USGS Science⌕ Search

SEARCH · USGS Science

Results for “Arctic, Antarctic, and Alpine Research”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,661 records · Page 70Linked to original sources
USGS2025

Evolution of permeability and strength recovery of shear fracture under hydrothermal conditions

Geothermal energy is a clean and renewable resource that depends on the ability to move water through hot rock. In many locations, the ability to move water through rock requires the presence of extensive natural or human-made systems of fractures. However, these fracture systems are influenced by a variety of complex processes that occur at the temperature and pressure conditions found in geothermal reservoirs. To make geothermal systems more efficient, it is important to understand how these fractures evolve over time in response to these processes. This study explored how fractures in rock change under high-temperature and pressure conditions, like those found in geothermal reservoirs, through laboratory experiments and numerical simulations. In general fractures, tend to close due to pressure from the surrounding rock preventing the flow of water. One set of laboratory experiments revealed that fractures in granitic rock can weaken over time at elevated temperatures. These weak fractures can then slip slowly potentially keeping the fracture open for a longer period. This study also showed that at the highest temperature examined (250 °C) large differences between the chemical composition of the rock and the fluid moving through it could improve water flow temporarily likely due to the water dissolving parts of the rock. Flow rate predicted by models shows overall good agreement with the flow rate measured in our experiments but with some long time-scale variations that may be due to mechanical wear of the fracture surface. A second set of experiments found that, over the temperature range examined, the closure of fractures was caused by brittle failure driven by high stresses at points where fracture surfaces were in contact. This result suggests that fracture closure in geothermal reservoirs could be counteracted by maintaining high pore pressures. Additionally, we also tested a new method using electrical resistance to measure fracture closure in controlled systems with high precision.

Final Technical Report↗
USGS2026

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

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

Minnesota↗
USGS2025

Earthquake recurrence estimates for northern Caribbean faults from combinatorial optimization

We use combinatorial optimization to find the optimal spatial distribution of random samples of earthquakes (≥6.5) that minimize the misfit in target slip rates for all faults in the northeast Caribbean, and we derive magnitude-frequency relationships with uncertainties for these faults. Slip rates for many faults are derived from GPS block models, not direct measurements, because of their underwater locations. Predicted recurrence rates for eastern Hispaniola and Puerto Rico Trench faults are 220-450 yr for M7 and 3-5 kyr for M8, with maximum feasible magnitude of M8.2. The most frequent earthquakes with magnitudes ≥7.0 are predicted on the large upper plate strike-slip faults, Enriquillo (EF) and Septentrional Fault, commensurate with the historical record. Calais et al. (2023) suggested that shortening in western Hispaniola is accommodated on the offshore Jérémie and onshore Malpasse faults north and south of EF, instead of on terrestrial faults in western Hispaniola and EF. Because of our system-modeling approach, such a configuration predicts less frequent earthquakes on EF and on western Hispaniola and Muertos convergent zones. Recurrence times of a few 100s yr for M6.7 earthquakes is predicted on the submerged faults in Mona Passage, and infrequent M>7 earthquakes are predicted on the Virgin Islands faults.

Lesser Antilles↗
USGS2024

Geomorphic map of the Umatilla River corridor, Oregon

This map portrays the distribution of landforms along the Umatilla River in northeastern Oregon and covers a corridor 127 kilometers long from the confluence of the Umatilla River with the Columbia River upstream to Meacham Creek. The map encompasses the valley bottom and extends about 1 kilometer up the adjoining hillslopes. Map data are intended to support water quality and fisheries enhancement efforts pursuant to the First Foods, a resource-management approach that focuses on traditionally gathered foods including water, fish, big game, roots, and berries and calls attention to the reciprocity between people and the foods upon which humans depend. The Umatilla River drains about 6,300 square kilometers on the northwest slope of the Blue Mountains in northeast Oregon. Most of the drainage basin is underlain by Miocene basalt flows of the Columbia River Basalt Group. Younger, weakly lithified, late Miocene and early Pliocene gravel deposits of local origin (for example, McKay Formation) are mapped in a few places. Upland surfaces are mantled with windborne silt (loess) correlative with deposits elsewhere known as the Palouse Formation. Surfaces below an elevation of about 340 meters were inundated repeatedly by large Pleistocene glacial outburst floods, most emanating from glacial Lake Missoula in western Montana. In backflooded areas such as the lower Umatilla River valley, Missoula floods deposited extensive slack-water silt. Areas mapped as open water, active channel and tie channel, flood basin, valley bottom, and modified land constitute the geomorphic floodplain: the area subject to occasional inundation by the Umatilla River. Deposits and landforms within the floodplain are inset into Missoula flood deposits and hence postdate the 20–15-kilo-annum Missoula floods. Some floodplain deposits are no more than a few centuries old, as indicated by substantial erosion and deposition during the Umatilla River flood of February 2020, the largest since systematic measurements began in October 1903. Deposits and landforms of the floodplain are transient features within the longer-term incision of the Umatilla River into mid-Miocene flood basalts and younger gravel of the McKay Formation.

Oregon↗
USGS2025

Dietary bioavailability of uranium to a model freshwater invertebrate

Uranium (U) mining increases environmental exposures. Understanding how U is taken up by organisms can aid in evaluating the potential for bioaccumulation and toxicity. Although the importance of aqueous geochemical speciation is well recognized for U bioavailability after dissolved exposures, far less is known about the processes controlling U bioavailability after dietary exposures. This study characterizes the biogeochemical drivers of dietary U uptake in the freshwater snail Lymnaea stagnalis in laboratory experiments. Solids tested included benthic diatoms pre-exposed to dissolved U(VI), soils from contaminated U mine sites, and colloidal hydrous ferric oxide (HFO) synthesized in the presence of dissolved U(VI) or with U complexed by natural organic matter (NOM). Results showed that U was bioavailable from all solids. Uranium assimilation efficiency (AE), a proxy for dietary U bioavailability, varied among solids. AE was lowest for the U-contaminated soils (25 ± 17%) and highest for the U-laden diatoms (71 ± 13%). AE varied slightly among HFO preparations, suggesting modest influences of NOM and iron on U bioavailability. Increases in dietary U exposures reduced feeding rates, and the extent of feeding inhibition appeared inversely related to U bioavailability. The high U assimilation and range of bioavailability have implications for toxicity risks inferred without considering dietary uptake.

Environmental Science and Technology↗
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

Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes

Great subduction earthquakes ( M w ≥ 8.0) can generate devastating tsunamis by rapidly displacing the seafloor and overlying water column. These potentially tsunamigenic seafloor offsets result from coseismic fault slip and deformation beneath or within the accretionary wedge. The mechanics of these shallow rupture phenomena and their dependence on subduction zone properties remain unresolved, partly due to the sparsity of offshore observations of shallow megathrust earthquake deformation. Here, we analyze how offshore structure influences shallow rupture mechanics and slip partitioning using 3D dynamic earthquake simulations of the Cascadia subduction zone (CSZ) megathrust with and without variably dipping seaward- or landward-vergent splay faults in the wedge that sole into the megathrust. Resulting tradeoffs between splay and megathrust slip reveal structural controls on rupture partitioning, with greater splay slip leading to less shallow megathrust slip updip. Gently dipping and seaward-vergent splays host more slip than those with steeper, landward-vergent splays. To isolate the underlying mechanisms, we compare models with Andersonian and plunging principal stresses. Results suggest distinct static and dynamic processes control the dip- and vergence-dependence of splay rupture: static (mis)alignment relative to far-field tectonic loading favors slip on more optimally oriented, shallowly dipping splay faults. In contrast, dynamic stress interactions of an updip-propagating megathrust rupture front with the free surface and potential branch faults favor forward branching onto seaward-vergent splays and inhibit backward branching onto landward-vergent splays. Resulting seafloor displacements suggest splay fault structure may influence coseismic tsunami source processes, highlighting the importance of dynamically viable rupture scenarios in subduction hazard assessments.

Cascadia subduction zone↗
USGS2026

Simulation of groundwater flow to evaluate hydrogeologic controls on a PFAS plume, Coakley Landfill Superfund Site, Rockingham County, New Hampshire

Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), have been detected at combined concentrations above 2,000 nanograms per liter (ng/L) at groundwater seep locations near the Coakley Landfill Superfund site, in North Hampton, New Hampshire. The landfill was active from 1972 to 1985. An impermeable cap was placed on the landfill in 1998. The adjacent area to the Coakley Landfill has many water supply wells, and transport of PFAS compounds to the wells is a concern. Fracture anisotropy in the underlying bedrock aquifer complicates the understanding of PFAS transport because groundwater preferentially travels along fractures that may not align with the prevailing groundwater flow direction. In 2018, the U.S Environmental Protection Agency and the U.S. Geological Survey began an investigation of the groundwater flow from the Coakley Landfill site. This report describes the modification of a numerical groundwater-flow model for the local area around the Coakley Landfill and summarizes findings of the investigation. In addition, this report includes a brief description of PFOA and PFOS occurrence, a discussion of model construction, evaluation of model performance through calibration, and discussion of simulation results for two periods (before and after capping). Limitations are also discussed. Results show that simulated groundwater flow moves from the Coakley Landfill to the west and north. Advective transport modeling using particle tracking shows that groundwater from the landfill discharges primarily to streams to the west and north, and a small amount is transported to distal wells. Dilution of contaminants through advection and dispersion likely plays a role in whether PFAS compounds from the landfill will be detected above laboratory reporting levels at distal wells.

EarthArXiv↗
USGS2025

A framework for understanding the effects of subsurface agricultural drainage on downstream flows

Understanding controls on streamflow volume and magnitude is important to water resource management applications, such as critical water and transportation structure design and floodplain mapping. Changes in land use and agricultural practices, such as subsurface agricultural drainage, may be contributing to changes in streamflow characteristics. Subsurface agricultural drainage, also known as tile drainage, is the practice of installing drains in the subsurface of agricultural fields to improve productivity. Because of the complex interactions between subsurface drainage systems, precipitation, local soil conditions, and land management practices, it is difficult to determine how subsurface agricultural drainage affects downstream flow. Previously developed subsurface agricultural drainage conceptual models under dry, saturated, and winter conditions are summarized, and current literature on the effects of subsurface agricultural drainage on downstream flows, focusing on peak flow, non-event flow, and total flow to develop frameworks for discussing these systems is compiled. The effects that subsurface drainage has on hydrologic systems are expected to vary by site and are seasonally based on system design, soil type, moisture conditions, precipitation characteristics, and land conditions. Subsurface drainage can affect the magnitude of peak flow by converting surface runoff from a storm event to subsurface runoff. By increasing hydrologic connectivity of a catchment, subsurface drainage can increase non-event flow or the flow between two storm events, typically dependent on lateral flow through the subsurface and groundwater. Theoretically, by diverting water from groundwater recharge or by reducing water available for evapotranspiration, subsurface drainage may increase the total volume of flow. Precipitation changes may increase infiltration, excess overland flow, and flood risk regardless of the presence or absence of subsurface drainage.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗
USGS2025

Assessment of density pattern retention of generalized data for 1:100,000-scale United States topographic maps

Cartographic generalization reduces the complexity of geographic data to produce legible, smaller-scale displays that retain essential information and logical geographic patterns. Generalization is a vital process in topographic map production. An important challenge in this process is managing and evaluating consistency across scale in the density and spatial distribution of map features such as buildings, roads, streams, water bodies, and elevation contours. Density patterns in these features reflect underlying physiographic conditions, which include factors such as bedrock geology, tectonics, climate, and landforms. Assessments of an acceptable level of change in feature density patterns are critical to ensuring the readability, usability, and accuracy of generalized maps and data. Preserving realistic density patterns across mapping scales also supports sustainable development goals in cartography, by helping to prioritize and communicate the relative reliability of geospatial data at specific scales.

Conference Paper↗
USGS2025

Bayesian mapping of regionally grouped, sparse, univariate earth science data

Some earth science data are naturally grouped by region, and it is often desirable to map these data by region. However, if there are only a few samples within each region, then the map should be smoothed in an appropriate way to mitigate the problems that arise from having only a few samples. A smoothing algorithm based on a Bayesian hierarchical model is developed and presented in this report. This algorithm has several features that make it especially suitable for mapping earth science data: it can account for measurements that are censored, it can process multiple datasets with different measurement errors and different censoring thresholds, and it can calculate the uncertainty in any statistic that is mapped. The algorithm is demonstrated by mapping gold concentrations that are measured in streambed sediments in the Taylor Mountains quadrangle in southwestern Alaska.

Alaska↗
USGS2026

Cnidarian–algal partnerships structure bacterial communities during strobilation in Cassiopea xamachana

Cnidarian–algal (Symbiodiniaceae) symbioses rely on complex interactions among the cnidarian host, algal symbionts, and associated bacterial communities. In the upside-down jellyfish Cassiopea xamachana , the polyp-to-medusa transition (strobilation) requires the establishment of symbiosis with Symbiodiniaceae algal partners, yet bacterial community dynamics during this developmental process remain unknown. Here, we experimentally induced symbiosis in aposymbiotic polyps using four algal treatments: xenic Symbiodinium microadriaticum (native symbiont), xenic Breviolum minutum , antibiotic-treated B. minutum , and a photosynthetically impaired B. minutum mutant. We combined 16S rRNA gene sequencing with measurements of photosynthetic efficiency, asexual budding, and algal surface N-glycan profiles to characterize holobiont assembly during symbiosis onset and strobilation. Algal treatment structured bacterial communities in both algal cultures and polyp tissues. Our analyses identified a set of amplicon sequence variants that consistently distinguished strobilating polyps from non-strobilating aposymbiotic and mutant polyps, in addition to potential bacterial biomarkers associated with successful metamorphosis. Strobilation was associated with the enrichment of bacterial communities putatively involved in sulfur and nitrogen cycling, whereas non-strobilating aposymbiotic and mutant polyps were characterized by opportunistic bacteria and increased community variability. Together, these results reveal coordinated changes in algal physiology, surface glycan profiles, and bacterial community structure associated with successful strobilation in C. xamachana and support a model in which tripartite host–alga–bacteria interactions influence cnidarian life stage transitions.

ISME Communications↗
USGS2024

Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning

Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.

Michigan, Wisconsin↗
USGS2000

Natural attenuation of chlorinated volatile organic compounds in ground water at Area 6, Naval Air Station Whidbey Island, Washington

Natural attenuation is a viable alternative to pump and treat for meeting remediation objectives in the vicinity of the southern contaminant plume. The combination of historically low contaminant concentrations in ground water, a landfill cap that limits source area contributions, favorable conditions for degradation of VC, and a relatively long downgradient distance to potential receptors are all favorable for natural attenuation as a remediation alternative. Natural attenuation could effectively meet all but one remediation goal that extraction wells PW- 2, PW-4, PW-6, PW-7, PW-8 and PW-9 are currently being employed to meet. The goal of preventing migration of all VC across the site boundary could not be met by natural attenuation. Some VC would migrate south of the Navy boundary, but the potential for subsequent VC mineralization downgradient of the base and the existing institutional controls would result in minimal additional risk from using natural attenuation. In the western contaminant plume natural attenuation is not currently a viable alternative to pump and treat for meeting remediation objectives. There is a possibility that rates for reductive dechlorination of TCE and TCA could increase substantially if the plume was allowed to migrate beneath the Oak Harbor landfill, but there are not enough data to be certain of such an increase. TCA and TCE concentrations at the leading edge of the western plume need to be reduced to at least 25 and 40 µg/L, respectively, to be protective of potential downgradient receptors. Source area TCA and TCE concentrations have decreased substantially over the past ten years, and the extraction wells PW-3 and PW-5 in particular are removing a significant mass of contaminants from ground water, so natural attenuation may be a viable alternative for the western plume in the future. There would be some possible side benefits of using natural attenuation as an alternative to pump and treat in the southern contaminant plume. The first would be that the resulting decrease in the amount of treated water that would need to be recharged in the swale north of the landfill would result in less off-base migration of contamination across the western site boundary. The second benefit would be a substantial reduction in the amount of dissolved iron and manganese being extracted from the shallow aquifer and run through the treatment system. Removing that source of operation and maintenance problems would result in more effective containment and removal of contamination in the western contaminant plume. The most critical data gap identified in this evaluation is the paucity of contaminant chemistry information downgradient of the Navy boundary in the vicinity of the southern contaminant plume. Without such data, the behavior of the plume and the protectiveness of natural attenuation to downgradient receptors cannot be verified, and field attenuation rates for VC cannot be determined directly. The existing long-term monitoring plan would need to be reviewed and revised if natural attenuation is selected as a remedy for the contamination in the southern plume. In particular, additional performance monitoring wells may be required downgradient of the property.

Washington↗
USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗
USGS2025

Smectite-rich horizons in Inceptisols trigger shallow landslides in tropical granitic terranes

Puerto Rico was affected by >70,000 landslides in the wake of 2017 Hurricane Maria, and landslide prevalence was especially high in the Utuado region in the Cordillera Central. Landslide density was highest where soil parent material is granodiorite; landslide slip surfaces tended to be shallow (<60 cm), and often were mobilized rapidly and with long runout distances. This study combines field observations with soil mineralogy (bulk and clay fractions), soil geochemistry (bulk fraction), and soil strength as determined by field cone penetrometer testing (CPT) to test the hypothesis that clay-rich subsoil horizons function as slip planes when water-logged. Soil pits were excavated to depths of ∼200 cm in Ultisols on an undulating plateau and to ∼100 cm in Inceptisols on steep slopes (36-43 o ) that flank the plateau and cone penetrometer tests (CPT) were done within 2 m of the soil pit. Six pits were located adjacent to scarps from previous landslides, enabling analysis of soil profiles downward through extrapolated slip surfaces. Results from X-ray diffraction (XRD), X-ray fluorescence (XRF) and thermogravimetric analysis (TGA) indicate that soils are heterogeneous, often with subsoil horizons enriched in clay minerals and immobile elements (Al, Fe, Ti). Inceptisols on steep slopes often contain smectite-rich horizons at 30–60 cm depth that appear to function as slip surfaces; in other Inceptisols, such horizons are not present and landslide susceptibility is potentially lower. In Ultisols, soil mineralogy is dominated by kaolinite with minor halloysite, and increased kaolinite content at soil depths ≥80 cm at some sites suggests potential slip surfaces enhancing probability of landslides. The origin of clay-rich horizons appears to be (1) fractures in granodiorite that facilitate water flow and leaching, accelerating mineral dissolution during early weathering stages, and (2) smectite-rich buried soils under permeable colluvium likely deposited by a prior mass wasting event. Where clay-rich layers occur beneath more-permeable horizons, rapid infiltration then absorption of water in clay-rich subsoil horizons causes decreased shear strength and increased landslide susceptibility.

Puerto Rico↗
USGS2026

Lunar analog study using portable gamma-ray neutron detector: Radiochemical mapping of silicic-to-basaltic volcanic terrains in the San Francisco Volcanic Field, Arizona

Studying lunar silicic volcanism provides key insights into the Moon’s crustal evolution, magmatic processes, and volcanic history. The Lunar-VISE (Lunar Vulkan Imaging and Spectroscopy Explorer) mission will investigate the Gruithuisen domes, a unique lunar region hypothesized to have formed through silicic volcanism. Using instruments on a Firefly Aerospace lander and a Honeybee Robotics rover, Lunar-VISE will analyze mineralogy, geochemistry, and surface properties to determine the origin and evolution of the domes, with a gamma-ray and neutron spectrometer (LV-GRNS) among its payload instruments. In preparation for this mission, we conducted preliminary fieldwork using a handheld gamma-ray neutron detector with NaI(Tl) and Cs LiYCl :Ce (CLYC) scintillators. This study focuses on various rhyolitic and basaltic volcanic centers in the San Francisco Volcanic Field (SFVF) near Flagstaff, Arizona—specifically Sugarloaf Peak, Bonito Lava Flow, and Robinson Mountain, a region containing several well-characterized lunar analog sites. The SFVF was selected for this study due to its broad compositional diversity spanning basaltic to rhyolitic compositions, its well-preserved volcanic morphologies, and its extensive use in previous NASA field campaigns and astronaut training exercises, making it an ideal terrestrial laboratory for testing planetary exploration techniques. We measured natural radioactivity, specifically from potassium (K), thorium (Th), and uranium (U) and other elements in their decay chains, which serve as diagnostic tracers of magmatic differentiation and crustal evolution processes, to assess geochemical variability across compositionally diverse terrains. The detector’s sensitivity was assessed across varying concentration levels. Regionally averaged concentrations of radioisotopes were determined by gamma-ray spectroscopy at selected sites. Our measurements reveal significant compositional variations between sites, with Sugarloaf Peak (rhyolitic, silicic dome) exhibiting the highest average radioisotope concentrations (K: 3.29 ± 0.24 wt%, U: 14.35 ± 1.81 ppm, Th: 27.14 ± 2.43 ppm), while Bonito Lava Flow (K: 1.13 ± 0.08 wt%, U: 3.86 ± 0.52 ppm, Th: 7.52 ± 1.02 ppm), and Robinson Mountain (K: 1.46 ± 0.16 wt%, U: 5.59 ± 1.06 ppm, Th: 11.75 ± 1.98 ppm) show lower concentrations aligned with basaltic compositions. Gamma-ray fluxes were elevated by a factor of approximately three to four at Sugarloaf Peak relative to nearby basaltic terrains, consistent with expected geochemical differentiation patterns. Furthermore, at meter scales, proximity to geological features significantly affects measurements. Th concentrations adjacent to a cliff face at Sugarloaf’s base were 28% higher than values measured 3-5 meters away from the same feature, demonstrating localized compositional heterogeneity. Analysis of station-by-station measurements reveals that K, U, and Th concentrations show an elevation trend at Robinson Mountain and generally higher concentrations near Sugarloaf Peak’s summit, suggesting progressive magmatic differentiation and/or the presence of more evolved lithologies at higher elevations. By mapping these elements on Earth using GRNS, we aim to optimize measurement techniques for Lunar-VISE and similar rover-borne missions by demonstrating the applicability of portable GRNS instruments for planetary surface exploration in an analog environment.

Arizona↗
USGS2000

Water quality of selected springs and public-supply wells, Pine Ridge Indian Reservation, South Dakota, 1992-97

This report presents results of a water-quality study for the Pine Ridge Indian Reservation, South Dakota. The study was a cooperative effort between the U.S. Geological Survey and the Water Resources Department of the Oglala Sioux Tribe. Discharge and water-quality data were collected during 1992-97 for 14 contact springs located in the northwestern part of the Reservation. Data were collected to evaluate potential alternative sources of water supply for the village of Red Shirt, which currently obtains water of marginal quality from a well completed in the Inyan Kara aquifer. During 1995-97, water-quality data also were collected for 44 public-supply wells that serve about one-half of the Reservation's population. Quality-assurance sampling was used to evaluate the precision and accuracy of environmental samples. Ten of the springs sampled contact the White River Group, and four contact the Pierre Shale. Springs contacting the White River Group range from calcium bicarbonate to sodium bicarbonate water types. Two springs contacting the Pierre Shale have water types similar to this; however, sulfate is the dominant anion for the other two springs. In general, springs contacting the White River Group are shown to have better potential as alternative sources of water supply for the village of Red Shirt than springs contacting the Pierre Shale. Nine of the springs with better water quality were sampled repeatedly; however, only minor variability in water quality was identified. Six of these nine springs, of which five contact the White River Group, probably have the best potential for use as water supplies. Discharge from any of these six springs probably would provide adequate water supply for Red Shirt during most periods, based on a limited number of discharge measurements collected. Concentrations of lead exceeded the U.S. Environmental Protection Agency (USEPA) action level of 15 µg/L for three of these six springs. Five of these six springs also had arsenic concentrations that exceeded 10 µg/L, which could be problematic if the current maximum contaminant level (MCL) is lowered. Blending of water from one or more springs with water from the existing Inyan Kara well may be an option to address concerns regarding both quantity and quality of existing and potential sources. All nine springs that were sampled for indicator bacteria had positive detections on one or more occasions during presumptive tests. Although USEPA standards for bacteria apply only to public-water supplies, local residents using spring water for domestic purposes need to be aware of the potential health risks associated with consuming untreated water. One spring contacting the White River Group and two springs contacting the Pierre Shale exceeded 15 pCi/L for gross alpha; these values do not necessarily constitute exceedances of the MCL, which excludes radioactivity contributed by uranium and radon. Additional sampling using different analysis techniques would be needed to conclusively determine if any samples exceeded this MCL. Nine springs were sampled for selected pesticides and tritium. The pesticides atrazine, carbaryl, and 2,4-D were not detected in any of the samples. The nine springs were analyzed for tritium in order to generally assess the age of the water and to determine if concentrations exceeded the MCL established for gross beta-particle activity. Tritium results indicated two springs are composed primarily of water recharged prior to atmospheric testing of nuclear bombs and two other springs have a relatively large percentage of test-era water. The remaining five springs had tritium values that indicated some percentage of test-era water; however, additional sampling would be needed to determine whether water is predominantly pre- or post-bomb age. Of the 44 public-supply wells sampled, 42 are completed in the Arikaree aquifer, one is completed in an alluvial aquifer, and one is completed in the Inyan Kara aquifer. Water from the alluvial well is a sodium bicarbonate water type, water from Arikaree aquifer ranges from calcium bicarbonate to sodium bicarbonate types, and water from the Inyan Kara well is a calcium sulfate bicarbonate type. Of the 44 wells sampled, 28 (64 percent) tested positive for indicator bacteria in presumptive tests. Because these were single samples that generally were collected upstream from chemical treatment feeders, positive detections do not necessarily constitute exceedances of drinking-water standards. A single sample from an Arikaree well exceeded the MCL for arsenic of 50 µg/L. Arsenic exceeded 10 µg/L for six additional Arikaree wells and for the alluvial well and the Inyan Kara well, which could be problematic if the current MCL is lowered. The alluvial well also exceeded the secondary maximum contaminant level (SMCL) for dissolved solids, which is non-enforceable, and the action level for lead. The Inyan Kara well exceeded the SMCL's for iron and for manganese and the MCL of 5 pCi/L for radium-226 and 228 combined. Several Arikaree wells exceeded SMCL's for either pH, sulfate, dissolved solids, iron, or manganese. One Arikaree well exceeded the MCL of 4.0 mg/L for fluoride and another exceeded the MCL of 10 mg/L for nitrite plus nitrate. Ten Arikaree wells equalled or exceeded 15 pCi/L for gross alpha; however, these values do not necessarily constitute exceedances of the MCL, which excludes radioactivity contributed by uranium and radon. Additional sampling using different analysis techniques would be needed to conclusively determine if any samples exceeded this MCL. Eight wells, all from the Arikaree aquifer, equalled or exceeded the proposed MCL of 20 µg/L for uranium and 33 wells (75 percent) equalled or exceeded one-half of the proposed MCL. Although this standard has only been proposed, additional information regarding the extent of elevated uranium concentrations in the Arikaree aquifer, and the geochemical processes involved, may be beneficial. It was determined from analyses of uranium isotope data for five wells that the source of elevated uranium concentrations is naturally occurring, rather than anthropogenic.

South Dakota↗