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USGS2025

Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA

The U.S. Geological Survey (USGS) is updating the 2008 assessment of conventional hydrothermal resources for the Great Basin in the western United States. As part of this work, the workflow for hydrothermal resource favorability maps is being modified to integrate modern data-driven machine learning (ML) methods. Improvements include: [1] using new and refined evidence layers (features); [2] using an order of magnitude more training sites (labeled examples); [3] utilizing simple but non-linear supervised ML algorithms; [4] representing positive training sites (wells with measured heat flow) with their ordinal value proportional to the magnitude of convective upflow (i.e., low, high, or very high convective signals instead of past strategies using positive-negative labels); [5] supplementing training sites with additional sites with low convective signals to represent diverse under-sampled areas where hydrothermal systems are unlikely to exist; [6] comparing with competing approaches; and [7] utilizing Monte Carlo cross-validation to estimate and evaluate prediction uncertainty. For the new favorability map, over half of the power-producing systems (i.e., 15 of 28) are predicted in the 99th percentile of most favorable locations (i.e., the highest 1 % of favorability, corresponding to 1 % of the map area), exceeding the performance of past models that have explicitly used power plants as training sites. Previous favorability maps predicted approximately half of the power-producing hydrothermal systems above the 80th percentile (i.e., 20 % of the map area). For the new favorability map, 93 % of power-producing systems (i.e., 26 of 28) are above the 80th percentile. The power-producing systems for which the new model does not perform well are either comparatively small, low-temperature systems or systems also not predicted well by prior modeling approaches, suggesting that these few systems are unusual when compared with most power-producing systems. Focusing research on these known, seemingly different systems may yield new insights and subsequent discovery of new prospects.

California, Idaho, Nevada, Oregon, Utah↗
USGS2024

Coastal Science Navigator companion guide—Discover the U.S. Geological Survey coastal science products you need

The Coastal Science Navigator is an online gateway to a wide variety of U.S. Geological Survey (USGS) coastal change hazards-related information, data, and tools relevant to stakeholders’ scientific and decision-making needs. The products within the Coastal Science Navigator provide data related to past, present, and future threats to our coastlines. The filter search allows users to see all available products and identify relevant options by time scale, geographic scope, coastal hazard theme, and other filters. The guided search suggests products based on users’ answers to a short series of questions. A comprehensive summary is available for each product. The idea for the Coastal Science Navigator arose in 2020 in response to stakeholder feedback identifying the need for a central source for USGS coastal science information. It was published in July 2023 and initially included 55 products. Regular updates are planned to integrate other existing and new products. This guide introduces some of the many coastal change hazards-related products available through the USGS. In it, we showcase the products included in the Coastal Science Navigator’s initial publication in July 2023. While it is not representative of all the information, tools, and data available, we hope it serves as a compelling snapshot of what the USGS has to offer and encourages you to explore the Coastal Science Navigator to discover more of the products you need. To navigate this guide, the products have been organized by the time scale they are best suited for—past, present, or future—although many products cover multiple time scales. An additional section features software, one of the many product types available as filters within the Coastal Science Navigator. Other products include downloadable data, websites, and geonarratives (web pages that combine text, images, and interactive maps into narratives you can scroll through). Featured geographic scopes are also highlighted within this guide, detailing some of the many regions in which the USGS conducts research and illustrating another way to filter products within the Coastal Science Navigator.

Circular↗
USGS2023

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions↗
USGS2026

Vegetation cover and composition in environments surrounding uranium mines in the Grand Canyon ecosystem, Northern Arizona

Mining uranium from breccia-pipe deposits in the greater Grand Canyon region has occurred since the mid-1900s. However, possible ecosystem contamination with harmful levels of radionuclides may have occurred due to mining activities in the 21st century. In response, a 20-year Federal moratorium on new mining claims in the Grand Canyon watershed was initiated in 2012, to allow time to evaluate the potential effects of uranium exploration and mining on human health, wildlife, and water resources. This moratorium, nor the 2023 designation of the “Baaj Nwaavjo I’tah Kukveni–Ancestral Footprints of the Grand Canyon National Monument,” precludes operation or development of mining claims predating 2012. Vegetation is a core ecosystem component that may be affected by uranium mining (for instance, through uptake and storage of radionuclides from the air or soil) or may act as a vector of exposure to wildlife, livestock, and humans (for instance, via their consumption of contaminated plant tissues). To provide baseline information about the plant communities associated with uranium mines in the Grand Canyon region, the U.S. Geological Survey surveyed an approximately 200-meter-wide buffer surrounding four breccia-pipe deposits, each in a unique stage of mine development, and at one reference area (a livestock water tank) that underwent ground disturbance but contains no mineral deposits. We sectioned the buffer zones into 0.65–4.52 hectare plots, within which we (1) inventoried all plant species, (2) measured percent cover of plant species, plant functional groups, and ground surface types (dark cyanobacteria, lichen, moss, bedrock, rock, embedded litter, duff, plant bases, and bare soil) using line-point intercept, and (3) measured length and frequency of gaps between perennial plant canopies using canopy gap intercept. We found that plant composition at the mines and the reference area differed from one another but were all characteristic of expected regional vegetation patterns. We provide this data summary as potential baseline information for future research and management efforts.

Arizona↗
USGS2024

A comparative analysis of OpenET for evaluating evapotranspiration in California almond orchards

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in soils, age, and variety. It also compares OpenET ensemble evapotranspiration (ET) data with applied irrigation and precipitation records over an additional 148 almond orchards located in the Central Valley of California. Results show OpenET models, including the ensemble ET value, produced reasonable and actionable ET values, with overall coefficient of determination (R 2 ) and mean absolute error values of 0.73- and 0.95-mm d −1 at the daily time step, respectively. However, given the temporal sampling of Landsat (8-day revisit) and the interpolation methods used, the assessed ET models had difficulty in capturing short-term variability in almond ET; for example, the rapid decline in measured ET observed as a response to lack of irrigation preceding and during almond harvest. The study also drew attention to the spatial complexity in scenarios where irrigated orchards are surrounded by hot/dry areas, causing discrepancies between measured and modeled ET values. In comparison with irrigation records, OpenET ensemble ET was capable of quantifying water input (applied irrigation + precipitation) in almond orchards to within 13 % when evaluating monthly data. Initial results presented here reinforce the idea that RSET models, such as in OpenET, are powerful tools, yet their application requires nuanced understanding and careful consideration of local conditions.

California↗
USGS2024

Simulation of groundwater flow and brine discharge to the Dolores River in the Paradox Valley, Montrose County, Colorado

Salinity, or total dissolved solids (TDS), of the Colorado River affects agricultural, municipal, and industrial water users and is an important concern in the Western United States. In the Paradox Valley of southwestern Colorado, natural discharge of sodium-chloride brine to the Dolores River from the underlying core of a salt-valley anticline accounts for about 6 percent of the salinity load to the Colorado River. Formation of the Paradox Valley began during the Miocene, and subsequent erosion exposed the Pennsylvania Paradox Formation in the core of the anticline where a cap rock, collapse features, breccia, and sodium-chloride saturated brine developed at the top of the exposed salt diapir. The discharge of brine to the Dolores River is affected by these dissolution features, along with seasonal hydrologic conditions and density-dependent flow between older dense brine and the younger fresh groundwater in the overlying alluvial aquifer. To reduce TDS concentrations in the Dolores River through the Paradox Valley, the Bureau of Reclamation has pumped brine from a series of shallow wells adjacent to the river since July 1996. The pumped brine is collected and piped to a deep disposal well where it is injected into the Mississippian Leadville Limestone at a depth of about 4,570-meters below land surface. The pumping and injection operation is collectively known as the Paradox Valley Unit (PVU), and by 2015, the PVU had substantially reduced TDS concentrations in the Dolores River by about 70 percent. Since 2019, injection-pressure limits and related seismic activity have constrained deep-well injection and thus brine pumping at the PVU. In cooperation with the Bureau of Reclamation, the U.S. Geological Survey developed a MODFLOW-6 three-dimensional, variable-density groundwater flow and TDS transport model of the Paradox Valley to evaluate the effects of PVU pumping operations on brine discharge to the Dolores River and to guide additional research. The finite-difference model grid consists of 76 rows and 48 columns oriented from northwest to southeast in alignment with valley topography and groundwater-flow directions in the near-surface freshwater alluvial aquifer. A 7-layer hydrogeologic framework was developed from existing datasets to represent the alluvial aquifer, cap rock, collapse breccia, and groundwater flow and TDS transport from the underlying Paradox Formation salt to the Dolores River. The model represents a 33-year transient calibration period from 1987 through 2020 that includes pre-PVU conditions from 1987 through June 1996 and post-PVU conditions from July 1996 through 2020. A 1,000-year simulation of groundwater flow and coupled TDS transport computed the initial conditions for the subsequent 33-year transient simulation. Observations of precipitation, streamflow, evaporation, agricultural land use, and PVU brine pumping rates were used to specify appropriate boundary conditions to the model representing time-varying recharge, tributary streamflow, groundwater underflow, evapotranspiration (ET), and PVU pumping. Values for average monthly streamflow and TDS concentration at the upstream streamgage, the Dolores River at Bedrock (USGS streamgage 09169500), were specified as model input where the Dolores River enters Paradox Valley. Observed pumping from the PVU, water levels and TDS concentrations in groundwater, and streamflow and estimated TDS concentrations at the downstream streamgage, the Dolores River near Bedrock (USGS streamgage 09171100), were calibration targets that constrained the manual calibration of model parameters representing aquifer hydraulic conductivity, storage, streambed conductance, recharge, and (ET). Two primary model-calibration targets were the match between observed and simulated TDS mass flux from PVU pumping wells and the match between estimated and simulated TDS mass flux to the Dolores River. The simulated TDS mass withdrawn by pumping wells is calculated by the model as the product of the assigned pumping rate and simulated groundwater TDS concentrations. Because actual pumping rates were assigned as simulated values, the total simulated PVU pumping for the 33-year calibration is within 0.5 percent of the observed values. However, simulated concentrations and thus mass flux of TDS withdrawn by the PVU pumping wells were consistently about 26 percent less than observed values for all the simulated time periods (33-year simulation, pre-PVU, and post-PVU). The representation of brine inflow was explored through additional modeling to evaluate the effect of the simulated brine source on groundwater TDS concentrations. Results indicated that a saturated-salt constant-flux brine source best replicated the magnitude and transient pattern observed for TDS mass flux from PVU pumping wells. The simulated TDS mass flux to the Dolores River is compared to estimates based on observed streamflow and specific conductance (SC) data for the downstream streamgage. The calibrated model provided a close fit of simulated to measured streamflow at the downstream streamgage, and the calibrated model fit to estimated TDS concentrations at the downstream streamgage was reasonable. The greatest differences between simulated and estimated values occurred during drought periods from June 2000 to March 2003, May 2012 to June 2013, and October 2013 to October 2014, when simulated TDS concentrations in the river were greater than estimated concentrations. In general, simulated TDS mass flux to the river for the pre-PVU period is in good agreement with estimated values (2-percent difference), but the model overestimated TDS mass flux to the river by about 41 percent during the post-PVU period. The model uncertainty with respect to TDS mass flux to the river indicates other processes or model parameters not well represented by the model are affecting the system, especially during drought. During model calibration, the most sensitive parameters were identified as vertical hydraulic conductivity of the alluvial aquifer, conductance of the Dolores River streambed, ET extinction depth and rate, and recharge rate. Five 5-year scenarios of conditions for 2021–25 were simulated to assist evaluation of alternative strategies to manage the discharge of brine into the Dolores River. The first scenario simulates no PVU pumping and serves as a base case for comparison to the other scenarios. Two scenarios simulate the effects of varying withdrawal timing at an annual rate about one-third less than during 2010 through 2018. During high-flow spring snowmelt runoff periods when brine discharge is naturally minimized, PVU pumping does not substantially affect salinity in the Dolores River, and comparison of these two scenarios indicates that scheduling brine withdrawals during times of low river stage is nearly as effective at reducing TDS mass flux to the river as pumping brine year-round. Cessation of pumping during periods of high river stage may be advantageous for system maintenance, brine injection, and seismic-risk reduction. The fourth scenario tested the effect of reducing irrigation-return flow on brine discharge and predicted a slight reduction of TDS mass flux to the Dolores River, but not as great a reduction as that of using the PVU to remove brine. The fifth scenario simulated 5 years of drought conditions without PVU pumping and indicates brine discharge during drought about 15 percent greater than during average hydrologic conditions. Results from scenario 5 are consistent with the calibrated model results and indicate that aquifer properties and ET processes and parameters may be affecting simulation results during drought. The Paradox Valley groundwater model provides a reasonable overall match to observed conditions in the Dolores River. The model is useful for evaluating relative differences between brine management scenarios to inform PVU operational decisions and to identify gaps in data and process understanding. Representation of the brine source, hydraulic-conductivity parameters, and recharge and ET processes were identified as potential areas for additional field and modeling research. Additional research in the Paradox Valley might include field-data collection that provides additional information on the hydrogeologic framework, groundwater levels, groundwater TDS concentrations, stream characteristics, and aquifer properties. Additional modeling efforts could benefit from applying advanced tools for model development, calibration, and visualization including parameter-estimation and sensitivity analysis. Statistical evaluation of known model uncertainties such as hydraulic conductivity, streambed conductance, representations of the brine source, recharge, and ET could improve the match between simulated and estimated TDS mass flux from PVU pumping wells and to the Dolores River further informing model predictions and system understanding for the Paradox Valley.

Colorado↗
USGS2025

ShakeAlert®—Communication, education, outreach and technical engagement strategic vision

Executive Summary In 2006, the U.S. Geological Survey (USGS) began directly supporting ShakeAlert ® research and in 2012 the ShakeAlert demonstration system began testing ( Given and others, 2018 ). The ShakeAlert earthquake early warning (EEW) system is a partnership between the U.S. Geological Survey (USGS) and the three West Coast States (Washington, Oregon, and California) served by the ShakeAlert System, which is part of the larger Advanced National Seismic System (ANSS). With more than 143 million people exposed to potentially damaging shaking in the United States ( Jaiswal and others, 2015 ), earthquakes are a national hazard. Most of our Nation’s earthquake risk is concentrated in the highly populated areas on the active plate tectonic boundaries on the West Coast of the conterminous United States. ShakeAlert is the first public alert system in the United States to provide rapid mass notification of earthquake detection, potentially offering seconds of warning before strong shaking arrives. A few seconds may not seem like much time, but the information in ShakeAlert Messages can be used to trigger automated actions that can prevent injury or death, reduce immediate damage, and speed recovery from earthquakes. The information product issued by the ShakeAlert system is called a ShakeAlert Message and is one of the information products and tools of the ANSS. The ShakeAlert System includes the USGS component, plus the pathways by which ShakeAlert-powered products and (or) services are delivered to end users. Alerts can be delivered to cell phones or be used to trigger automated systems to protect equipment, facilities, and infrastructure, such as slowing or stopping a train. ShakeAlert-powered automated actions can include fire house doors that can be opened to prevent jamming, heavy equipment (for example, trains, elevators, and cranes) that can be automatically stopped or parked in safe positions, and pipeline valves that can be closed to prevent surges and spills. A few seconds of warning also may be sufficient for people to take protective actions, such as drop, cover, and hold on or modified protective actions for a broad range of populations. Advance training may increase the benefit of a speedy response to an alert. Outreach and education about EEW may raise awareness of the overall earthquake threat and how people can best react when they receive an alert or feel shaking. ShakeAlert communication, education, outreach, and technical engagement (CEO&TE) efforts are highly collaborative and essential for the success of the ShakeAlert System. This strategic vision informs how the vast ShakeAlert CEO&TE Community operates and works together. The CEO&TE Community delineates a strategic framework that is intended to set the path for a long-term, sustainable approach to CEO&TE through three focus areas and five priorities. Focus Areas Technical engagement.— The objective of this focus area is to expand and broaden ShakeAlert technical engagement and implementation. External engagement.— This focus area targets engagement in long-term communication, education, and outreach planning, implementation, and evaluation. Internal engagement.— The purpose of this focus area is to build and sustain a robust infrastructure to optimize collaboration, information sharing, and project planning among the community of stakeholders charged with implementing ShakeAlert CEO&TE. Priorities The enumeration of the five priorities listed below does not suggest priority ranking. Public safety, preparedness, and resilience; Technical implementation and engagement; Consistent messaging and communication; Integration with other Federal and State earthquake hazards products; and Educational resources development and dissemination. This strategic vision is a tangible outcome of collaboration among many stakeholders beginning in July 2016. Since then, the work of the ShakeAlert CEO&TE Community has grown into an international effort. The USGS has developed, tested, and implemented a broad spectrum of communication, education, and outreach tools and resources—all of which recognize that seconds matter when it comes to safety and mitigating harm from earthquake hazards. The CEO&TE social science research effort has provided invaluable insights into the ShakeAlert System’s human interface. USGS-licensed technical partners develop, test, and implement real-world applications using ShakeAlert Messages. The success of ShakeAlert CEO&TE efforts is predicated on robust collaboration across numerous agencies, organizations, and groups. As such, this strategic vision outlines a “partnership model” that delineates roles and responsibilities to ensure alignment with focus areas and priorities. The partnership model includes the CEO&TE lead agency (USGS); its principal partners (State agencies and university partners); its implementation partners (for example, technical partners who build systems to deliver ShakeAlert-powered products and (or) services [focus area one]), earthquake education partners who work to increase public preparedness for seismic events (focus area two); and other organizations that work together to enhance the adoption and effectiveness of the ShakeAlert System. These partners collaborate and convene through a variety of working groups and forums, which are also described in this strategic vision and align with focus area three (internal engagement). The CEO&TE Community collaboratively developed its operating principles and a consensus-based, decision-making strategic framework to guide its collective work. Performance metrics are used to continually measure success. Ultimately, the USGS and ShakeAlert CEO&TE Community are advancing the ShakeAlert System that as of the publication of this strategic vision to “provide earthquake early warning for all” serves more than 50 million people.

Circular↗
USGS2025

Near-surface geophysics: Environmental applications

The field of geophysics encompasses a broad and diverse compilation of methodologies that employs principles of physics to characterize properties of earth materials within the subsurface. While geophysical methods have a long history in resource exploration and studies of Earth’s interior, the subdiscipline of “near-surface geophysics” has evolved in recent decades for examination of the shallow, near-surface environment for a range of purposes ranging from archaeological or forensic investigations to assessment of geologic, hydrologic, biologic, and geochemical properties and processes. “Environmental geophysics” are near-surface geophysical studies and methods that focus on understanding natural systems (e.g., watershed hydrology, groundwater–surface water connections, biophysical processes) as well as research pertaining to anthropogenic impacts and land management, (e.g., contamination and remediation, saltwater intrusion, agricultural practices). This field can be further subdivided into subdisciplines focused on specific topics and applications, such as water resources and hydrology (hydrogeophysics) or biologic and microbial processes (biogeophysics). Studies in environmental geophysics span a range of scales, from pore-scale laboratory tests to watershed-scale or regional field experiments. Methods vary by the nature of physics employed, the specific measurement acquired, and how that data is ultimately processed and analyzed to produce interpretable results. There exists further diversity in the acquisition logistics, geometry, and timing of data collection. Geophysical data can be collected in boreholes (one-dimensional, 1-D, vertical profiles), along survey lines (two-dimensional, 2-D, cross-sections), or in dense sensor arrays or gridded profiles (three-dimensional, 3-D, models). Regarding the temporal aspect, studies can conduct one-time geophysical surveys to obtain detailed imaging of subsurface structure or use timelapse and continuous monitoring to investigate variations in subsurface properties over time. The cumulation of all possible permutations of these factors (method, acquisition geometry, survey design, and target application) results in an immense diversity among environmental geophysical studies. Nevertheless, this field remains unified in the pursuit of understanding natural and human-impacted near-surface environments through geophysical investigations. Here we highlight some key references within environmental geophysics. Resources on geophysical theory, acquisition logistics, processing and inversion workflows, and example case studies are categorized into the most common geophysical classes within Geophysical Methods. Lastly, example references for the dominant types of applications in environmental geophysical studies are catalogued in Environmental Applications.

Book chapter↗
USGS2024

Influence of inherited structure on flexural extension in foreland basin systems: Evidence from the northern Arkoma basin and southern Ozark dome, USA

Extensional faults are key components of foreland basin systems. They form within the upper crust in response to flexure of the lithosphere and accommodate subsidence within the foredeep and forebulge depozones. Such faults are excellent proxies for orogenic system evolution and control the distribution of natural resources and hazards. However, the spatiotemporal evolution of flexural extension has not been documented previously at a regional scale, thereby limiting our understanding of underlying geodynamic controls. Here, we resolve late Paleozoic flexural extension in the northern Arkoma basin and southern Ozark dome, USA. We synthesize a large database of previous mapping, existing research, subsurface data, and geophysical data into 3D geologic and 2D kinematic models. Mesh surfaces representing several key horizons from the Carboniferous Period (ca. 335-306 Ma) were constructed. These surfaces were built from oil and gas well tops (n = ∼10,000) and surface geologic map contacts using an advanced kriging method. The mesh surfaces are offset by a complex 3D fault network, allowing detailed analysis of along-strike and down-dip variations in fault displacement. Analysis of the 3D model reveals a regular and repeated fault segmentation pattern wherein E -W striking, left- and foreland-stepping en échelon normal faults are segmented by inherited NE striking basement faults. Maximum vertical separation along the E -W normal faults is generally focused between the inherited NE-trending faults. This suggests that the inherited basement faults delocalized extensional strain during late Paleozoic normal faulting. Maximum vertical separation and fault localization may correlate to areas with high-amplitude positive magnetic anomalies interpreted as Mesoproterozoic granitic rocks. Speculative covariance of magnetic anomalies and fault displacements implies that the relatively strong basement granite concentrated stress, leading to localized faulting within the relatively thin sedimentary cover. Lastly, we show that flexural extension migrated southeast to northwest from the Chesterian-Morrowan (ca. 335-319 Ma) to the Desmoinesian (ca. 306 Ma). The migratory flexural extension may be explained by diachronous loading during Pangean assembly, or by synchronous loading but variable load compensation due to inherent factors.

Arkansas, Oklahoma↗
USGS2025

Metal fingerprints of Eocene rhyolite magmas coincident with Carlin-type gold deposition in Nevada USA

Eocene magmatic systems contemporaneous with world-class Carlin-type Au deposits in Nevada (USA) have been proposed by some researchers as a key ingredient for Au mineralization, though evidence conclusively demonstrating their genetic relationship remains tenuous. This study provides the first direct evidence of the pre-eruptive metal budget of volatile- and metal-charged silicic magmas coincident in time (~41 to 34 Ma) and space (within 5 km) with Carlin-type Au deposits. We characterize the pre-eruptive metal fingerprints of these diverse magmatic systems to assess their potential as sources of metals for Carlin-type Au mineralization. Metal abundances from quartz-hosted melt inclusions (Au, Te, Ag, Sb, Tl, Mo, W, Sn, As, Pb, Co, Cu, Ni, and Zn) characterized in situ by SHRIMP-RG and LA-ICP-MS represent our best (and only) estimates for the pre-eruptive metal budget in these systems. Median metal concentrations are generally within one order of magnitude of average upper crust and average continental rhyolite values. But there are two notable exceptions, with median Au contents extending >1 order of magnitude higher than average upper crust and median Cu contents ranging >1 order of magnitude lower than upper crust. Despite this, melts contain lower Au/Cu (<0.1), Au/Ag (<5), and Au/Tl (<0.3) than most ore-grade Carlin-type rock samples and quartz-hosted fluid inclusions, regardless of their age and timing relative to nearby Carlin-type Au mineralization. The metal fingerprints of these magmatic systems, de-fined both by traditional and multivariate compositional data analysis techniques, are distinct from one another. Yet none are particularly specialized, e.g., high Au/Cu, in terms of being ideal ingredients as postulated by magmatic models for Carlin-type Au mineralization. Magmatic Au contents do not appear to be correlated with rhyolite “flavors” in the way that Cu, Sn, and Nb contents are. Fluid/melt partitioning modeling and magma volume estimates support the idea that a diverse array of non-specialized silicic magmas could feasibly contribute some or potentially all of the Au, Ag, and Cu in Carlin-type systems. The compositional diversity among contemporaneous magmatic systems could possibly contribute to some of the diversity observed across Carlin-type Au districts in Nevada.

Nevada↗
USGS2025

Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20

We present an assessment of water supply across the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico covering water years 2010–20. Our analysis drew on two national hydrologic models, the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system. Both models produced estimates of streamflow, evapotranspiration, soil moisture, snow water equivalent, and other hydrologic states and fluxes. The models were driven by the bias-adjusted 4-kilometer-resolution, long-term regional hydroclimate simulation over the conterminous United States dataset (CONUS404). We assessed spatial and temporal error distributions by comparing monthly simulations at the 12-digit hydrologic unit code and regional scale from both models against external benchmarking datasets. Results showed that average annual rainfall across the CONUS was 857 millimeters per year for the period of analysis, with water year 2012 the driest year (729 millimeters) and water year 2019 the wettest year (995 millimeters). Key interannual variability results included the following: (1) the California–Nevada hydrologic region had the highest variability in precipitation and snow accumulation, and (2) the Texas hydrologic region was among hydrologic regions with the highest variability in precipitation. We related interannual variability in precipitation to storage volumes in soil moisture, snow water equivalent, and lakes and reservoirs to highlight areas with little storage and large year-to-year variability in precipitation. These areas included the Southern High Plains, Central High Plains, Texas, Souris–Red–Rainy, Mississippi Embayment, and Midwest regions. Our analysis of groundwater-level data showed that several of these areas overlap aquifers where groundwater levels were considerably lower than historical averages, including the Colorado Plateaus aquifers, the Rio Grande aquifer system, and the Central and Southern regions of the High Plains aquifer. Many of these lowered groundwater levels are continuations of decades-long declines from overpumping that started well before the assessment period. The resulting water budgets and their analyses provide a high-resolution foundational assessment of the mean state and variability of the terrestrial hydrologic cycle across the CONUS and Alaska, Hawaii, and Puerto Rico to support a wide range of water resource management applications.

Professional Paper↗
USGS2026

Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems

In intermittent stream systems, including those occurring in Texas, USA, the severity of low-flow conditions, duration of seasonal disconnection, and frequency of no-flow events have been amplified by drought. Documentation of these no-flow events is necessary to evaluate ecosystem health. However, many intermittent reaches remain un-gauged given that perennial river sec-tions are often prioritized for gauge placement. Our objectives were to 1) document stream flow using Stream Temperature, Intermittency, and Conductivity (STIC) loggers to determine the frequency and duration of no-flow events in intermittent tributaries of the Colorado River, Texas and 2) compare logger data to publicly available data from streamflow discharge and precipitation gauge networks to understand differences among these data types for drying event characterization. We use these comparisons to summarize benefits and limitations of the application of in-stream data loggers. STIC loggers were deployed at 19 sites, one in each pool and riffle habitat of a stream reach. STIC loggers recorded a measurement of relative conductance every six hours from June 2022 to March 2024, which was used to determine the presence or absence of flow connectivity in a reach. No-flow duration among intermittent reaches varied between 37 and 270 days across tributaries during an ongoing drought in the study area. Overall, logger data was more precise than discharge data for characterizing no-flow events or precipitation data when documenting presence of water in the stream channel due to runoff. Lack of discharge gauges in intermittent tributaries left large sections of stream reaches undocumented and resulted in mischaracterization of flow patterns. Drought severity across the tributaries did not follow longitudinal patterns that would be expected by the climatic precipitation gradient of the study area. More research is needed to determine if factors such as population size affect severity. Likewise, precipitation data did not correlate well with logger water presence data, lacking consideration for groundwater recharge, soil hydrophobicity, and surface compaction. This study shows that to monitor no-flow events, detailed spatial datasets are necessary and that STIC loggers are useful tools that provide data to fill spatial information gaps and facilitate more accurate flow characterization and water presence data in intermittent systems.

Texas↗
USGS2025

Update of the 2008 provisional Enhanced Geothermal Systems (EGS) assessment for the Great Basin, USA

In response to the Energy Act of 2020, the U.S. Geological Survey (USGS) is updating the Enhanced Geothermal Systems (EGS) resource assessment for the Great Basin, USA. The previous 2008 provisional assessment estimated how much electricity could be generated from EGS resources of the western United States using models of electric-grade heat, models of heat extraction over time, and estimates of how much rock might be stimulated to produce viable amounts of heat. Herein, a similar conceptual strategy is applied, using updated models of heat extraction as a function of fracture spacing and well distance. Previously used reservoir heat delivery models are updated to have a dependence on fracture and well spacing, potentially improving future estimates of EGS resources as ongoing research provides a better understanding about the success of reservoir stimulation as a function of geology and location. For a range of well distances (250-1000 m) and fracture spacings (1-50 m), heat extraction efficiency ranges from 25-62%, demonstrating the importance of accounting for the most likely results of proven viable fracturing technologies. Although fracturing is important, the biggest uncertainty by far in estimating the EGS resource for the Great Basin is estimating which geologic units at what depths can be stimulated sufficiently to produce geothermal energy economically and efficiently. Uncertainties in these factors yield estimates that range over two orders of magnitude with an upper limit of ~174 terawatts-thermal (TWth) produced for 30 years from the upper 7 km of the crust. This upper limit would require significant technological advances to access most of the electric-grade resource across the Great Basin. Assuming that 1% of this estimate will be accessible in the next few decades gives a resource estimate similar to that made in the 2008 provisional assessment. These estimated EGS heat extraction rates far exceed ( greater than 100x) the natural geothermal heat production rate, thus geothermal electricity production at these rates might not be sustainable unless heat is also recharged from other sources (e.g., excess solar energy when supply exceeds demand). In addition to assessment maps and cumulative estimates, the new models of fractured reservoirs developed herein can be used to estimate steady power production given a set of fractures and well spacing, and estimates can be made for setback distances to ensure no thermal interference with nearby powerplants.

Arizona, California, Idaho, Nevada, Oregon, Utah↗
USGS2025

Wangyanite, PdNi8S8, a new Pd end-member mineral of the pentlandite group from the J-M reef, Stillwater Complex, Montana, USA

Wangyanite (IMA2024-008a), ideally PdNi 8 S 8 , is a Pd end-member mineral of the pentlandite group that was discovered in the J-M reef of the Stillwater Complex, Montana, USA. Wangyanite occurs as anhedral-subhedral granular crystals 200–400 µm in size, associated with isoferroplatinum, braggite, pentlandite, and chalcopyrite interstitial to plagioclase grains within anorthosite. Wangyanite exhibits a yellowish brown color with a black streak and a metallic luster. It is brittle with uneven fractures, and has a calculated density of 5.14 g/cm 3 . The mineral does not show discernible pleochroism, bireflectance, or anisotropy. It has an average composition of 9.95 wt.% Pd, 31.95 wt.% Ni, 25.02 wt.% Fe, 0.57 wt.% Co, 31.74 wt.% S, totaling 99.23 wt.%. The empirical formula, based on eight sulfur atoms per formula unit, is (Pd 0.76 Co 0.08 ) Σ0.84 (Ni 4.39 Fe 3.60 ) Σ7.99 S 8 . Wangyanite has a cubic cell with a space group of Fm -3 m (#225), having lattice parameters of a = 10.1167(12) Å, V = 1035.4(4) Å 3 , and Z = 4. Its crystal structure has been solved by single-crystal three-dimensional electron diffraction study. The strongest X-ray diffraction lines of wangyanite are claculated at [ d in Å ( I %)( hkl )]: 5.841(14.03)(111), 3.050(100)(311), 1.947(29.16)(115,333), 1.264(11.66)(800), 3.577(8.79)(220), 2.920(20.82)(222), and 2.321(9.34)(331). Wangyanite shares the same crystal structure as pentlandite, but the octahedrally coordinated site is mainly occupied by Pd in wangyanite. Based on the textural features and previous experimental Pd-Fe-Ni-S phase system, wangyanite could form by peritectic reaction between braggite, pentlandite and sulfide liquid. These mineral associations are stable in a Ni-Pd-rich sulfide melt system at about 550 °C or even lower temperature. Therefore, wangyanite can potentially serve as an indicator of the presence of Pd-rich residual melts. The mineral is named in honor of Prof. Christina Yan Wang, a well-known researcher on platinum-group element (PGE) occurrences and enrichment mechanisms in mafic-ultramafic intrusions, notably those deposits related to the Emeishan large igneous province in China.

Montana↗
USGS2026

Distributed volcanic fields—Patterns, products, processes, and plumbing

Distributed volcanic fields—also referred to as “monogenetic fields” or simply “volcanic fields”—are found on every continent, on the seafloors, and in every tectonic setting on Earth. Yet, our understanding of what constitutes a distributed volcanic field, and our knowledge of the common products, spatiotemporal patterns in activity, and plumbing systems of these fields, are commonly poor and (or) debated. Here we provide an overview of the current understanding of distributed volcanic fields (DVFs) through review and compilation of published data, with an emphasis on understanding the characteristics of fields that are essential to prepare for future hazardous volcanic activity. Distributed fields can erupt restricted to variable magma compositions. Activity in these fields produces nearly all types of volcanoes, including scoria and spatter cones, maars, low shields, lava fields, stratovolcanoes, and calderas, but monogenetic volcanoes are the defining characteristic of DVFs. The number of vents and lifespans of DVFs vary greatly; vent numbers range from 2 to greater than 1,000, and fields can remain active for 150,000 to 10 million years. Some characteristics of DVFs appear field dependent. Although the volumes of single monogenetic eruptions within DVFs globally are variable (from less than 0.1 to a few cubic kilometers), each field may have a characteristic range in eruption volumes. Eruptions within distributed volcanic fields can have a random distribution and timing, but spatial and (or) temporal vent clustering and alignment are common, and eruptions may be time or volume predictable. Average eruption recurrence intervals in DVFs span over an order of magnitude, from less than 3 to greater than 100 thousand years. Exposures of the shallow portions of older systems reveal that many magma batches end their ascent before reaching the surface, with some dikes stopping within only meters of the surface. Petrologic insights into the deeper plumbing systems of DVF volcanoes indicate variable depths of magma crystallization and (or) stalling, and that magma transport and storage systems may be unique to a particular DVF and its underlying crustal structure. Both seismic and petrologic data for mafic DVF eruptions corroborate intrusions of magma into storage systems in the months to years before eruption, as well as variable ascent rates through the crust (days to weeks). Few distributed fields are closely monitored, as they erupt infrequently, but these observations imply that the amount of time available to install monitoring instrumentation after the first felt seismicity may be short, as precursory activity is frequently on the order of days to months for modern DVF eruptions. Satellite-based geodesy may provide useful warning in such cases. This chapter concludes with outstanding questions and areas for future research that will aid in our understanding and preparedness for future DVF eruptions.

Professional Paper↗
USGS2024

Post-wildfire debris flows

Post-wildfire debris flows pose severe hazards to communities and infrastructure near and within recently burned mountainous terrain. Intense heat of wildfires changes the runoff characteristics of a watershed by combusting the vegetative canopy, litter, and duff, introducing ash into the soil and creating water repellant soils. Following wildfire, rainfall on bare ground is less able to infiltrate into the fire-altered soils and overland flow is less impeded by vegetation. Rainfall runoff in recently burned areas can erode hillslopes owing to the removal of soil binding organic matter near the soil surface by fire. In channels, loose, dry-ravel deposits composed of sand and gravel are readily entrained by concentrated runoff in channels. Entrainment of soil on hillslopes and in channels bulks up the sediment concentration of the rainfall runoff to generate debris flows capable of transporting boulders and large woody debris. Post-wildfire debris flows can be triggered by rainfall conditions that would typically produce little runoff during unburned conditions. The primary rainfall trigger for post-wildfire debris flows is high intensity rainfall during short duration convective rainstorms or periods of high rainfall intensity embedded within a long-duration frontal storm. Numerous observations of debris flows triggered by storms lasting less than an hour following periods of little to no rainfall indicate that antecedent rainfall is not a requirement for initiation of post-wildfire debris flows. Post-wildfire debris-flow hazard assessment entails estimating probability and magnitude of debris flows in the burned area, estimating debris-flow runout and intensity, and defining rainfall intensity-duration thresholds for debris-flow initiation. In the United States, probability and magnitude is estimated using empirically derived models largely based on data collected in southern California. The models provide maps to identify watersheds and drainage paths where post-wildfire hazards are most pronounced. Rainfall intensity-duration thresholds can be incorporated into flood hazard forecasting tools. Currently, work is underway to identify how to best implement debris-flow runout models in burned areas with efficiency and accuracy. Post-wildfire debris flows have been a long-recognized process in the Transverse Ranges of southern California; however, climate change is driving more frequent wildfires to burn more mountainous terrain throughout the western United States and worldwide. As a result, post-wildfire debris flows are becoming a more common threat in areas where they were once infrequent. As the threat of post-wildfire debris flow expands into new areas, evaluating the hazard becomes challenging because the degree to which wildfire increases debris-flow susceptibility varies from region to region. This chapter summarizes the knowledge to date for evaluating post-wildfire debris-flow susceptibility and hazard assessment. We summarize the characteristics of wildfire burn severity, topography, underlying soil and geology, and rainfall conditions that contribute to making a watershed most likely to produce post-wildfire debris flows. Methods for hazard assessment in the United States and other countries are summarized. We highlight knowledge gaps for how post-wildfire debris-flow susceptibility varies throughout the western United States and worldwide and identify research needs to improve hazard assessment methods in different geographies.

Book chapter↗
USGS2025

Cancer risk and estimated lithium exposure in drinking groundwater in the US

Importance Lithium is a naturally occurring element in drinking water and is commonly used as a mood-stabilizing medication. Although clinical studies have reported associations between receiving lithium treatment and reduced cancer risk among patients with bipolar disorder, to our knowledge, the association between environmental lithium exposure and cancer risk has never been studied in the general population. Objectives To evaluate the association between exposure to lithium in drinking groundwater and cancer risk in the general population. Design, Setting, and Participants This cohort study included participants with electronic health record and residential address information but without cancer history at baseline from the All of Us Research Program between May 31, 2017, and June 30, 2022. Participants were followed up until February 15, 2023. Statistical analysis was performed from September 2023 through October 2024. Exposure Lithium concentration in groundwater, based on kriging interpolation of publicly available US Geological Survey data on lithium concentration for 4700 wells across the contiguous US between May 12, 1999, and November 6, 2018. Main Outcome and Measures The main outcome was cancer diagnosis or condition, obtained from electronic health records. Stratified Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% CIs for risk of cancer overall and individual cancer types for increasing quintiles of the estimated lithium exposure in drinking groundwater, adjusting for socioeconomic, behavioral, and neighborhood-level variables. The analysis was further conducted in the western and eastern halves of the US and restricted to long-term residents living at their current address for at least 3 years. Results A total of 252 178 participants were included (median age, 52 years [IQR, 36-64 years]; 60.1% female). The median follow-up time was 3.6 years (IQR, 3.0-4.3 years), and 7573 incident cancer cases were identified. Higher estimated lithium exposure was consistently associated with reduced cancer risk. Compared with the first (lowest) quintile of lithium exposure, the HR for all cancers was 0.49 (95% CI, 0.31-0.78) for the fourth quintile and 0.29 (95% CI, 0.15-0.55) for the fifth quintile. These associations were found for all cancer types investigated in both females and males, among long-term residents, and in both western and eastern states. For example, for the fifth vs first quintile of lithium exposure for all cancers, the HR was 0.17 (95% CI, 0.07-0.42) in females and 0.13 (95% CI, 0.04-0.38) in males; for long-term residents, the HR was 0.32 (95% CI, 0.15-0.66) in females and 0.24 (95% CI, 0.11-0.52) in males; and the HR was 0.01 (95% CI, 0.00-0.09) in western states and 0.34 (95% CI, 0.21-0.57) in eastern states. Conclusions and Relevance In this cohort study of 252 178 participants, estimated lithium exposure in drinking groundwater was associated with reduced cancer risk. Given the sparse evidence and unknown mechanisms of this association, follow-up investigation is warranted.

contiguous United States↗
USGS2024

Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the California Sacramento–San Joaquin Delta at the landscape scale—2018 high resolution mapping surveys

Executive Summary This study examined the abundance and distribution of nutrients and phytoplankton in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) and Suisun Bay, comprising three spatial surveys conducted in May, July, and October of 2018 that used continuous underway high frequency sampling and measurements onboard a high-speed boat to characterize spatial variation across the extent of the Delta. The method used involves simultaneously collecting information about the concentration and spatial distribution of all major nutrient forms with analogous information about the major classes of phytoplankton and associated water-quality conditions. The results showed substantial variation across space and time, providing an unprecedented snapshot of the dynamic environmental processes that shape the ways nutrients interact with and affect aquatic habitats in the Delta. The purposes of this study were to improve our understanding of how hydrodynamics, landscape features, and aquatic primary productivity interact to drive nutrient cycling and transport in the Delta and to provide insights into the underlying processes most directly responsible for the conditions at the time of this study, and thus into the range of conditions that may be expected following the wide array of prospective future changes to the Delta. One major anticipated change at the time of this study was the planned upgrade to the Sacramento Regional Wastewater Treatment Plant, but the study also informs our understanding of potential effects from other changes to the Delta, such as those caused by other nutrient-management actions, flow actions, large-scale wetland restoration, drought, flood, levee failure, and changes to water management. Nutrient loading is the primary driver of nutrient concentrations in the Delta, but several other major drivers interact to shape their distribution and effects: geomorphology, hydrodynamics, landscape features, and aquatic productivity. Hydrodynamics affect timescales of transport and dilution of nutrient loads in the Delta. During transit through the system, channel geometry, tidal mixing, and water exports affect hydrodynamics in diverse ways that influence water-residence and transport times, thereby markedly affecting the range of times during which natural internal cycling can alter nutrient concentrations and forms. Channel geometry and location shape tidal energy and river currents into these observed dynamics. Interactions with Delta aquatic landscapes such as herbaceous tidal marsh, submerged aquatic vegetation, and large expanses of intertidal or subtidal sediments (all highly productive landscapes) exert demand on available nutrient supplies but can also simultaneously transform and generate nutrients. Finally, while phytoplankton require nutrients to sustain production and thus are a potential nutrient sink, the amount and form of nutrients also can influence the occurrence of harmful algal blooms (HABs) that adversely affect aquatic organisms as well as affect the occurrence of beneficial algal blooms that result in production of algae that are favorable for imperiled Delta pelagic aquatic food webs. The surveys revealed a complex mosaic of spatial variation, with nutrient concentrations varying from near zero to well above concentrations considered eutrophic; nutrient concentrations were more often related to the extent of hydrologic transport and mixing than to specific geographic locations or to specific landscape features. Similarly, the surveys identified phytoplankton abundance ranging from near detection to the level of large phytoplankton blooms, with large variation in phytoplankton community composition. Although the study occurred during a period of low bloom activity, phytoplankton productivity appeared to be the strongest potential sink for inorganic nutrients in the Delta, indicating that it is a larger control on nutrient concentrations and distribution than previously understood. Cycling and transformation within the water column only appeared to substantially lower total nutrient concentrations at the longest estimated transport timescales. Contrary to expectations, we did not observe substantial nutrient depletion near landscape-scale features such as open-water habitats, submerged aquatic vegetation beds, extensive wetlands, or exposed sediments, indicating that these habitat types did not act as major sinks for nutrients in the Delta during these surveys. These results indicated that nutrient reduction efforts may have the greatest effect on pelagic phytoplankton productivity in the more productive reaches of the Delta and estuary, but these effects are unlikely to be magnified by changes to nutrient loss within the Delta over conceivable changes in flow conditions, Delta water management actions, or large-scale wetland restoration activities. Nevertheless, local processes were shown to cause substantial loss, and thus integrating of nutrient effects with other indicators of aquatic habitat conditions will help inform planning future actions at specific sites. Finally, we note that the primary contribution of this study was intended to be the survey data themselves. Aside from the results highlighted in this report, the surveys are a benchmark against which future environmental change may be evaluated, including changes to nutrient management or water exports, drought, large-scale wetland restoration, and climate change. Further, although we highlight some of the main findings from the surveys in this report, the necessarily limited scope precludes examination of many topics for which these surveys may be highly informative. To facilitate the utility of these data to stakeholders, managers, and researchers, we have released the data online (Bergamaschi and others, 2020) and created an online data exploration portal ( https:​//ca.water​.usgs.gov/​bay-​delta/​2018-​delta-​wide-​mapping-​surveys.html ) where users may query the surveys in a variety of ways to test hypotheses, examine relationships, assess spatial trends, and download data. The data exploration portal is intended to be an immersive experience that allows users to gain greater understanding of the complex interactions that shape Delta aquatic environments. This report is intended as a companion to the portal, allowing the reader to challenge and further explore the highlighted findings. This study was a collaboration between the U.S. Geological Survey and the Delta Regional Monitoring Program, with additional funding provided from U.S. Geological Survey Cooperative Matching Funds Program.

California↗