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USGS2024

The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 ( m / z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r 2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r 2 = 0.93), praseodymium (Pr) (r 2 = 0.94) and samarium (Sm) (r 2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Journal of Geochemical Exploration↗
USGS2026

Evolution of arsenic speciation during thermal treatment simulating wildfire heating in arsenic-rich sediments

Understanding arsenic transformations during wildfires can help better constrain the environmental impacts of increased wildfire intensity, frequency, and burned area. Previous studies have monitored the evolution of metal(loid) speciation at specific time/temperature endpoints, hampering the comprehension of the dynamic transformations of metal(loid)s during wildfires. Here, a novel approach, namely in situ time-resolved X-ray absorption near edge structure (TR-XANES) spectroscopy, was used for the first time to monitor the heat-induced redox transformations of arsenic (As) in two As-rich sediments with different characteristics. No arsenic transformations were observed in either sediment at room temperature or when the sediments were heated to a maximum temperature of 400 ºC. When heated to a maximum temperature of 600 or 700 ºC, As underwent complex, dynamic, and partially reversible redox transformations, the extent of which varied with sediment properties, initial As speciation, and heating temperature and duration. In the case of sediments initially containing As(V) and a low sulfide/sulfate ratio, the As(V) was reduced to As(III) over a short period of time, followed by immediate reoxidation of As(III) to As(V). The extent of the transient As reduction increased with increasing maximum temperature. The final As speciation at the end of the heating experiment was not substantially different from that at the beginning of the experiment. In contrast, in sediments that were best described by a more complex combination of reference compounds (As(V) coprecipitated with or adsorbed on iron oxide, arseniosiderite, arsenopyrite) with a high sulfide/sulfate ratio, As(V) phases were reduced to As(III) and As(III) was further reduced to As(-I) (at 700 ºC, only), followed by delayed reoxidation of As(-I) to As(III) (at 700 ºC, only) and reoxidation of As(III) to As(V). Approximately 9% and 26% of all As remained as As(III) ( i.e., was not reoxidized to As(V)) at the end of the experiment when heated to a maximum temperature of 600 and 700 ºC, respectively, which is higher than the relative abundance of As(III) in the native sediment. These fire-induced As transformations can potentially enhance As mobilization to surface water and groundwater, posing risks to environmental and human health.

California↗
USGS2024

Imaging of seismic discontinuities using an adjoint method

For imaging of seismic discontinuities at depth, reverse time migration (RTM) is a powerful method to apply to recordings of seismic events. It is especially powerful when an extensive receiver array, numerous seismic sources, or both, permit adequate reconstruction of incident and scattered wavefields at depth. Reconstructing either the incident or scattered wavefield at depth becomes less accurate when relatively few recordings of seismic events are available. Here we explore an inverse scattering approach to imaging discontinuities based on an adjoint method, employing sensitivity kernels (Frechet derivatives) that represent jumps in material properties across seismic-discontinuity surfaces. When combined with ray-based requirements on scattering geometry, it constitutes a powerful approach to determining the locations and amplitudes of the discontinuities, recovering only those properties that can be resolved by a spatially limited source and/or receiver distribution. This is illustrated by synthetic examples with local sources followed by a field example in a subduction zone setting

Washington↗
USGS2025

Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020

Frequency analysis on annual peak streamflow (hereinafter, peak flow) is essential to water-resources management applications, including critical structure design (for example, bridges and culverts) and floodplain mapping. Nonstationarity is a statistical property of a peak-flow series such that the distributional properties (the mean, variance, or skew) change either gradually (monotonic trend) or abruptly (shift, step change or change point) through time. Not incorporating or accounting for observed nonstationarity into peak-flow frequency analysis might result in a poor representation of the true probability of large floods and thus misrepresent the actual flood risks to life and property. This report summarizes how hydroclimatic variability might affect the temporal and spatial distributions of peak-flow data in the State of Montana (and northern Wyoming) and is part of a larger study to document peak-flow nonstationarity and hydroclimatic changes across a nine-State region consisting of Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flows. This study was completed in cooperation with the Montana Department of Natural Resources and Conservation. The purpose of this report is to characterize temporal and spatial patterns of nonstationarity in peak flows and hydroclimatology in Montana and northern Wyoming. In this evaluation, peak-flow, daily streamflow, and model-simulated gridded climatic data were examined for monotonic trends, change points, and other statistical properties that might indicate changing climatic and environmental conditions. This report includes background information on the study area, the history of U.S. Geological Survey peak-flow data collection and frequency analysis in Montana, and the review of research relating to hydroclimatic variability and change in Montana. This study might help provide a framework for addressing potential nonstationarity issues in peak-flow frequency updates that commonly are completed by the U.S. Geological Survey in cooperation with other agencies throughout the Nation. The analytical structure of this study includes analyses of monotonic trends and change points in numerous hydroclimatic variables in assigned 30-, 50-, 75-, and 100-year analysis periods. For Montana and part of Wyoming, the 30-, 50-, 75, and 100-year analyses included 157, 70, 48, and 12 streamgages, respectively. For those streamgages, nonstationarities were analyzed in the following variables: (1) climatic variables, including annual and seasonal (winter, spring, summer, and fall) temperature and precipitation; (2) daily streamflow variables, including the annual center of volume duration, annual center of volume median, and peaks over threshold with a mean of four events per year; and (3) annual peak-flow variables, including peak-flow timing and magnitude. A likelihood approach was used to express statistical confidence and assign the nonstationarity results as likely upward or downward (highest statistical confidence), somewhat likely upward or downward (less statistical confidence), or about as likely as not (little statistical confidence; hereinafter, neutral). For the nonstationarity analyses of the climatic, daily streamflow, and peak-flow variables, the results are presented in detail and discussed with respect to statewide patterns and geographic variability. For each of the 30-, 50-, and 75-year analyses, peak-flow change-point and monotonic trend analyses were compiled for streamgages classified with likely downward or likely upward trends. For those streamgages, the associated basin characteristics and nonstationarity results for peak-flow timing, daily streamflow, and climatic variables were investigated and statistically compared to discern associations among other variables that might contribute to the peak-flow nonstationarity results. The 50- and 75-year peak-flow nonstationarities identified in this study are mostly downward, in association with mostly upward temperature and potential evapotranspiration:precipitation monotonic trends. For the 50-, 75-, and 100-year analyses, the peak-flow change points are predominantly downward and are concentrated in the 1970s and 1980s, which indicates general consistency among the longer trend periods. These findings are in association with substantial research documenting globally rising temperature and atmospheric greenhouse gas concentrations that might be largely attributed to anthropogenic activities. Anthropogenic effects might represent long-term (on the order of several decades to more than a century) climate changes that might happen within highly variable natural climate fluctuations. Several paleo studies in the north-central United States have indicated that hydroclimatic extremes (that is, low- and high-streamflow conditions) before European settlement have been outside of extremes since the 1900s. Depending on the interactions of anthropogenic effects and natural climate variability, extreme high-streamflow conditions might occur in the future, even in the presence of long-term downward peak-flow trends.

Montana, Wyoming↗
USGS2025

Memory and jamming in fault zone sediments

Many subsurface processes involve transitions in granular material states, from arrested to creeping to flowing. Experiments and frameworks for idealized systems reveal that granular fabrics develop during shearing, co-evolve with applied stress, and govern such transitions. We use microtomography to test whether fabrics at two San Andreas fault sites reflect slip history and whether idealized frameworks extend to nature. Near-surface sediments within the fault zone transition between deformation patterns over the seismic cycle, including bulk/localized grain re-arrangements, individual grain fracturing, and localized zones of fracturing. Aseismic and co-seismic shearing produce distinct preferred grain orientations. Co-seismic fabrics can be preserved after centuries of aseismic strain, aseismic fabrics may be overprinted, and grain size and coordination number influence the fabrics. Idealized frameworks, namely anisotropic critical state theory, frictional jamming, and material memory, can explain our observations, and fault zone sediments likely undergo cycles of memory creation and erasure that influence rigidity spatiotemporally.

California↗
USGS2000

Ground-water quality atlas of Oakland County, Michigan

The U.S. Geological Survey (USGS), in cooperation with Oakland County Health Division (OCHD), collected 140 water samples from 38 wells in Oakland County during 1998 to better understand ground-water quality. OCHD had observed temporal variations in concentrations of various constituents, so two additional sets of samples were collected to evaluate potential short-term variability related to sample collection procedures and long-term seasonal variability. Replicate samples from 28 wells were analyzed in the Michigan Department of Environmental Quality (MDEQ) Drinking Water Laboratory to compare MDEQ’s analytical results to those obtained from the USGS National Water Quality Laboratory. Several additional databases describing population, land use, water supply, soils, geology, and flows of ground water and surface water are presented in the first part of the report to assist in interpreting the water-quality data. Maps created from these databases are provided in the first portion of the report as an extension of the study-area description. The U.S. Environmental Protection Agency (USEPA) has established Maximum Contaminant Levels (MCL) and Secondary Maximum Contaminant Levels (SMCL) for which samples were analyzed in this study. Water from the 38 wells sampled by the USGS did not exceed the SMCL or MCL for sulfate, fluoride, or nitrite. However, water from 26 wells exceeded the SMCL for iron, water from 12 wells exceeded the SMCL for manganese, and water from 12 wells exceeded the SMCL for dissolved solids. Water from two wells exceeded the MCL for nitrate, although nitrate concentrations in water from most wells was below the detection limit. Water from seven wells exceeded the SMCL for chloride, and water from all wells contained detectable concentrations of chloride. Water from five wells exceeded the MCL for arsenic, and most of the wells sampled contained detectable concentrations of arsenic. These five wells were identified from previous MDEQ analyses to have elevated arsenic concentrations, and were sampled to obtain additional chemistry information. Replicate samples were collected from 26 of the 38 wells for analysis at the MDEQ Drinking-Water Laboratory to compare the results with the USGS National Water Quality Laboratory. The results of the replicate analyses indicate close agreement between the laboratories, with mean differences for nitrate, chloride, and arsenic of 0.10 milligrams per liter (mg/L) as nitrogen, 6.8 mg/L, and 0.0008 mg/L, respectively between the USGS and MDEQ analyses. Potential health effects associated with ingesting nitrate, chloride, and arsenic are provided with the water-quality data, along with references for further information.

Michigan↗
USGS2025

The Long Island Sound and Watershed Metadata map application

The Long Island Sound and its watershed encompass an area of about 17,000 square miles and include the Connecticut, Housatonic, and Thames Rivers, which all drain to the sound. Dozens of organizations from government agencies, nonprofits, and Tribal Nations have developed projects and monitoring programs to analyze and protect the water resources of the watershed and sound. The abundance of data and lack of an existing searchable index require a centralized metadata repository to allow users to find water resources data more efficiently. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and the Long Island Sound Study, has created an interactive map application to visualize and search for metadata information across organizations working to monitor and protect the Long Island Sound.

Connecticut, Massachusetts, New Hampshire, New Yor↗
USGS2025

Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA

Society is fundamentally dependent upon commodities that are used in end-use products for the aerospace, defense, energy, telecommunication, and transportation sectors, resulting in centuries of mining to supply these commodities and materials. Waste from these mining operations can remain on the landscape indefinitely, but there is a lack of national understanding of the distribution and scale of such waste features. The renewable energy transition will continue to increase demand for critical minerals and will result in increasing volumes of mine waste on the Earth’s surface. Reprocessing mine waste can reduce environmental risks and recover needed commodities to match growing demand for societal growth. Therefore, understanding the approximate abundance of commodities that may be available for recovery within mine waste features can be an important piece of domestic critical mineral supply.

Arizona, Colorado, New Mexico, Utah↗
USGS2000

Stormflow chemistry in the Santa Ana River below Prado Dam and at the diversion downstream from Imperial Highway, southern California, 1995-98

The Santa Ana River drains about 2,670 square miles of the densely populated coastal area of southern California, near Los Angeles. Almost all the flow in the river, more than 200,000 acre-feet annually, is diverted into ponds where it infiltrates and recharges underlying aquifers. About 2 million people are dependent on these aquifers for water supply. Stormflow in the Santa Ana River is considered a source of "high-quality" water suitable for use as a source of ground-water recharge. To test this assumption, stormflow samples were collected at two locations--below Prado Dam and at the diversion point downstream from Imperial Highway--for 12 winter storms between 1995 and 1998. Nitrate concentrations decreased during stormflow from a median concentration of 7.8 milligrams per liter in base flow to concentrations less than 1 milligram per liter in some large storms. Concentrations of chemically reduced forms of nitrogen (nitrite, ammonia, and organic nitrogen) increased during stormflow and are the predominant forms of nitrogen in large stormflows. Dissolved organic carbon (DOC) concentrations increased from a median concentration of 4.6 milligrams per liter in base flow to more than 20 milligrams per liter in some stormflows. Concentrations of DOC were especially high during the first storm of the rainy season, and large increases in DOC concentrations were measured even as a result of small early season storms that did not cause large increases in streamflow. DOC present during early season stormflow had less ultraviolet absorbance at 254 nanometers (UV 254 ) per unit of carbon than did DOC from late season stormflows. DOC in water held in storage behind Prado Dam had the highest UV 254 absorbance per unit of carbon. Maximum pesticide concentrations in stormflow did not exceed U.S. Environmental Protection Agency Maximum Contaminant Levels. Most pesticide concentrations were less than 1 microgram per liter and less than the detection limits obtained using standard drinking water analyses. Increases in concentrations of pesticides such as diazinon, malathion, and chlorpyrifos in stormflow result from runoff from urban areas downstream from Prado Dam. In general, large late season stormflows have the most pesticide detections of all stormflows sampled. Concentrations of methyl tert-butyl ether (MTBE), a gasoline additive, during base flow were as high as 0.9 microgram per liter and concentrations decreased during stormflow. Like pesticides, the concentrations did not exceed the U.S. Environmental Protection Agency Maximum Contaminant Levels for MTBE.

California↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS2025

Overcoming the data limitations in landslide susceptibility modelling

Data-driven models widely used for assessing landslide susceptibility are severely limited by the landslide and environmental data needed to create them. They rely on inventories of past landslide locations, which are difficult to collect and often nonrepresentative. Furthermore, susceptibility maps are most needed in regions without the means to assemble an inventory. To overcome these challenges, we develop a method for assessing shallow landslide susceptibility based on a probabilistic morphometric analysis of the landscape’s topography, rather than the characteristics of landslides. The model assumes that hillslopes with higher relief and gradient compared to the surrounding landscape are more prone to landslides. We demonstrate the superior performance of this approach over contrasting data-driven models across the northwestern United States. As our morphometric model only requires elevation data, it overcomes the major limitations of data-driven models and facilitates the creation of effective susceptibility models in areas where it was previously unfeasible.

Oregon, Washington↗
USGS2025

Assessment of water chemistry of the Coconino aquifer in northeastern Arizona

The Coconino aquifer was investigated as a potential groundwater resource for the Hopi Tribe and Navajo Nation in northeastern Arizona. Basic groundwater chemistry, including major ions, total dissolved solids, and selected trace metal concentrations, are presented and analyzed to characterize the Coconino aquifer. The geochemical compositions of groundwater are associated with changes in geology and groundwater movement and are compared to drinking-water standards to determine suitable areas for potential groundwater resource development. Dissolved-solids concentrations in much of the Coconino aquifer water were higher than the U.S. Environmental Protection Agency’s secondary drinking-water standard of 500 milligrams per liter (mg/L) due to a buried halite body in the southeastern part of the study area. However, trace metal concentrations were generally low. Groundwater may need to be treated for high dissolved-solids concentrations before it is suitable for use as a resource for the Hopi Tribe and Navajo Nation.

Arizona↗
USGS2024

The impact of source time function complexity on stress drop estimates

Earthquake stress drop—a key parameter for describing the energetics of earthquake rupture—can be estimated in several different, but theoretically equivalent, ways. However, independent estimates for the same earthquakes sometimes differ significantly. We find that earthquake source complexity plays a significant role in why theoretically (for simple rupture models) equivalent methods produce different estimates. We apply time‐ and frequency‐domain methods to estimate stress drops for real earthquakes in the SCARDEC (Seismic source ChAracteristics Retrieved from DEConvolving teleseismic body waves, Vallée and Douet, 2016 ) source time function (STF) database and analyze how rupture complexity drives stress‐drop estimate discrepancies. Specifically, we identify two complexity metrics—Brune relative energy (BRE) and spectral decay—that parameterize an earthquake’s complexity relative to the standard Brune model and strongly correlate with the estimate discrepancies. We find that the observed systematic magnitude–stress‐drop trends may reflect underlying changes in STF complexity, not necessarily trends in actual stress drop. Both the decay and BRE parameters vary systematically with magnitude, but whether this magnitude–complexity relationship is real remains unresolved.

Bulletin of the Seismological Society of America↗
USGS2025

Groundwater hydrology, groundwater and surface-water interactions, water quality, and groundwater-flow simulations for the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado, 2017–19

In 2017, the U.S. Geological Survey, in cooperation with the Upper Arkansas Water Conservancy District, began a study to provide a comprehensive analysis of the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado. The study included collection of data pertaining to groundwater hydrology, groundwater and surface-water interactions, and water quality in the alluvial aquifer. In addition to providing foundational information on the hydrology of the alluvial aquifer, a numerical groundwater-flow model was developed to estimate the potential effects of additional storage of groundwater in the alluvial aquifer. Groundwater-level elevation data from 30 wells were used to estimate groundwater-flow directions in the alluvial aquifer, which were generally from the southwest to northeast, away from the Sangre de Cristo Mountains and towards perennial streams in the center of the valley. Although some seasonal variation was apparent in groundwater-level elevation records, no statistically significant seasonal trends were indicated. Statistically significant long-term trends were indicated in groundwater-level elevation records for 8 of the 30 wells, and of these wells with statistically significant trends, all but 1 indicated a negative trend of groundwater-level elevations. Spatial evaluation of wells with statistically significant negative groundwater-level elevation trends showed many are in areas of denser well drilling for domestic or other uses, indicating increasing groundwater use could potentially be causing groundwater-level elevation declines. There were instances of wells with no statistically significant groundwater-level elevation trends also located in areas of greater density of well completions. Additional investigations may be necessary to more fully characterize the processes responsible for negative groundwater-level elevation trends. Streamflow gain or loss calculations were completed for low flow in 2017–19 and for high flow in 2018 in nine reaches of streams within the study area. Stream reaches of the upper Texas Creek, upper Grape Creek, upper-middle Grape Creek, and Taylor Creek displayed consistent streamflow loss in each period from 2017 to 2019. These stream reaches represent long-term sources of recharge to the alluvial aquifer. Streamflow gain or loss varies through time in other stream reaches (lower Texas Creek, lower-middle Grape Creek, lower Grape Creek below Westcliffe, and lower Grape Creek above DeWeese Reservoir). The temporally variable behavior indicates these stream reaches may be sources of groundwater recharge or areas of groundwater discharge, likely depending on temporal dynamics between the elevation of the water table and the stream. Water-quality samples were collected from 10 groundwater wells and 10 stream sites during September through November 2019. All groundwater and stream samples were analyzed for major and trace elements and stable isotopes of water. A subset of groundwater samples was also analyzed for the environmental tracers sulfur hexafluoride, tritium, and noble gases. Comparison of water-quality results to U.S. Environmental Protection Agency drinking water-quality standards indicated no constituents exceeded primary standards for human health. Spatial evaluation of water quality indicated the concentrations of various constituents are likely controlled by groundwater and surface-water interactions and by spatial variability in bedrock geology underlying the alluvial aquifer. Specifically, streams shown to gain from groundwater had water chemistry constituent compositions similar to groundwater, whereas streams exiting the Sangre de Cristo Mountains tended to have compositions consistent with snowmelt. Groundwater geochemistry appeared to be partially controlled by oxidation-reduction processes and by proximity to igneous rocks in the Wet Mountains. Environmental tracers used to estimate groundwater age indicated all sampled groundwater contained tracers representing modern recharge (approximately less than 65 years old) but mixing of premodern recharge (approximately more than 65 years old) also occurs. Spatial evaluation of environmental tracers indicated large faults may be conduits for upwelling of older groundwater. No trends were observed in groundwater age with well depth, indicating all sampled wells are located within the zone of active groundwater flow. The presence of modern groundwater in wells with statistically significant negative groundwater-level elevation trends indicates groundwater storage depletions may be partially offset by capture of modern recharge. Repeated sampling of groundwater age would be necessary, however, to determine if any trends in groundwater age exist, which may indicate changing groundwater recharge, storage, or discharge. Additional investigations could also consider quantifying groundwater age in deeper wells to more fully define the depth of active groundwater flow. A numerical groundwater-flow model was developed to estimate components of the water budget, simulate groundwater and surface-water interactions, and evaluate the potential effects of aquifer storage and recovery. Simulated groundwater-level elevations from the calibrated groundwater-flow model are similar to the observed pattern of groundwater-level elevations with higher elevations in the western part of the study area along the Sangre de Cristo Mountains. Simulated water-budget components indicate most of the recharge to the alluvial aquifer is derived from streamflow losses, which is consistent with observations of losing streams along the mountain front. The largest groundwater discharge component of the alluvial aquifer was to streams in the center of the valley, where observations of stream gain or loss indicated the predominance of gaining conditions. Comparison of groundwater and surface-water interactions between the calibrated groundwater-flow model for 2000-19 (the base-case model) and a simulation including additional recharge, representing potential aquifer storage and recovery operations, indicated the additional recharge distributed throughout the area had minimal effects on streamflow in the nearby Grape Creek. An analysis of subregional groundwater budgets showed approximately 54 percent of the additional recharge flowed back to nearby Grape Creek, and the other 46 percent was distributed laterally into adjacent cells in the alluvial aquifer. The comparison of simulations and subregional water budget show the additional recharge did not substantially alter groundwater-level elevations or basin wide groundwater storage. Although the analysis of additional recharge provided in the numerical groundwater-flow model considers only one of many possible recharge scenarios, the model provides a useful tool that could be modified for various scenarios to understand potential effects of managed aquifer recharge.

Colorado↗
USGS2024

Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance

The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.

Earthquake Spectra↗
USGS2025

Fiber-optic distributed temperature sensing of hydrologic processes—Diverse deployments and new applications by the U.S. Geological Survey

Fiber-optic distributed temperature sensing instruments harness the temperature-dependent properties of glass to measure temperature continuously along optical fibers by using precise pulses of laser light. In the mid-2000s, this technology was refined for environmental monitoring purposes such as snowpack-air exchange, groundwater/surface-water exchange, and lake-water stratification. Fiber-optic distributed temperature sensing has revealed unprecedented details about preferential flow processes; however, the method is labor intensive and requires specific training, resulting in limited use by the broader water community. With the ongoing national implementation of the U.S. Geological Survey Next Generation Water Observing System, there has been renewed interest in harnessing the unique spatiotemporal monitoring capabilities of fiber-optic distributed temperature sensing. This fact sheet briefly describes this technology, highlights uses by the U.S. Geological Survey, and discusses current applications and future opportunities.

Fact Sheet↗
USGS2025

Special issue "Effects of surface geology on seismic motion (ESG): General state-of-research"

To understand and predict the behaviors of strong ground motions incurred during devastating earthquakes, studies focused on the “effects of surface geology (ESG) on seismic motions” (following tradition, herein contracted as: “ESG”) have progressed steadily in the last three decades. These ESG studies typically involve in situ measurements of the wavefield and commonly apply both analytical and computational approaches. Concurrently, improvements in ESG related research can be readily attributed to the proliferation of openly accessible strong motion data, as well as advances in computational power. Nevertheless, there remain significant shortfalls in our understanding of the epistemic and aleatory uncertainties associated with the ESG as demonstrated by phenomena from recent deadly earthquake-related site effects. Thus, investigations toward addressing these deficiencies should be underscored in future earthquake related disaster mitigation efforts. This special issue of Earth, Planets, and Space (EPS) is dedicated to the ongoing efforts by the International Association of Seismology and Physics of the Earth’s Interior (IASPEI) and the International Association of Earthquake Engineering (IAEE) that champion activities promoting studies related to the ESG.

Earth, Planets and Space↗
USGS2026

A case study of maximum depositional ages from terrestrial sandstones near the Cretaceous—Paleogene transition, western Williston Basin, USA

We present a new Bayesian method for deriving maximum depositional ages from detrital K-feldspar using total-fusion 40 Ar/ 39 Ar data. Individual analyses weighted by K/Ca ratio, age uncertainty, and percent radiogenic argon prioritize a result to come from accurately measured volcanic sources. Results from this method applied to sandstones from the Hell Creek region of northeastern Montana show that detrital K-feldspar maximum depositional ages align closely with detrital U-Pb zircon ages as well as tephra based chronostratigraphic constraints from both 40 Ar/ 39 Ar and U-Pb data. An age model informed by maximum depositional ages and available tephra data provides an estimate of 1.74 ± 1.04 Ma for the duration of deposition for the Hell Creek Formation. Combined age model and maximum depositional age data suggest ≤ 1.84 Ma of missing time is represented by the Hell Creek and Fox Hills formational disconformity, coinciding with the final regression of the Western Interior seaway.

Montana↗