new studies for critical mineral exploration.

southern Midcontinent↗
USGS2010

Divisions of geologic time—Major chronostratigraphic and geochronologic units

Effective communication in the geosciences requires consistent uses of stratigraphic nomenclature, especially divisions of geologic time. A geologic time scale is composed of standard stratigraphic divisions based on rock sequences and is calibrated in years. Over the years, the development of new dating methods and the refinement of previous methods have stimulated revisions to geologic time scales. Advances in stratigraphy and geochronology require that any time scale be periodically updated. Therefore, Divisions of Geologic Time, which shows the major chronostratigraphic (position) and geochronologic (time) units, is intended to be a dynamic resource that will be modified to include accepted changes of unit names and boundary age estimates. This fact sheet is a modification of USGS Fact Sheet 2007-3015 by the U.S. Geological Survey Geologic Names Committee.

Fact Sheet↗
USGS2026

Numerical modeling of Late Pleistocene to Holocene earthquake-induced progressive rock slope damage in the paraglacial Serpentine valley, Prince William Sound, Alaska

Landslides in deglaciating fjords pose a potential tsunami threat to nearby communities; however, processes contributing to long-term progressive rock damage and landslide conditioning remain poorly constrained in paraglacial settings. Here, we analyse the role of earthquake-induced rock mass damage over late Pleistocene to Holocene time scales, as a conditioning factor for modern landslides, using distinct element numerical modelling to assess spatial and temporal patterns of fracture propagation influenced by varying glacier thickness. Conceptualised numerical models were parameterised by in situ rock mass, glacial and topographic conditions in Serpentine valley, located in Prince William Sound, Alaska, where several large landslides are actively developing along the western valley wall. Results show that although rigid glacier buttressing reduces co-seismic rock mass damage, it does not suppress it completely, and damage occurs both above and below the glacier surface elevation. We demonstrate that topography, and especially steep slopes with topographic convexity, as well as preexisting damage of joint networks and faults inherited from tectonic and exhumation induced stresses, exert primary control on the location of new co-seismic damage. Simulations representing a simplified deglaciation sequence over the past 25 ka, with a series of 10 evenly spaced earthquakes, generated rock mass damage patterns that qualitatively match in situ landslide structural and kinematic observations at one instability in Serpentine valley. Our conceptual study helps clarify the role of repeated seismicity over glacial timescales as a long-term conditioning process for paraglacial rock slope failure, highlighting spatial and temporal patterns of progressive damage accumulation, with outcomes relevant for modern landslide hazard assessment.

Alaska↗
USGS2026

Light-dependent activity of deepwater sculpin (Myoxocephalus thompsonii) across substrates with and without predation risk

Light availability strongly influences predator–prey interactions in deepwater ecosystems, where visual constraints shape both foraging success and prey behavior. The behavioral response of deepwater sculpin ( Myoxocephalus thompsonii ) to siscowet lake trout ( Salvelinus namaycush siscowet ) was studied under ecologically relevant light intensities spanning several orders of magnitude typical of daytime downwelling light in the 20–100 m depth range of Lake Superior. Trials were conducted over varying substrates (gravel, sand, and black fabric). Deepwater sculpin showed a significant preference for gravel over sand and black fabric. In the absence of siscowet, sculpin movement frequency increased as light intensity decreased. Sculpin reaction distance to siscowet was influenced by both light and substrate. Reaction distance was shortest at low light intensities, peaked at intermediate light intensities (3.05 × 10⁹ to < 6.0 × 10⁹ photons m⁻2 s⁻1), and declined again at the highest light intensities tested. In the presence of siscowet, sculpin activity was suppressed at the upper end of the light range (≥ 6.0 × 10⁹ photons m⁻2 s⁻1). The greatest increase in movement occurred between 6.0 × 10⁹ and 3.05 × 10⁹ photons m⁻2 s⁻1, which corresponded to the range where siscowet prey capture declined, suggesting sculpin exploit this low-light window to move with reduced risk. Reduced activity in the presence of predators is common among cryptic species, and our findings suggest that sculpin restrict movement at higher light levels to avoid detection by siscowet.

Wisconsin↗
USGS2025

Mechanics and statistics of postseismic shaking

Analysis of two weeks of continuous post-seismic shaking after the 2019 M7.1 Ridgecrest, CA earthquake sequence using 4 nearby borehole seismometers reveals that continuous ground motions decay as Omori’s law in time and follow the Gutenberg-Richter distribution in logarithmic amplitude. The measured temporal decay in amplitudes agrees with predictions of the rate-and-state framework and indicates shaking amplitudes are proportional to the velocity of afterslip. Our ground motion-based statistical framework provides a basis to forecast shaking intensity in the minutes to hours after a large earthquake.

California↗
USGS2025

Evaluating mass flow meter measurements from chambers for greenhouse gas emissions from orphan wells and other point sources

This study evaluates the performance of a rigid gas flux chamber equipped with a mass flow meter (MFM) for measuring gas emissions from leaking orphan wells and similar pressure-driven gas point sources. We conducted a series of laboratory and field experiments to evaluate the sensitivity, stability, and dynamic range of an MFM chamber system and found an optimal method for sealing the chamber to the ground to isolate the emission source. From these results, we estimate the effects of different soil gas permeabilities on measurements and identify the uncertainty of environmental processes that can impact measurements. Simulations of an MFM chamber are compared to those of a dynamic flux chamber to contrast the data derived with both methodologies and illustrate the potential for measuring high variability leaks with the MFM chamber. Using a low flow resistance MFM and a chamber well-sealed to the ground, it is possible to measure leaks down to 1.08 x 10 -3 cubic meters per hour (m 3 h −1 ) (refenced to 25°/1 atm), corresponding to 0.77 grams per hour (g h −1 ) methane or 2.11 g h −1 carbon dioxide, with a mean uncertainty of 0.89 % relative standard deviation. Environmental processes such as heated gas inside the chamber from solar gain, wind blowing across the chamber vent, and changing humidity in the chamber, can cause variation in MFM measurements. Over 11 d of continuous monitoring under varying weather conditions, the standard deviation of the environmentally sourced signals was found to be 7.40 x 10 -3 m 3 h −1 (equivalent to or 5.27 g h −1 methane or 14.45 g h −1 carbon dioxide). Strategies to obtain the highest quality data from MFM chambers include burying the edges of the chamber below the surface sufficiently deep to seal the chamber edges against gas flow and soaking the dirt with water to lower the chances of escaping gases, while monitoring the gas flow and adjusting the chamber seal to achieve a maximum flow rate.

Atmospheric Measurement Techniques↗