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Results for “IEEE Transactions on Geoscience and Remote Sensing”

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

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1,665 records · Page 19Linked to original sources
USGS1995

Effects of waste-disposal practices on ground-water quality at five poultry (broiler) farms in north-central Florida, 1992-93

Waste-disposal areas such as chicken-house floors, litter stockpiles, fields that receive applications of litter, and dead-chicken pits are potential sources of nitrates and other chemical constituents in downward-percolating recharge water. Broiler- farms in north-central Florida are concentrated in a region where the Upper Floridan aquifer is unconfined and susceptible to contamination. Eighteen monitoring wells installed at five sites were sampled quarterly from March 1992 through January 1993. Increases in median concentrations of constituents relative to an upgradient well were used to determine the source of the nitrate at two sites. At these sites, increases in the median concentrations of nitrate as nitrogen in ground water in the vicinity of waste-disposal areas at these sites were: 5.4 mg/L for one chicken house; 9.0 mg/L for a second chicken house; 2.0 mg/L for a fallow field that received an application of litter; and, 2.0 mg/L for a dead-chicken pit. At the three remaining sites where the direction of local ground-water flow could not be ascertained, the sources of concentrations of nitrate and other constituents could not be determined. However, median nitrate concentrations in the vicinity of waste-disposal areas at these sites were: 45.5 mg/L for a set of two chicken houses; 3.0 mg/L for a stockpile area; and 2.1 mg/L for a hayfield that received an application of litter. The nitrate concentration in ground water in the vicinity of a field that had previously received heavy applications of litter increased from 3.0 mg/L to 105 mg/L approximately 4 months after receiving an application of commercial fertilizer. Increases in concentrations of organic nitrogen in ground water in the vicinity of waste-disposal areas may be related to the decomposition of litter and subsequent movement with downward percolating recharge water.

Florida↗
USGS2023

Slow slip detectability in seafloor pressure records offshore Alaska

In subduction zones worldwide, seafloor pressure data are used to observe tectonic deformation, particularly from megathrust earthquakes and slow slip events (SSEs). However, such measurements are also sensitive to oceanographic circulation-generated pressures over a range of frequencies that conflate with tectonic signals of interest. Using seafloor pressure and temperature data from the Alaska Amphibious Community Seismic Experiment, and sea surface height data from satellite altimetry, we evaluate the efficacy of various seasonal and oceanographic pressure signal proxy corrections and conduct synthetic tests to determine their impact on the timing and amplitude prediction of ramp-like signals typical of SSEs. We find that subtracting out the first mode of the complex empirical orthogonal functions of the pressure records on either the shelf or slope yields signal root-mean-square error (RMS) reductions up to 73% or 80%, respectively. Additional correction with proxies that exploit the depth-dependent spatial coherence of pressure records provides cumulative variance reductions up to 83% and 93%, respectively. Our detectability tests show that the timing and amplitude of synthetic SSE-like ramps can be well constrained for ramp amplitudes ≥4 cm on the shelf and ≥2 cm on the slope, using a fully automated detector. The principal limits on detectability are residual abrupt changes in pressure that occur as part of the transition to and from summer to winter conditions but are not adequately characterized by our seasonal corrections, as well as the inability to properly account for instrumental drift, which is not readily separated from the seasonal signal.

Alaska↗
USGS2025

Map of topographic lineaments interpreted as recent surface ruptures along the Bennett Valley and Southern Maacama Fault Zones, Sonoma County, California

This study documents lidar-illuminated topographic lineaments interpreted as evidence of recent surface fault ruptures and surface ruptures related to distributed deformation along the Bennett Valley Fault Zone and the southernmost Maacama Fault Zone in the northern San Francisco Bay area (fig. 1, on map sheet). Together, these fault zones form a structural connection across a right stepover between the main Maacama Fault Zone and the Rodgers Creek Fault, overlapping principal strands of the San Andreas plate boundary system north of San Francisco Bay (figs. 1, 2, on map sheet) that accommodate about a quarter of the ~40 millimeters per year of regional dextral tectonic slip (Parsons and others, 2013). Although much of the Bennett Valley Fault Zone is seismically active (McLaughlin and others, 2012; Sowers and others, 2010), only the north end of the fault zone (the “Spring Valley strand,” indicated on southern map panel of map sheet and labeled “D” in figure 2, on map sheet) was previously known to have youthful geomorphic expression and to displace Holocene deposits (McLaughlin and others, 2008; Sowers and others, 2010; Sowers and others, 2016). Holocene activity along the length of the Bennett Valley Fault Zone and southernmost Maacama Fault Zone, with possible implications for rupture propagation, continuity, and slip transfer, had not been identified. However, fault splays that project eastward from the Rodgers Creek Fault have been mapped and hypothesized to accommodate slip transfer to the Bennett Valley Fault Zone (Hecker and Randolph Loar, 2018). The generally subtle and distributed nature of surface-rupture evidence along the Bennett Valley and southernmost Maacama Fault Zones, and extensive vegetation cover, had left recent faulting previously unmapped along most of the zone. The map presented here represents a new compilation of inferred surface-rupture features detected using high-resolution topographic lidar data from an airborne lidar survey of Sonoma County, California (OpenTopography, 2014). These data, which enable subtle topographic features to be discerned, indicate that recent (likely Holocene) surface ruptures extend throughout the Bennett Valley and southernmost Maacama Fault Zones. The rupture-lineament map was created using a GIS (geographic information system) framework and is included herein as an image map at a scale of 1:36,000 and as digital datasets (included as supplemental information to this report). The mapping is intended to lay the groundwork for future studies designed to better characterize how plate-boundary slip is accommodated on this important and complex system of faults.

California↗
USGS2025

Geochemical evidence for the origin of late Quaternary loess, Seward Peninsula, Alaska

Loess is the most widespread surficial deposit in the state of Alaska. Although loess of last glacial age is common in mid-continental North America, records of last glacial loess in Alaska have been elusive. Here we report a record of last glacial loess on the Seward Peninsula, along with studies of a transect of loess localities also thought to date to the last glacial period. Highly diverse hypotheses on the origin of loess on the Seward Peninsula include local volcanic rocks and mountain ranges to the north and south, as well as offshore deposits. We present particle size and mineralogical and geochemical data that indicate that the most likely sources for loess in this part of eastern Beringia are glaciogenic silt particles of the Kobuk River and Noatak River, both of which drain the Brooks Range to the northeast. Northeasterly paleowinds were therefore responsible for loess on the Seward Peninsula. Such winds probably occurred during late summer or early autumn, when river discharge was at a minimum but temperatures were still above freezing. Northeasterly winds during the last glacial period are in good agreement with a recent paleoclimate model.

Alaska↗
USGS2025

Earthquake stress-drop values delineate spatial variations in maximum shear stress in the Japanese forearc lithosphere

Earthquake stress drop (Δσ) may increase with depth and stress in the brittle lithosphere. However, the range of uncertainty in Δσ and the lack of constraints on absolute stress make it difficult to establish whether they are correlated. Here, we investigate Δσ dependence on depth and maximum shear stress ( τ max ) based on ~11 years of seismicity in the northeastern Japanese forearc following the 2011 Tohoku-Oki megathrust earthquake. We interpret Δσ estimates computed using both individual spectra and spectral-ratio methods and find that Δσ exhibits a clear depth dependence within the seismically active upper ~60 km of the forearc lithosphere ( ~ 0.8 MPa per 10 km). We further compare Δσ values with quantitative τ max estimates from finite-element models of force balance. We find that median Δσ values increase with τ max in the brittle forearc lithosphere and that earthquake stress release is proportional to τ max . The dependence of Δσ on τ max explains the apparent depth dependence of Δσ and suggests that average Δσ values provide a relative measure of the stress at failure. In the northeastern Japanese forearc, Δσ values remained roughly constant in the decade following the Tohoku-Oki earthquake, suggesting negligible changes in failure stress in the forearc since the mainshock.

Communications Earth and Environment↗
USGS2025

Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration

Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model-data integration workflow to address uncertainty in groundwater response to beaver-induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning-based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down-valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down-valley underflow, from 2% during dry pond periods to 20% during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down-valley underflow, minimizes the effect of beaver-induced inundation on water quality. We emphasize the need for field-scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response.

Colorado↗
USGS2025

Analysis of the potential effects of Uzbekistan’s mineral endowment on the critical mineral supply of tungsten

Tungsten appears on the 2018 and 2022 U.S. Geological Survey critical mineral lists in part because of a very high global production concentration in China, which produces almost 83 percent of the world’s mined tungsten. Using known parameters and values from other tungsten mining operations, we created hypothetical scenarios in which three tungsten deposits in Uzbekistan are considered for development. Our results show that all three deposits are likely to be economically viable to develop under 2024 market conditions. If the three studied tungsten deposits were put into production, Uzbekistan could become the third-leading tungsten-producing country in the world and increase world output of tungsten by 2.7 percent. Putting these tungsten deposits in Uzbekistan into production could slightly reduce the tungsten global market concentration, therefore reducing the supply disruption potential for tungsten.

Open-File Report↗
USGS2024

Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea

We investigate the dynamic interactions between the Southern San Andreas Fault (SSAF) and a proximal normal fault (NF) beneath the Salton Sea in southern California. The NF, positioned near the SSAF terminus at Bombay Beach, exhibits 11–15 displacement events across 14 stratigraphic sequences, with a range of 0.2–1.4 m of vertical offset since ∼2–3 ka. Notably, four of these events may align temporally with SSAF earthquakes, raising questions about the possible interplay between the two faults. Utilizing dynamic rupture models, we analyze the coseismic interactions between the SSAF and NF, addressing under what conditions the SSAF induces slip on the NF. Our findings reveal that a suite of SSAF ruptures, particularly those propagating from north to south, can trigger slip on the normal fault and replicate observed vertical offsets. If the SSAF extends beneath the Salton Sea, earthquakes originating south of the NF intersection are less likely to trigger normal fault slip, although we cannot exclude this possibility. Some SSAF ruptures do not trigger discernible slip on the NF, rendering such events undetectable in the stratigraphic record. Our research contributes toward discussions regarding the seismic hazard in southern California, shedding light on the interplay between the SSAF and NF.

California↗
USGS2025

Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems

Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.

Alaska↗
USGS2024

Simulating present and future groundwater/surface-water interactions and stream temperatures in Beaver Creek, Kenai Peninsula, Alaska

In many places, coldwater ecosystems are facing increasing pressure from anthropogenic warming. This study examined stream temperatures and the water balance in the Beaver Creek watershed on the Kenai Peninsula in south-central Alaska—an area that is experiencing rapid warming. Low-gradient streams near the Kenai coast provide important spawning and rearing habitat for salmon but may be especially vulnerable to rising temperatures, because of long residence times, inflows from abundant riparian wetlands, and reliance on groundwater discharge that may also warm, or decrease in volume with rising evapotranspiration. In recent decades, observed maximum 7-day temperatures have consistently exceeded statistical (regression-based) projections. Here we simulate total streamflows and temperatures with a physics-based model that links the Soil Water Balance, MODFLOW 6 and SNTEMP simulation codes on a 7-day timestep. The model is based on existing data and groundwater levels, instream flows, and stream temperatures collected during 2019–23. Future climate scenarios were developed for 2023–50 from downscaled climate projections. Results indicate that groundwater discharge is about 64 percent of the total streamflow during the months of May through September. Total streamflow and groundwater discharge are expected to remain similar to current conditions through 2050. Stream temperatures are expected to rise; by midcentury, near the Beaver Creek mouth the model predicts 34 to 63 additional days per year with average weekly temperatures above 13 degrees Celsius, 14 to 81 additional days with average weekly temperatures above 15 degrees Celsius, and routine exceedances of 20 degrees Celsius during the warmest periods. Projected stream temperatures vary spatially. Areas of high groundwater inflows in the lower main stem and some tributaries may be most resilient to warming air temperatures during dry conditions. During storm events, groundwater-dominated tributaries may have the coolest stream temperatures.

Alaska↗
USGS2024

Cross section N–N' through the Valley and Ridge province of the southern Appalachian basin, from Greene County, west-central Alabama, to Bibb County, central Alabama

Introduction Geologic cross section N–N′ is the sixth in a series of geologic cross sections constructed by the U.S. Geological Survey to document and improve understanding of the geologic framework and petroleum systems of the Appalachian basin. Cross section N–N′ provides a regional view of the structural and stratigraphic framework of the Appalachian basin in the Valley and Ridge province in western and central Alabama; it spans approximately 69 miles (mi) (111 kilometers [km]). This geologic cross section is a companion to geologic cross sections E–E′ , D–D′ , C–C′ , I–I′ , and A–A′ that are located approximately 350 to 550 mi (563 to 885 km) to the northeast. Cross section N–N' complements earlier geologic cross sections through the Alabama part of the Appalachian basin. Although some of the other cross sections show more structural and stratigraphic detail, they are of more limited extent geographically and stratigraphically. Cross section N–N′ contains information that is useful for evaluating energy resources in the Appalachian basin. Although the Appalachian basin petroleum systems are not shown on the cross section, many of their key elements (such as source rocks, reservoir rocks, seals, and traps) can be inferred from lithologic units, unconformities, and geologic structures shown on the cross section. Other aspects of petroleum systems (such as the timing of petroleum generation and petroleum migration pathways) may be evaluated by burial history, thermal history, and fluid flow models based on what is shown on the cross section. In addition, cross section N–N′ may be used as a reconnaissance tool to identify plausible geologic structures and strata for the subsurface storage of liquid waste or for the sequestration of carbon dioxide.

Alabama↗
USGS2025

Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast

We use the Third Uniform California Earthquake Rupture Forecast Epidemic Type Aftershock Sequence model, which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and multi-fault earthquakes. A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was examined as well. We demonstrate that the probability of one-or-more loss exceedances (occurrence exceedance probability) is greater for the Poisson model because it has fewer seismically quiet time windows. The discrepancy between dollar loss estimates with a given exceedance probability is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 h and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window (aggregate exceedance probability) was therefore also examined, for which the Poisson model again implies higher risk at intermediate losses but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our study, in part because application specific details will likely be important, but our results highlight how full time dependence can be reckoned with once authoritative forecast models are made available.

California↗
USGS2025

Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses

Seawater intrusion threatens groundwater resources in coastal regions, including southern Baldwin County, Alabama, where the freshwater-saltwater interface dynamics remain poorly understood. To address this gap, this study uses combined physics-based and machine-learning models to quantify seawater intrusion caused by natural (storm surges) and anthropogenic (human activities) perturbations. The long short-term memory network and wavelet analysis were used to assess vertical aquifer vulnerabilities, revealing that the shallow part of the Coastal lowlands aquifer system (CL1) in the southern Baldwin County region is more susceptible to sea level rise and groundwater extraction than deeper aquifers. Based on these findings, a cross-sectional numerical model (physics approach) for the CL1 aquifer was developed to evaluate tidal and storm surge effects, using Tropical Storm Claudette (June 2021) as a case study. Results showed that tidal fluctuations had a minimal impact on the saltwater-freshwater interface location, whereas storm surges caused substantial inland movement, with effects lasting for nine months. The steady-state version of the three-dimensional (3D) physical model predicted seawater intrusion across the entire area, and convolutional neural network-based modeling further validated the model results. The 3D physical model was also applied to a smaller area to assess human impact on the saltwater interface due to two groundwater pumping scenarios (± 50% of the baseline pumping rate). Results revealed that a 50% increase in groundwater withdrawals caused seawater to advance ~ 320 m inland, whereas a 50% reduction led to a ~ 270-meter retreat. This study highlights the vulnerability of Alabama’s shallow coastal aquifers to seawater intrusion due to storm surges and human activities, and demonstrates that combining physics-based models with machine learning approaches can improve groundwater predictions, though its accuracy depends on the availability of site-specific data.

Alabama↗
USGS2025

USGS—An Unparalleled Scientific Asset

The U.S. Geological Survey (USGS) delivers information critical to powering our economy, managing our natural resources, and keeping Americans safe and healthy. 1 Mapping the Nation $21B Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B. $25.6B in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS. $13.5B in annual benefits is generated by the USGS's 3D Elevation Program. Securing America’s Energy Independence 44% USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation. 29.4B barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments. Protecting Americans’ Health and Safety $424B in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk. USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption. $4.5B is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property. Supporting National Security $3.1B The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list. Enhancing Our Lands and Waters $21B in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation. USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone. $45B USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy. Fostering American Prosperity $4.1T Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued. 45,000 metric tons Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply. Guarding American Food Security $70.2B USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production. $11.8B USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry. 1 Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.

General Information Product↗
USGS2025

Insights and strategic opportunities from the USGS 2024 Per- and Polyfluoroalkyl Substances (PFAS) Interagency Workshop

Introduction In 2021, the U.S. Geological Survey (USGS) published Circular 1490 titled, “Integrated Science for the Study of Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) in the Environment: A Strategic Science Vision for the U.S. Geological Survey” (Tokranov and others, 2021). Circular 1490 was created to be a resource for USGS scientists prioritizing and planning research related to per- and polyfluoroalkyl substances (PFAS) and to be a guide for developing partnerships with other scientists, State and Federal agencies, and stakeholders engaged in PFAS research and management and mitigation of the environmental and human-health effects of PFAS. This USGS PFAS Strategic Science Vision document was intended to be the foundation for a “living strategic vision,” periodically providing updates on the state of USGS PFAS research, emerging PFAS data gaps and needs, and progress on interagency and stakeholder PFAS partnerships and priorities. To meet this objective, the USGS planned to host an Interagency and Stakeholder PFAS Workshop every 2–3 years. During September 10–12, 2024, the USGS hosted the first Interagency and Stakeholder PFAS Workshop in Reston, Virginia. The Workshop brought together experts from other Federal agencies (U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, Food and Drug Administration, Department of Defense [Air Force, Army]), State agencies (Washington Fish and Wildlife, Virginia Department of Transportation), and academia (Harvard University, University of Maryland) to address key challenges relating to the measurement and modeling of PFAS and the implications for environmental health. Participants engaged in in-depth discussions centered around six pivotal topics related to PFAS: (1) sampling protocols, methods and interpretation; (2) environmental sources, source apportionment, and occurrence; (3) environmental fate and transport; (4) human and wildlife exposure routes and risk; (5) bioconcentration, bioaccumulation, and biomagnification; and (6) ecotoxicology and effects. Each topic had three breakout sessions. A recurrent theme of workshop discussions was how data on a nationwide scale for PFAS occurrence in various environmental matrices, including air, water, food crops, biota, soil, and streambed sediment could help to advance scientific understanding. Participants noted significant geospatial data gaps, particularly in the midwestern and southern United States and the Pacific Northwest. PFAS data collection tends to be more robust along the eastern seaboard and in California. Participants stressed how enhancing the integration of large and small datasets across various agencies could help to support national scale understanding of PFAS. To address these gaps, attendees suggested leveraging datasets from Federal entities like the USGS and the U.S. Department of Defense, State agencies, and municipal utility services to develop predictive contaminant detection and transport models. Improved coordination between water quality programs and USGS research could help to facilitate access to valuable data, leading to comprehensive databases that inform PFAS point (wastewater treatment plants and landfills) and nonpoint (runoff from land, atmospheric deposition, food packaging) sources, environmental transport mechanisms, environmental detection and concentrations, potential exposure routes, and health effects on different biota, including humans. A specific request was made to develop a map demarking the depth of modern (1953 or later) groundwater, which is susceptible to surface-derived anthropogenic (that is, human-made) contamination, based on tritium-age dating. Emphasis was placed on incorporation of hydrology, groundwater flow paths, groundwater–surface water interactions, and landscape factors in predictive statistical models as a step to improve contaminant source identification and tracking. Molecular fingerprinting approaches garnered attention as techniques to link specific PFAS mixtures detected in a sample to environmental sources and levels in biota (Dávila-Santiago and others, 2022). Integrating data from abiotic (that is, water, soil, and air) and biotic (that is, living organisms) systems identified as a research opportunity. For example, understanding the composition of soils and sediments, which include a mixture of mineral, plant, and animal components, could advance understanding of exposure pathways. The discussions highlighted opportunities to explore and understand the potential redistribution and biotic exposures of PFAS from biosolid and wastewater treatment plant effluent land application practices, in addition to atmospheric releases and discharges from landfill and wastewater treatment plants. Participants identified research gaps surrounding how these sources may contribute to contamination and may affect surrounding ecosystems, including a better definition of anthropogenic background concentrations. Moving forward, the collection of co-occurrence data was noted as a means to improve understanding of complex mixtures and to leverage companion modeling efforts focused on areas with high and low contamination levels to identify areas of concern and unaffected resources. Participants emphasized how centralized USGS databases and the establishment of sample-metadata archives can help to ensure that samples are preserved and accessible for future research. In conclusion, the workshop participants identified opportunities to bridge data gaps and improve measurement techniques, modeling frameworks, databases, and communication, to enhance the understanding of PFAS and their effects on environmental and human health. Upon completion of the workshop, participants indicated an interest in developing strategic data collection, modeling, and analytical approaches to address these challenges.

Open-File Report↗
USGS2026

Ground motions from finite faults with unknown geometry

Earthquake emergency response and loss modeling require accurate models of ground‐motion intensity metrics (IMs), such as those produced by ShakeMap. In the critical minutes and hours after an earthquake, however, knowledge of the earthquake source geometry limits the accuracy of these models, especially in areas where seismic instrumentation is insufficient to constrain the shaking intensity pattern. Previous attempts to overcome this limitation have centered on computing the mean distance metrics from a suite of assumed source geometries. That approach is inadequate with modern ground‐motion models (GMMs) because they typically include terms for the hanging wall effect, depth to top of rupture, and other nonlinear terms. Such approaches also propagate the distance uncertainty through the GMMs and may not properly allocate the additional uncertainty into the between‐ and within‐event components. Here we present Finite‐Fault SIMulation with Mixed Effects Regression (FFSIMMER), a method to address these limitations by computing IM distributions from a suite of rupture realizations that fully accounts for all geometry‐related GMM terms and allows for the separation of the between‐ and within‐event components of the total uncertainty. The accuracy of this method is limited by the available constraints on the source parameters. To address this, FFSIMMER can incorporate constraints based on knowledge of the source, such as the approximate strike and dip based on knowledge of the plate tectonics and focal mechanism of the earthquake. We demonstrate the improvement in accuracy that can be achieved with the 2025 M 7.7 Mandalay, Burma (Myanmar), earthquake by incorporating constraints on the range of plausible source parameters.

Bulletin of the Seismological Society of America↗
USGS2025

The 3D Elevation Program—Supporting Rhode Island’s economy

Introduction High-resolution elevation data are critical to applications of landscape modeling and planning, both of which have a significant effect on Rhode Island’s economy. In these and other enterprises, program managers, while aiming to strike a balance between accuracy and cost, strive to obtain the best available elevation data to help them address a range of issues. Programs focused on climate change, environmental management, transportation design and asset management, aviation navigation and safety, riverine ecosystem management, wildlife habitat characterization and management, shellfish aquaculture, and the management and mapping of forests, parks and recreation areas, soils, wetlands, and impervious surfaces are also among the critical applications that meet the State’s management needs and depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Rhode Island↗
USGS2025

Groundwater age estimates for the Mississippi River Valley alluvial aquifer based on tracer data collected during 2018–20

This study characterized groundwater age across the Mississippi River Valley alluvial aquifer (MRVA). Groundwater samples from 69 MRVA wells and 19 wells in Tertiary units of the Mississippi embayment aquifer system (MEAS) were analyzed for sulfur hexafluoride (SF 6 ), tritium ( 3 H), helium (He), and (or) carbon-14 of dissolved inorganic carbon ( 14 C). The age distributions of 89 samples were estimated by fitting lumped parameter models to processed tracer concentrations with the U.S. Geological Survey software TracerLPM. Mean ages of MRVA groundwater samples ranged from 12 to 22,000 years, with a median of 140 years. Mean ages of MEAS groundwater samples ranged from 230 to 52,000 or more years, with a median of 13,500 years. The spatial distribution of MRVA groundwater ages was found to be influenced by depth, inflow of groundwater from deeper units, and soil saturated hydraulic conductivity. In parts of the MRVA, the spatial distribution of MRVA groundwater ages was found to be influenced by annual recharge and (or) annual groundwater pumpage.

Alabama, Arkansas, Illinois, Kentucky, Louisiana, ↗