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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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USGS2024

Deep syntectonic burial of the Anthracite belt, Eastern Pennsylvania

Fluid inclusion microthermometry and Raman spectroscopy of fluid inclusions in quartz veins from the Pennsylvanian rocks of the Anthracite belt, eastern Pennsylvania support a deep burial model of coalification in favor of focused orogenic hot fluid flow. High-temperature (250 to 255 °C) trapping of CH 4 ± CO 2 saturated aqueous fluids and CH 4 ± CO 2 inclusions indicate fluid trapping at depths of 11.5 to 13.4 km under a cover of Pennsylvanian to Permian(?) syntectonic load. In the folded rocks to the south of the Anthracite belt, CH 4 ± CO 2 fluid inclusions indicate a sediment load that was up to 16.3 km thick. Re -equilibrated aqueous fluid inclusions from veins in Silurian through Devonian rocks give the same range of trapping conditions but a wide range of fluid salinities suggesting that folding, fracturing, and meteoric recharge resulted in the intermixing of fluids from throughout the stratigraphic succession.

Pennsylvania↗
USGS2024

Diel temperature signals track seasonal shifts in localized groundwater contributions to headwater streamflow generation at network scale

Groundwater contributions to streamflow sustain aquatic ecosystem resilience; streams without significant groundwater inputs often have well-coupled air and water temperatures that degrade cold-water habitat during warm low flow periods. Widespread uncertainty in stream-groundwater connectivity across space and time has created disparate predictions of energy and nutrient fluxes across headwater networks, hindering predictions of cold-water habitat resilience under climate change scenarios. Recently, annual paired air and water temperature signals have been harnessed to indicate stream water thermal sensitivity and the dominance of deep versus shallow groundwater influence, although the utility of diel air–water temperature signal metrics for hydrologic inference has remained unexplored. Here we analyzed two consecutive years of locally paired, air–water temperature data from 47 headwater stream sites in the Catskill Mountains, New York, USA, and discovered characteristic seasonal patterns in diel temperature signal sinusoid metrics (amplitude ratio, phase lag, and mean ratio) driven by shifts in streamflow generation mechanisms and stream network position. Hydrologic interpretations of observed patterns were supported by stream heat budget model scenarios and additional analysis of paired air–water temperature data from two streams in Shenandoah National Park, Virginia, USA, with well characterized stream-groundwater connectivity. We found that within smaller tributaries, streamflow generation transitions from runoff to groundwater dominance were driven by hillslope drying during seasonal periods of lower precipitation. This was evidenced by significant correlations (p < 0.01) between daily water:air temperature signal amplitudes (non-linear decreases of ∼ 50 %) and derived base-flow index at 22 of the 28 sites, indicating enhanced local groundwater influence on streamflow promotes decoupling of diel air–water temperature signals. Additionally, ratios between daily water:air temperature signal means were lower in tributaries (∼0.68) when compared to main-stem (∼0.8) sites, increasing linearly throughout the observational period. In conceptual stream heat budget models, groundwater inflow had minimal effects on daily phase lags (∼0.2 hr), but increases in fractional groundwater discharge (0–50 %) depressed daily amplitude (∼20 % to 50 %) and mean ratios (∼15 %), supporting the sensitivity of daily metrics to interpreted changes in seasonal groundwater contributions to streamflow. During observational periods (i.e., April through October 2021 and 2022), significant differences (p < 0.01) between tributary and main-stem air–water metrics occurred when base-flow contributions were highest (∼0.93 vs. ∼ 0.68), as sites lower in the network had daily temperature metrics dominated by stream channel thermal inertia, rather than local groundwater connectivity, showing enhanced air–water diel signal coupling during warmer, drier periods. Divergent air temperature coupling across the network was interpreted as being driven by distance from local groundwater source zones, additional lateral groundwater inflows do not contribute a meaningful fraction to channel discharge lower in the network. Given the growing footprint of stream temperature observations, diel air–water temperature signals can provide distributed metrics sensitive to upstream groundwater discharge. Consequently, these metrics can support ongoing efforts by resource managers and researchers seeking to forecast the resilience of cold-water habitat to climate warming and changing precipitation regimes in mountain headwater streams.

New York, Virginia↗
USGS1976

Solute transport and modeling of water quality in a small stream

An injection of chloride, sodium, and stable strontium was made at a constant rate for 3 hours into Uvas Creek, Santa Clara County, Calif., to determine the mass transport processes in a small stream. Five observation points were selected within a 610-metre reach of the stream below the injection site. Water samples were collected at the observation points during and immediately after the injection. A mathematical model of the stream was obtained by solving analytically and optimally the one-dimensional mass transport equation of the solutes in the stream. Comparison of field results with a simplified mathematical model indicates the dominance of convection in the behavior of sodium and chloride. The concentration of chloride and sodium can be closely simulated by the model. However, strontium cannot be well represented by the simplified model, which contains a first-order decay-type sink.

California↗
USGS2026

Remote compositional analyses of space-weathered lunar maria

Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.

Planetary Science Journal↗
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

Statewide surficial geologic map of Nebraska underscores Quaternary landscape evolution from the High Plains to the Central Lowland

Surficial geologic mapping in Nebraska has been conducted primarily at the 1:24,000 scale since the mid-1990s, although there have also been limited efforts to map generalized Quaternary and surficial geology within the state and the region. We compiled and evaluated disparate maps (1:24,000–1:1,000,000) and datasets—including geologic, soil and soil parent material, and geomorphic maps as well as LiDAR derivatives—to produce a single 1:500,000 scale surficial geologic map of Nebraska that is the first of its kind. This new map provides a coarse-scale surficial geologic map that will be incorporated into a nationwide U.S. Geological Survey Quaternary geologic map. It also reflects the variation and uniqueness of physical landscapes in the state, where the Great Plains and Central Lowland physiographic provinces meet, further developing a richer interdisciplinary understanding of regional geomorphology in the heart of North America.

Nebraska↗
USGS2024

Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications

The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.

Earthquake Spectra Journal↗
USGS2025

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

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

Planetary Science Journal↗