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USGS2026

USGS 2025 critical minerals review

The United States Geological Survey (USGS) provides scientific information for the Department of Interior and the nation, consistent with its original mission expressed in the Organic Act of 1879 (43 U.S.C. 31): “the classification of the public lands and examination of the geological structure, mineral resources, and products within and outside the national domain.” Legislation such as the Energy Act of 2020 and the 2022 Infrastructure Investment and Jobs Act (43 USC 31l) and recent executive actions (Executive Orders 14154 , 14153, 14241 Secretary’s Orders 3417, 3418, 3422, 3436) underscore the importance of mineral resources and focus USGS activities on mapping and assessing mineral resources, with a particular focus on those presently identified as critical, both in ground and above ground in mine wastes. This article reviews selected activities and accomplishments by the USGS Mineral Resources Program related to critical minerals in 2025. Highlights include a new List of Critical Minerals, a first-ever national mine waste inventory, international minerals partnerships, mineral resource assessment advancements, and national data collection activities and outcomes of the Earth Mapping Resources Initiative (Earth MRI). The selected contributions are not comprehensive but are intended to demonstrate USGS leadership in critical mineral mapping and assessment, the importance of domestic and global partnerships, and the breadth of research activities that are responsive to national needs and priorities.

Mining Engineering↗
USGS2025

Review: The hydrogeology of critical mineral resources relevant to the energy transition

Attaining the goals of the international treaty on climate change (the Paris Agreement) will greatly increase the demand for the critical minerals required to implement clean-energy technologies. This poses both challenges and opportunities to the hydrogeologic community from several perspectives. Here, important insights that the hydrogeological sciences have to offer for mineral exploration, mineral production, and addressing environmental issues related to mining and mine decommissioning are summarized. This study focuses on copper, cobalt, lithium, and rare earths to represent the broad spectrum of critical minerals and illustrate their relevance by referring to projected demands and production rates. The current understanding of the hydrogeologic processes that form major deposits of these minerals are then summarized. Ore is defined as the naturally occurring material from which minerals of economic value can be extracted, where most ore deposits are the products of complex hydrogeologic couplings between fluid flow, heat transport, solute transport, chemical reactions, and mechanical deformation. Exploration models for the discovery of deeper, hidden deposits are potentially informed by hydrogeologic theory and hydrogeochemical processes. Hydrogeologic understanding and methods are also essential to production and recovery. Longstanding challenges are mine dewatering and (conversely) mine water supply, as well as mineral-extraction practices such as spoil heap leaching and in situ mining. New challenges arise from element extraction from subsurface brines. Finally, the quantity of water use and potential environmental impacts of mining on water quality are at the core of ‘social license’: the approval and acceptance of society to mining activities.

Hydrogeology Journal↗
USGS2026

Assessing the state of hydrologic science in the Upper Klamath Basin—A comprehensive review of data, tools, and models

Water demand in the Upper Klamath Basin (UKB) from various stakeholders and ecological needs often outstrips available supply, leading to persistent management challenges. This study reviews the state of hydrologic science within the UKB as of 2025—specifically, the tools, data, and models available for assessing five key components of the water system: (1) surface water; (2) precipitation; (3) evapotranspiration; (4) groundwater; and (5) water use. The UKB water supply is critical for Native American communities, regional agriculture, and federally listed fishes and faces challenges from competing needs, climate variability, and operational/regulatory requirements. We assess existing datasets, regional and national models, and historical studies to understand the available resources and identify gaps that may hinder integrated water assessments and management. Our findings indicate areas where improvements in data collection and model precision could improve the accuracy of water-availability forecasts and support water-management practices. This review can inform near-term forecasting, assist in optimizing water-resource data collection and management strategies, and support regional water-availability assessments of the basin.

Oregon↗
USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗
USGS2024

The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates

LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.

Fire↗
USGS2026

Global pegmatite-hosted lithium, cesium, and rubidium resources: A dataset for grade and tonnage modeling

Quantitative mineral resource assessments of potential undiscovered deposits can inform future mineral supply scenarios, but their accuracy is conditional on building robust grade and tonnage models of known deposits. This study presents an up-to-date global compilation and analysis of recently discovered and original, in-situ pegmatite-hosted Li, Cs, and Rb resources prior to historic production. Our analysis yields a median tonnage of 21.2 million tons (Mt) and grade of 1.12% Li 2 O, respectively, for global Li pegmatite deposits ( n = 73). The grades and tonnages of Li pegmatite resources vary depending on the age of the bedrock host domain, pegmatite crystallization age, and primary ore mineralogy. Lithium pegmatite resources hosted in Archean to transitional Archean-Paleoproterozoic domains have the largest median tonnage (29.8 Mt; n = 38), and those hosted in Paleoproterozoic to Mesoproterozoic domains have smaller median tonnages (6.5 Mt; n = 16). Cesium deposits where pollucite is the primary ore mineral have a bimodal grade distribution, with modes of 2.40 and 0.035 wt% Cs 2 O for high- and low-grade deposits, respectively, while Rb deposits are more unimodal with a median grade of 0.247 wt% Rb 2 O. Pegmatite-hosted Cs and Rb resources have median tonnages of 7.6 and 6.3 Mt, respectively. Covariation between ore mineralogy and the degree of crustal enrichment in pegmatite-hosted deposits is diagnostic of petrogenetic differences, including melt source characteristics, magma evolution, or variable degrees of volatile solubility. The Li pegmatite compilation is suitable for fitting robust numerical models to support quantitative assessments. More well-defined Rb and Cs pegmatite resources are required for quantitative assessments, but these data provide useful information about original in-place resources for framing supply discussions.

Ore Geology Reviews↗
USGS2025

Cooling perspectives on the risk of pathogenic viruses from thawing permafrost

Climate change is inducing wide-scale permafrost thaw in the Arctic and subarctic, triggering concerns that long-dormant pathogens could reemerge from the thawing ground and initiate epidemics or pandemics. Viruses, as opposed to bacterial pathogens, garner particular interest because outbreaks cannot be controlled with antibiotics, though the effects can be mitigated by vaccines and newer antiviral drugs. To evaluate the potential hazards posed by viral pathogens emerging from thawing permafrost, we review information from a diverse range of disciplines. This includes efforts to recover infectious virus from human remains, studies on disease occurrence in polar animal populations, investigations into viral persistence and infectivity in permafrost, and assessments of human exposure to the enormous viral diversity present in the environment. Based on currently available knowledge, we conclude that the risk posed by viruses from thawing permafrost is no greater than viruses in other environments such as temperate soils and aquatic systems.

mSystems↗
USGS2025

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter↗
USGS2026

Microclimate mediates the strength and direction of avian biotic interactions

Theory predicts that that the strength and direction of species interactions can shift from being competitive in benign environments toward being facilitative in stressful environments. However, the environmental context dependency of species interactions has rarely been tested in animal communities. We capitalized on a 15-year, landscape-scale dataset, collected annually in a relatively stable old-growth forest environment to test the long-held hypothesis that the strength and direction of species interactions might be mediated by climatic conditions. It is generally accepted that competitive and facilitative interactions drive the distributions of many species. Using multi-species dynamic occupancy models applied to long-term data, we tested whether annual settlement by bird species could affect either the persistence or settlement by other phylogenetically related species, and whether these interactions are mediated by microclimate. We found that species interactions were influenced by microclimate for some, but not all avian species pairs. Related species pairs more often showed settlement dynamics that were indicative of attraction rather than repulsion. In some cases, competitive interactions at warmer microclimates flipped to become facilitative in colder ones. However, the reverse was also true: facilitative interactions amplified for some species under warm conditions. Furthermore, species pairs that were closely related were more likely to exhibit competitive relationships along at least part of the microclimatic gradient. Our results highlight the importance of using long-term data to incorporate competitive and facilitative interactions into species distribution models and support the notion that the strength and direction of species interactions can be dependent on microclimatic environmental conditions.

Oregon↗
USGS2025

Microbial ecology of permafrost soils: Populations, processes, and perspectives

Permafrost microbial research has flourished in the past decades, due in part to improvements in sampling and molecular techniques, but also the increased focus on the permafrost greenhouse gas feedback to climate change and other ecological processes in high latitude and alpine permafrost soils. Permafrost microorganisms are adapted to these extreme environments and remain active at low temperatures and when resources are limited. They are also an important component of global elemental cycles as they regulate organic matter turnover and greenhouse gas production, particularly as permafrost thaws. Here we review the permafrost microbiology literature coupled with an exploration of its historical aspects, with a particular focus on a new understanding advanced by molecular biology techniques. We further identify knowledge gaps and ways forward to improve our understanding of microbial contributions to ecosystem biogeochemistry of permafrost-affected systems.

Permafrost and Periglacial Processes↗
USGS2025

Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health

Produced water is a chemically complex waste stream generated during oil and gas development. Roughly four trillion liters were generated onshore in the United States in 2021 (ALL Consulting, 2022, https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf ). Efforts are underway to expand historic uses of produced water to offset freshwater needs in water-stressed regions, avoid induced seismic activity associated with its disposal, and extract commodities. Understanding the potential exposures from current and proposed produced water uses and management practices can help to inform health-protective practices. This review summarizes what is known about potential human exposure to produced water from onshore oil and gas development in the United States. We synthesize 236 publications to create a conceptual model of potential human exposure that illustrates the current state of scientific inquiry and knowledge. Exposure to produced water can occur following its release to the environment through spills or leaks during its handling and management. Exposure can also arise from authorized releases, including permitted discharges to surface water, crop irrigation, and road treatment. Knowledge gaps include understanding the variable composition and toxicity of produced water released to the environment, the performance of treatment methods, migration pathways through the environment that can result in human exposure, and the significance of the exposures for human and ecosystem health. Reducing these uncertainties may help in realizing the benefits of produced water use while simultaneously protecting human health.

Environmental Health Perspectives↗
USGS1996

Techniques to estimate generalized skew coefficients of annual peak streamflow for natural basins in Texas

This report presents two techniques to estimate generalized skew coefficients used for log-Pearson Type III peak-streamflow frequency analysis of natural basins in Texas. A natural basin has less than 10 percent impervious cover, and less than 10 percent of its drainage area is controlled by reservoirs. The estimation of generalized skew coefficients is based on annual peak and historical peak streamflow for all U.S. Geological Survey streamflow-gaging stations having at least 20 years of annual peak-streamflow record from natural basins in Texas. Station skew coefficients calculated for each of 255 Texas stations were used to estimate generalized skew coefficients for Texas. One technique to estimate generalized skew coefficients involved the use of regression equations developed for each of eight regions in Texas, and the other involved development of a statewide map of generalized skew coefficients. The weighted mean of the weighted mean standard errors of the regression equations for the eight regions is 0.36 log 10 skew units, and the weighted mean standard error of the map is 0.35 log 10 skew units. The technique based on the map is preferred for estimating generalized skew coefficients because of its smooth transition from one region of the State to another.

Texas↗
USGS2024

A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps

Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes > fire characteristics > ecologic processes and characteristics > land surface characteristics > soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.

Water Resources Research↗
USGS2025

Assessment of western Oregon debris-flow hazards in burned and unburned environments

In the steep and mountainous environment of western Oregon, debris flows pose a considerable threat to property, infrastructure and life. Wildfire is commonly known to increase the susceptibility of steep slopes to debris flows, but the extent of this process in the western Cascades is not well understood. The US Geological Survey (USGS) currently estimates postfire debris-flow likelihood and triggering rainfall thresholds using a model calibrated to a southern California inventory of debris flows generated by excess runoff within the first year after fire. Because of a lack of available data, this model has not been tested in western Oregon, or in locations where postfire debris flows initiate via other mechanisms (e.g., shallow landslides or in-channel failures). Using repeat field observations and aerial imagery, we developed two new debris-flow inventories within and adjacent to the perimeters of five 2020 wildfires in western Oregon: Archie Creek, Holiday Farm, Beachie Creek, Lionshead and Riverside. The first inventory focuses on postfire debris flows (2020–2022); the second focuses on debris flows prior to fires (1995–2020). Our inventories of prefire and postfire debris flows were used to document initiation mechanisms in Oregon's western Cascades and to evaluate the effects of wildfire. We found that wildfire changed the distribution of debris-flow initiation mechanisms in the western Cascades. After the wildfires, annual rates of runoff-generated debris flows increased by 22% and the number of shallow landslide-initiated debris flows decreased by 17% relative to before the wildfires. Despite this shift, shallow landsliding was the dominant debris-flow initiation mechanism in both unburned and burned environments. We found the performance of the current USGS debris-flow likelihood model was degraded relative to other previously tested locations across the intermountain western United States. Our results highlight the need for improved postfire hazard assessment in western Oregon based on regional model calibration that is tuned to the dominant debris-flow initiation mechanisms.

Oregon↗
USGS2026

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

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

Earth-Science Reviews↗
USGS2026

The United States Magnetotelluric Array and the National Impedance Map

The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long-period magnetotelluric stations covering the entirety of the contiguous United States on a quasi-regular 70 km grid. Funding across multiple federal agencies was critical to sustaining this effort to its completion. Important components of the project included active guidance and participation from the MT community, the open and timely availability of all data, and the application of consistent instrumentation and robust data processing. Together with parallel advancement in the development of publicly available three-dimensional (3D) inversion codes, the USMTArray has revitalized the US magnetotelluric community and increased the visibility of magnetotellurics within the Earth-science community. Taken as a whole, these data are visualized as the National Impedance Map, which, together with a 3D synthesis conductivity model of the nation, reveals the electrical architecture of the contiguous US. USMTArray data are used by researchers worldwide for fundamental and applied studies, including investigations of continental architecture and evolution, estimation of hazards to critical infrastructure due to geomagnetic storms, and assessment of the nation's undiscovered geothermal and mineral resources. We here review the history and development of the project, discuss the challenges and successes in its execution, present the National Impedance Map and synthesis conductivity model, and highlight the breadth of research stemming from this rich data set.

conterminous United States↗