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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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202 records · Page 6Linked to original sources
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

Total uncertainty quantification in inverse solutions with deep learning surrogate models

We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.

Journal of Computational Physics↗
USGS2026

A diatom-based quantitative sea-ice proxy for the Bering and Chukchi seas

Sea ice affects Earth's climate system on both regional and global scales. Its incorporation into climate can be used to achieve more accurate predictions of future climate. However, instrumental records of sea-ice concentration do not extend earlier than 1978. In an effort to extend this record, we constructed a proxy using the generalized additive model based on relative abundances of five easy-to-identify diatom species found in sediment samples across the Bering and Chukchi seas. Here we present the first quantitative diatom-based sea-ice proxy developed for Beringia. The developed proxy has been applied to two sediment cores in the Bering Sea ranging from 0 to 25.7 ka (HLY0204 51JPC) and 369 to 430 ka (IODP Exp 323 Site U1345) and one in the Chukchi Sea ranging from 2.7 to 10 ka (HLY0204 24JPC). The obtained reconstructions of sea-ice concentrations are similar, but not identical to previously published qualitative and nearby records based on other proxies. Because our results are quantitative, they can be incorporated into regional climate models. The proxy is publicly available as an R Shiny application (app) and can be applied to any diatom count from marine sediments in the region.

Bering Sea, Chukchi Sea↗
USGS2024

Uncertainty and spatial correlation in station measurements for mb magnitude estimation

The body‐wave magnitude (⁠⁠) is a long‐standing network‐averaged, amplitude‐based magnitude used to estimate the magnitude of seismic sources from teleseismic observations. The U.S. Geological Survey National Earthquake Information Center (NEIC) relies on in its global real‐time earthquake monitoring mission. Although waveform modeling‐based moment magnitudes are the modern standard to characterize earthquake size, is important because (1) in many cases, waveform modeling is not possible (e.g., low signal‐to‐noise events), (2) is applicable over a broad range of magnitudes, ∼M 4–7, and (3) there is a many decades‐long history of estimating magnitudes. We use the NEIC Preliminary Determination of Epicenters earthquake catalog to investigate the uncertainty in NEIC station measurements. We show that measurements are spatially correlated, which can bias event ⁠, and we describe an empirical relation between this spatial correlation and station‐to‐station distance. We further describe an approach to mitigate bias from the spatial correlation. Accounting for the spatial covariance of observations can change the event from −0.15 to 0.07 units (10th to 90th percentile) for smaller events (⁠⁠). These smaller events have the largest standard deviations ranging from 0.05 to 0.15 units (10th to 90th percentile).

The Seismic Record↗
USGS2026

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation↗
USGS1991

Reconnaissance of the occurrence of agricultural chemicals in ground water in Haywood, Lake, Obion and Shelby Counties, Tennessee

Data on the occurrence of agricultural chemicals in ground wafer in Tennessee are sparse. The surficial alluvial aquifer is an important source of domestic water supply in West Tennessee, and potentially is subject fo contamination from the application of agricultural chemicals in the area. Nineteen shallow wells completed in the alluvial aquifers in areas of high density agricultural use were sampled in the winter and again in the summer of 1988 to ascertain the occurrence of agricultural chemical in ground water. Although no triazine herbicides or organophosphorus insecticides were detected in any of the wells sampled, elevated nitrite plus nitrate (as nitrogen) concentrations were detected. Results from the winter sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 7.8 milligrams per liter with a median concentration of 2.6 milligrams per liter. Results from the summer sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 8.9 milligrams per liter, median, 2.5 milligrams per liter. The highest concentrations occurred in the shallowest wells, and, in one instance, in a shallow well near a heavily irrigated field.

Tennessee↗
USGS2025

Road salt collection and redistribution at an urban rain garden on sandy soil, Gary, Indiana

Rain gardens installed as green infrastructure to divert storm runoff from entering combined sewers also collect dissolved constituents and particulates. An urban rain garden in northwestern Indiana, USA, was continuously monitored from November 2019 to May 2021 to evaluate the fate of dissolved constituents entering the rain garden in runoff. Physical and chemical properties of soils in the rain garden were also monitored, along with underlying groundwater. Linear regression models relating specific conductance to chloride concentration indicated that the 0.0371-ha (3998 square feet) rain garden collected approximately 1490 kg (3285 pounds) of road salt from the surrounding 0.2228 ha (24,500 square feet) of impervious surfaces. Soils and groundwater were seasonally affected by road salt application but carryover from year to year was not indicated. Rain garden soil permeability (5.20 × 10 −5 to 9.72 × 10 −5 m/s) remained unchanged during the study period and soil organic carbon generally increased under native vegetation. The results suggest that a rain garden built on sandy soil can divert substantial quantities of runoff and dissolved constituents from combined sewers; however, chloride is transported to sub-infrastructure groundwater that eventually discharges to adjacent waterways with concentrations lower than those observed in runoff.

Indiana↗
USGS2025

Enhancing mineral systems exploration through geochronology, thermochronology, and isotope analysis: USGS Geochron and USGS Isotope databases

A mineral systems approach to mineral exploration provides a comprehensive framework for understanding ore deposit formation by examining the geodynamic, magmatic, hydrothermal, and sedimentary processes responsible for mineralization, alteration, and remobilization of economic mineral deposits. Temporal and thermal constraints on ore genesis are crucial for refining mineral system models and guiding predictive exploration strategies. Geochronology and thermochronology offer invaluable insights into the timing and thermal evolution of ore-forming processes, whereas isotopic analyses provide critical information on the source and geochemical history of ore-forming fluids. Combining these methodologies have proven highly effective for mineral exploration in regions like Australia, however, their combined application has been limited in the United States. To apply these tools to mineral systems-based exploration, the U.S. Geological Survey (USGS) has developed two products: (1) The USGS Geochron Database, and (2) the USGS Isotope Database. These databases provide centralized repositories of geo/thermochronological dates and data (Geochron Database) and both radiogenic and stable isotope data (Isotope Database) generated by the USGS and partners over the past decades. Integrating these datasets together and with traditional exploration approaches provides the mineral exploration community with powerful tools for determining the temporal and thermal histories of ore systems and identifying metallogenic source provinces.

Continental United States↗
USGS2024

The 3D Elevation Program—Supporting New Hampshire’s economy

Introduction The topography of New Hampshire ranges from the Coastal Lowlands to the Eastern New England Upland to the White Mountains region. High-quality statewide elevation data are useful in managing this very diverse landscape. For example, the short coastline, including the Great Bay estuary and the Hampton-Seabrook marshes, is of disproportionately high value to New Hampshire’s tourist economy. The vulnerability of the coast to the effects of sea-level rise underscores the need for accurate, high-quality nearshore topographic elevation data and offshore bathymetric data to effectively manage the coast’s valuable resources, which include important fisheries, habitat, and infrastructure. Another important use for accurate elevation data in New Hampshire is in the evaluation of flood hazards and their potential environmental and infrastructure effects. This evaluation includes mapping of inundation and sediment transport, and assessing the associated costs of flooding. Addressing this challenge requires detailed knowledge of both surface topography and inland bathymetry. Other important activities having a substantial economic element and needing accurate elevation data include geologic resource assessment and hazard mitigation, urban and regional planning, infrastructure and construction management, and cultural resources preservation and management. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional model of the Earth’s surface and aboveground features.

New Hampshire↗
USGS2026

Understanding the resource potential of natural hydrogen on Earth: Scientific gaps, uncertainties and recommendations

A comprehensive scientific research roadmap is essential to bridge knowledge gaps and deepen the understanding of key geological, geochemical, and geophysical aspects of natural hydrogen (H 2 ) as a potential new energy resource. This paper reviews major scientific uncertainties on natural H 2 , suggesting research priorities, as a guide for defining exploration strategies, techniques, and data interpretation. The uncertainties concern all phases of the natural H 2 cycle, from generation (source rocks) through migration (advection and diffusion) and accumulation (reservoir and cap rocks) to the application and interpretation of subsurface and surface geochemical and geophysical exploration techniques. Understanding H 2 sources and generation rates (the amount of H 2 generated by a given volume of rock over time) is crucial for determining whether a geological H 2 system operates as a short-term dynamic system with rapid H 2 production and release, or as a conventional gas system with long-term accumulations, analogous to petroleum reservoirs. Preliminary estimates for serpentinisation, radiolysis, and organic matter degradation suggest that H 2 generation is not inherently fast, especially for non-hydrothermal continental systems (crystalline basement of shields, ophiolites, peridotite massifs, sedimentary basins), and long-term accumulations, like those of fossil natural gas systems, represent the most likely scenario. The mechanisms of H 2 migration through geological formations require application of fundamental principles of fluid-flow physics, distinguishing advection and diffusion, as well as their forms (from gas-phase, bubble flows to aqueous solutions). Additional studies of H 2 accumulation and retention in subsurface reservoirs could improve understanding of mechanisms of H 2 migration by focusing on the rock fluid-bearing properties and the factors affecting H 2 preservation, such as the presence of cap rocks impermeable to H 2 , pressure conditions, residence times, and microbial or abiotic consumption. Advanced techniques, including reservoir modelling, flow simulations, 3D imaging (micro-CT) of H 2 -bearing rocks, and extraction and analysis of gas occluded in rocks, can provide insights into the stability and potential recoverability of H 2 accumulations. The interpretation of surface exploration techniques, including gas geochemistry, geophysics, and remote sensing, long employed in mineral and energy resource exploration, is now being adapted for natural H 2 studies, but challenges remain in the data interpretation. Distinguishing H 2 seepage due to geological degassing from H 2 produced near the surface by modern microbial processes or artificial sources, such as hammering or drilling for soil-gas sampling, drilling into aquifers, and corrosion in boreholes, is an essential step in exploration. The simple detection of H 2 in soils, even in morphological structures like sub-circular depressions or “fairy circles”, cannot be cursorily interpreted as a signal of natural H 2 seepage from a deep source. A holistic geochemical approach, including isotopic analyses of gases associated with H 2 , is recommended to distinguish among the variety of possible H 2 origins. Observations of H 2 in wells should be interrogated to rule out possible artifacts such as corrosion and drill bit metamorphism. The integration of multiple geophysical methods, including seismic, gravimetric, magnetic, and electro-magnetic surveys, is recommended to mitigate interpretation ambiguities regarding the structure of a subsurface H 2 system (source and reservoir rocks, including fluid and gas storage), due to the non-uniqueness of rock-specific physical properties.

Earth-Science Reviews↗
USGS2026

Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state

Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.

Louisiana↗
USGS2025

Geochemical processes related to mined, milled, or natural metal deposits in a rapidly changing global environment

The demand for metals and raw materials, such as nickel and copper, has been projected to expand in the coming decades, driven by the global energy transition, the need for green technologies, and expanding infrastructure. Consequently, the increasing extraction and production of mining waste can have adverse impacts on surrounding environments and human health. The aim of this thematic collection is to fill critical knowledge gaps in the present-day cycles of metal(loid)s from source to larger sinks, and the effect of environmental management, anthropogenic development, and climate change. Altogether, the studies have been conducted in different natural settings around the world and comprise investigations in laterites, a soil-medicinal plant system, watersheds, and banded iron formations, among others. The geochemical applications in tracing mineralization, its secondary products, and/or potential impact on the immediate environment are highly diverse with applied tools ranging from isotope tracers to major and trace element systematics. Particularly the use of rare earth elements, their patterns and anomalies are methods employed by several studies in this collection. We summarize the findings to offer a potential future direction for the use of geochemical tracing techniques in resource exploration in the context of climate change and environmental challenges.

Geochemistry: Exploration, Environment, Analysis↗
USGS2026

Uranium—Deposits, production and resources, market dynamics, and supply chain risks

Introduction Interest in nuclear power for the generation of electricity has risen with the increase in the need for more diverse baseload power, enhanced energy security, and the development of new technologies, such as small modular reactors (SMRs), which could provide power for remote areas, industrial applications, and artificial intelligence (AI) data centers. In 2024, the U.S. Department of Energy received $2.7 billion in congressional funding to bolster the domestic uranium production and nuclear fuel supply chain and address reliance on imports from foreign suppliers. In 2025, the U.S. Government issued several Executive and Secretary’s orders aimed at revitalizing the U.S. nuclear sector. If SMRs are to be as widely deployed in the United States and worldwide as envisioned, demand for uranium (nuclear reactor fuel) will likely increase. After the Fukushima nuclear accident in 2011, the market spot price of uranium began a decline, followed by a decrease in U.S. and global uranium exploration and mine development expenditures that led to a uranium supply deficit until 2020, when prices started to recover, prompting a resurgence in uranium exploration and development. In January of 2024, the uranium spot price rose to a 17-year high $106 (U.S. dollars) per pound of U3O8 (triuranium oxide, commonly known as “yellowcake”), which is expected to increase uranium exploration, mine development, and uranium production domestically and worldwide.

Fact Sheet↗
USGS2023

Stream sediment geochemistry in mineral exploration: A review of fine-fraction, clay-fraction, bulk leach gold, heavy mineral concentrate and indicator mineral chemistry

Stream sediment surveys support early-stage reconnaissance mineral exploration and regional assessment programmes, enhanced by recent improvements in analytical method detection limits, continuously improving mineral chemistry, and new approaches to the interpretation of geochemical data. Sediment surveys may be used to predict catchment basin lithology, mineralization type based on pathfinder geochemistry, and geological features based on indicator mineral chemistry. Sediment surveys that target a finer-fraction sediment sample led to the discovery of the La Colosa gold deposit, Colombia. The Batu Hijau porphyry Cu–Au deposit in Indonesia was discovered based on an anomalous clay-sized fraction sample 12 km downstream. In an arid region with poorly developed drainages and minor topographic relief, the Ag-base-metal Navidad District in Argentina was discovered with clay-fraction sediment geochemistry. Heavy mineral concentrate (HMC) sediment surveys that include mineral chemistry determinations have led to global diamond discoveries. HMC surveys contributed to discovery of the Ring of Fire Ni–Cu–PGE and chromite district, Ontario, Canada. Discoveries and geochemical mapping can assist advancement of the application of stream sediment geochemistry in those global areas for which lithologies and deposits are exposed. Stream sediment surveys continue to be one of the most cost-effective geochemical methods for covering large areas for mineral exploration.

Geochemistry: Exploration, Environment, Analysis↗
USGS2024

Streamflow depletion caused by groundwater pumping: Fundamental research priorities for management-relevant science

Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.

Water Resource Research↗
USGS2025

Characterization and validation of tidally calibrated strains from the Alto Tiberina Near Fault Observatory Strainmeter Array (TABOO-NFO-STAR)

Six horizontal borehole tensor strainmeters (TSM1-6) installed from Fall 2021 to Spring 2022 comprise the Alto Tiberina Near Fault Observatory Strainmeter Array (STAR), providing an unprecedented opportunity to investigate seismic and aseismic deformation from hazardous high- and low-angle normal faults in Italy. Prior to use in tectonic applications, they require in-situ calibration and correction for non-tectonic signals. We tidally calibrate the instruments, characterize the calibration uncertainty, and test the results against environmental and earthquake signals originating from local to teleseismic distances. The STAR sites demonstrably deviate from assumptions common to the standard manufacturer's calibrations, including negative areal coupling at TSM3-6. While the tidally calibrated strains have ~3-56% uncertainty, the calibrated dynamic strains show interstation precision and accuracy to nanostrain levels, and static coseismic offsets in the array footprint are within uncertainty. TSM3 records a complex series of strains that may arise from dynamically triggered near-borehole fracture slip and fluid flow that does not appear to affect its sensitivity to lower strain rate deformation. Future calibration improvement may be afforded with longer stable timeseries, particularly for TSM4. Overall, our analyses demonstrate expanded geodetic capability for detecting deformation in the Alto Tiberina Near Fault Observatory.

Alto Tiberina Near Fault Observatory↗
USGS2026

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

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

California↗
USGS2025

Drone-based radiometric surveys provide high-resolution mine waste characterization

Airborne radiometric surveys use passive geophysical techniques to characterize geochemical variations at or near earth’s surface. These methods have been used for a variety of mapping applications, including mineral resource evaluation. However, detailed characterization of smaller geologic targets, including mine waste features, requires flying at lower altitudes and with tighter line spacing than is feasible with traditional aircraft. Here, a small uncrewed aircraft system (sUAS) equipped with a radiometric sensor was used to acquire high-resolution gamma-spectrometry over small mine waste features and a low-grade stockpile in southwestern New Mexico. The sUAS radiometric system mapped local variability within each survey area and revealed ~2–10 m wide zones where radioelements K, Th, and U may be elevated 2–10× the surrounding material. Additionally, the sUAS radiometric data revealed radioelement variability across survey sites, which correlated reasonably well with variability seen in geochemical samples at each survey site, even though samples collected from individual sites showed high local variability. The sUAS data characterized local heterogeneity within mine waste and other small geologic targets at scales of a few meters to tens of meters, which is not possible with traditional crewed aircraft, and with continuity of coverage that is not possible with ground surveys, thus filling a key gap in geophysical survey spatial resolution.

New Mexico↗