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USGS2024

Earthquake scenario development in conjunction with the 2023 USGS National Seismic Hazard Model

We present earthquake scenarios developed to accompany the release of the 2023 update to the US Geological Survey National Seismic Hazard Model (NSHM). Scenarios can serve a range of local and regional needs, from developing proactive-targeted mitigation strategies for minimizing impending risk to aiding emergency management planning. These deterministic scenarios can also be used to communicate seismic hazard and risk to audiences who are not well versed in methods, such as probabilistic seismic hazard analyses. Specifically, we discuss the scenarios developed, challenges, and lessons learned in the development process, and how this work aided the development of the 2023 NSHM itself. In total, 28 scenarios were developed for Hawaii, Utah, Alaska, and Virginia considering the 2023 NSHM science, past scenario efforts, and input from local experts and stakeholders. Finally, we investigate how NSHM modeling decisions can change estimated impacts to Utah and Hawaii in more detail showing, for example, that a shallower dip of the Wasatch fault under Salt Lake City can increase predicted ground-motion intensities and therefore estimated losses and deaths.

Earthquake Spectra↗

USGS2025

A geospatial analysis of water-quality threats from orphan wells in principal and secondary aquifers of the United States

Throughout the history of oil and gas production in the United States, millions of wells have been drilled for exploration and energy production. Hundreds of thousands of unplugged wells are no longer actively producing and are currently under orphan status, with no responsible party obligated for plugging. Orphan wells can pose threats to water resources by providing pathways for contaminants such as hydrocarbons and brines to migrate into water-supply aquifers. In this study, we investigate the potential threats to groundwater resources posed by orphan wells at the national scale. Water-quality data is extremely sparse in relation to orphan wells nationally and may not be suitable for identifying contamination from oil and gas development. We used geospatial and statistical methods to evaluate which principal and secondary aquifer systems may be most susceptible to contamination from orphan wells. Analysis involved three sets of susceptibility factors including: 1) factors related to the number and density of orphan wells; 2) factors that can threaten well integrity and contribute to transport of contaminants; and 3) factors related to groundwater withdrawal rates and the affected populations/communities in the event of water quality disturbances. From a dataset of 117,672 documented orphan wells, 64,203 fall within a principal aquifer system, while the remainder fall within a secondary aquifer system. By assessing the combination of well integrity and hydrogeologic factors within these aquifer systems, five groupings of principal aquifers were identified, where groups ranged from aquifer systems with high numbers of orphan wells, multiple well integrity threats and high withdrawals, to aquifers with a relatively low number of orphan wells, limited well integrity threats and minimal water use. Three regions of the country emerge containing aquifers with higher susceptibility to contamination from orphan oil and gas wells. These regions include 1) The Appalachian Basin (including the Pennsylvanian Aquifer System), 2) The Gulf Coast Aquifers (including the Coastal Lowlands Aquifer system) and 3) The California Aquifers (including the California Coastal Basin Aquifer system). This work is the first multivariate geospatial investigation of orphan wells and groundwater resources on a national scale, and sheds light on which aquifers are most susceptible to groundwater contamination from orphan wells.

Science of the Total Environment↗

USGS2025

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Colorado↗

USGS2026

Cascadia Subduction Zone science: Call for the next generation community seismic velocity model

The Cascadia subduction zone (CSZ) hosts major seismic and tsunami hazards, yet key questions persist about the relationship between margin structure, fluid distribution, episodic tremor and slip, shallow megathrust behavior, shaking and tsunamigenesis, and the resulting hazard estimates. Addressing these problems requires an empirically grounded, three‐dimensional seismic velocity model to illuminate subsurface structure and properties and to provide a basis for geophysical studies such as earthquake simulations and ground‐motion estimation. In May 2024, the National Science Foundation‐funded Cascadia Region Earthquake Science Center (CRESCENT) community velocity model (CVM) working group, with U.S. Geological Survey and regional partners, convened a workshop to identify priorities for such a model. Participants emphasized the features necessary for addressing key science questions, including implementing findability, accessibility, interoperability, and reusability (FAIR) access, capturing along‐strike and along‐dip structural heterogeneity, resolving shallow offshore–onshore structure, constraining elastic properties and quantifying their uncertainties for numerical wave propagation simulations, their validation benchmarks, and supporting associated accurate earthquake ground‐motion simulations and hazard assessments. This article describes the priorities defined in the workshop, and a description of how, guided by these needs, CRESCENT plans to develop multiple generations of a CVM to advance CSZ science and improve seismic and tsunami hazard modeling across the Pacific Northwest. The CVM will span the CSZ from the surface to ∼100 km depth, offshore and east of the Cascades into Idaho (∼132°–110° W) and the southern and northern tectonic regime transitions (∼36°–52° N) to capture the entire tectonic system as well as its surroundings.

Cascadia Subduction Zone↗

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↗

USGS2023

The 2023 US 50-State National Seismic Hazard Model: Overview and implications

The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard (both increases and decreases compared to previous NSHMs) are substantial because the new model considers more data and updated earthquake rupture forecasts and ground-motion components. In developing the 2023 model, we tried to apply best available or applicable science based on advice of co-authors, more than 50 reviewers, and hundreds of hazard scientists and end-users, who attended public workshops and provided technical inputs. The hazard assessment incorporates new catalogs, declustering algorithms, gridded seismicity models, magnitude-scaling equations, fault-based structural and deformation models, multi-fault earthquake rupture forecast models, semi-empirical and simulation-based ground-motion models, and site amplification models conditioned on shear-wave velocities of the upper 30 m of soil and deeper sedimentary basin structures. Seismic hazard calculations yield hazard curves at hundreds of thousands of sites, ground-motion maps, uniform-hazard response spectra, and disaggregations developed for pseudo-spectral accelerations at 21 oscillator periods and two peak parameters, Modified Mercalli Intensity, and 8 site classes required by building codes and other public policy applications. Tests show the new model is consistent with past ShakeMap intensity observations. Sensitivity and uncertainty assessments ensure resulting ground motions are compatible with known hazard information and highlight the range and causes of variability in ground motions. We produce several impact products including building seismic design criteria, intensity maps, planning scenarios, and engineering risk assessments showing the potential physical and social impacts. These applications provide a basis for assessing, planning, and mitigating the effects of future earthquakes.

Earthquake Spectra↗

USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗

USGS2025

Critical minerals in mine waste

Introduction Critical minerals are commodities with vulnerable supply chains that play a vital role in supporting the United States’ economy, national defense and security, emerging technologies, and energy independence. The prosperity of our Nation depends on generating a resilient supply of domestic critical minerals; mine waste may be an untapped source of these commodities. Mine waste from centuries of legacy mining persist on the landscape and may contain critical minerals and other valuable commodities previously deemed uneconomic to recover. At modern mines, the financial viability of recovering byproduct critical minerals, which are not the primary target, may be marginal and can ultimately destine them to mine waste. Further, mine waste can be a liability for the mining company or, at legacy mines, the taxpayer because of its effect on the landscape. The U.S. Geological Survey (USGS) has several initiatives to evaluate critical mineral resources in various types of waste. This factsheet highlights studies of mine waste carried out by USGS scientists at the Geology, Energy & Minerals Science Center in collaboration with other science centers funded through the USGS Mineral Resources Program. Recovery of critical minerals from mine waste can aid in remediation efforts and increase domestic supply of vital mineral resources.

Fact Sheet↗

USGS2026

Decadal trends and occurrence of geogenic constituents and mixtures in groundwater across the continental United States

Worldwide, about 50% of the population is served by groundwater-sourced drinking water. Numerous groundwater quality assessments have found that geogenic constituents are among the most common contaminants in drinking-water aquifers. Documenting changing groundwater quality is a crucial aspect of water availability assessments. We assess trends and occurrence of geogenic constituent concentrations in groundwater across the continental United States using 3 decades of data from the U.S. Geological Survey’s National Water Quality Network. Thousands of groundwater wells were grouped into agricultural, urban, or domestic supply network types. Although most networks and constituents had no statistically significant change in concentration, many had increasing concentration trends, elevated concentrations, or both. Lithium, sodium, radium, sulfate, and uranium had increasing trends in more than 10% of the study networks. Urban and domestic well networks had increasing lithium and sodium trends more often than agricultural networks. Manganese most commonly increased in domestic well networks; uranium more commonly increased in agricultural and urban networks. Elevated concentration mixtures were widespread, and mixture complexities appeared to increase over time. Our results indicate that more than 2.3 million domestic-well users may be affected by elevated concentrations of one or more geogenic constituents.

continental United States↗

USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗

USGS2024

Plan to coordinate post-earthquake investigations supported by the National Earthquake Hazards Reduction Program (NEHRP)

Introduction This report presents a plan supported by the National Earthquake Hazards Reduction Program (NEHRP) to coordinate domestic and international post-earthquake investigations (herein called “the Plan”). Post-earthquake scientific and engineering investigations are undertaken to capture critical information to understand the causes and impacts of the event, lessons from which can substantially improve the Nation’s resilience after future earthquakes. NEHRP is the Federal Government’s coordinated nationwide program to reduce risks to life and property from earthquakes. The Plan describes the activation and coordination of the four designated NEHRP Agencies in the Federal Government: Federal Emergency Management Agency, National Institute of Standards and Technology, U.S. National Science Foundation, and U.S. Geological Survey (USGS). The Plan also describes coordination between NEHRP Agencies and other organizations that may participate in pre-event and post-earthquake investigations, including non-NEHRP Federal agencies; State, regional, local, Tribal, and territorial agencies; domestic nongovernmental organizations; academic institutions and affiliated organizations; private companies; foreign governmental agencies and nongovernmental organizations; and international organizations. The Plan delineates the coordination of NEHRP post-earthquake scientific and engineering investigations to document the direct, indirect, and cascading physical and societal impacts from fault rupture and ground shaking hazards and from secondary hazards such as landslides, liquefaction, and tsunamis. In addition, the Plan identifies pre-event activities necessary to ensure that post-earthquake investigations are executed effectively. The USGS is the lead NEHRP Agency for activating and coordinating NEHRP post-earthquake investigations and for implementing this Plan. The USGS also leads coordination of the NEHRP Agencies in completing the pre-event activities identified in the Plan. The Plan has new information and supersedes USGS Circular 1242, “The Plan to Coordinate NEHRP Post-Earthquake Investigations,” which was published in 2003. This second-generation Plan was developed with the assistance of the Applied Technology Council (ATC) of Redwood City, California, under USGS contract 140G0121P0309, ATC-155. A 17-member Project Review Panel provided guidance on plan development, and input was solicited from subject matter experts representing key stakeholder groups and from participants at a public workshop.

Circular↗

USGS2025

Land-based nutrient flux to a fringing reef: Insights from Ofu Island, American Samoa

Submarine groundwater discharge (SGD) is a critical driver of nutrient transport in coral reef ecosystems, shaping water quality, primary productivity, and overall reef health. This study quantifies SGD fluxes and associated nutrient dynamics in two reef flat pools within the Ofu Unit of the National Park of American Samoa: Papaloloa and Fatuana. A multi-method approach integrating unoccupied aerial system-based thermal infrared (UAS-TIR) surveys, radon-based SGD measurements, multichannel electrical resistivity tomography (ERT), and discrete water sampling was used to assess SGD rates and nutrient contributions. UAS-TIR imagery revealed cooler sea surface temperatures in both pools, indicative of SGD, with the higher fluxes observed in Papaloloa. Radon measurements revealed a strong inverse correlation between SGD rates and tidal stage, with a more immediate SGD response at Papaloloa due to its highly permeable calcareous sand and gravel substrate. In contrast, a 2–3-hour lag in SGD response at Fatuana suggests discharge from a more inland aquifer that has lower diffusivity. Nutrient concentrations correlated with temperature and salinity, confirming SGD as the dominant nutrient transport mechanism, whereas isotopic analyses indicated inputs from both groundwater and potential anthropogenic sources. Despite lower SGD flux at Fatuana, higher algal cover suggests additional factors influencing algal proliferation, including substrate availability and hydrodynamic conditions. Excess nutrient inputs from SGD may contribute to algal overgrowth, which threatens Ofu’s thermally tolerant corals by increasing competition for space and light. These findings underscore the complexity of SGD-mediated nutrient dynamics in reef environments and emphasize the need for integrated hydrological and ecological assessments to support effective reef conservation and management strategies.

American Samoa, Ofu Island, Olosega Island↗

USGS2026

The Great Lakes Geologic Mapping Coalition—Working collaboratively to understand the geology of the Great Lakes Region

Introduction The Great Lakes Geologic Mapping Coalition (GLGMC), commonly referred to as the “Coalition,” is a partnership between the U.S. Geological Survey (USGS), the U.S. States of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin and the Canadian province of Ontario. The member States receive funding for geologic mapping work from the USGS National Cooperative Geologic Mapping Program (NCGMP), whereas Ontario participates as a nonfunded partner. The mission of the GLGMC is to produce three-dimensional (3D) geologic maps that depict unconsolidated sediments and near-surface bedrock in the Great Lakes region of North America. Geologic maps are the basis of most earth science investigations and help support resource exploration (energy, minerals, groundwater), natural hazard mitigation, infrastructure development, and land-use planning, all of which can be used to advance economic development and strengthen national security in the Great Lakes region. During the last few million years, the Great Lakes region has experienced repeated glacial advances and retreats, leaving behind extensive sediments, abundant natural resources, and widespread effects on the underlying bedrock geology (Swezey and others, 2022). Linked by shared histories of past glaciations, industrial agriculture, and legacy automotive, coal, steel, and manufacturing industries, the GLGMC member States collaborate to improve the understanding of the 3D distribution of the sediments overlying the region’s bedrock (fig. 1). Developing a comprehensive subsurface 3D framework of this glaciated terrain can provide earth science data to policymakers at all levels. These insights facilitate informed decisions on the exploration, use, and protection of vital resources, such as critical minerals, industrial materials, and aquifers, thereby supporting economic prosperity and the well-being of the citizens of this region. Since its inception in 1998, the Coalition has completed more than 100 geologic mapping projects across the Great Lakes region. Each project aims to deliver geologic maps, 3D datasets, and other information that improves understanding of the geology of the Great Lakes region, with an emphasis on economic and water resources. Key deliverables include 3D geologic maps and models typically portraying sediment thickness, often derived from top-of-bedrock and borehole data. These products are developed through a combination of fieldwork, subsurface modeling, and the collection and analysis of rock and sediment cores. To support Coalition goals, member States collaborate with scientists working on related STATEMAP, EDMAP, and FEDMAP projects. Coalition scientists also engage with Tribal Nations in the Great Lakes region to ensure that Tribal interests pertaining to Coalition work are addressed. Through this collaboration, the Coalition unites the efforts of State, Federal, and Tribal Nation stakeholders to advance geologic data production and enhance understanding of the geologic resources of the Great Lakes region.

Illinois, Indiana, Michigan, Minnesota, New York, ↗

USGS2024

Factors contributing to pesticide contamination in riverine systems: The role of wastewater and landscape sources

Wastewater treatment plant (WWTP) discharges can be a source of organic contaminants, including pesticides, to rivers. An integrated model was developed for the Potomac River watershed (PRW) to determine the amount of accumulated wastewater percentage of streamflow (ACCWW) and calculate predicted environmental concentrations (PECs) for 14 pesticides in non-tidal National Hydrography Dataset Plus Version 2.1 stream segments. Predicted environmental concentrations were compared to measured environmental concentrations (MECs) from 32 stream sites that represented a range of ACCWW and land use to evaluate model performance and to assess possible non-WWTP loading sources. Statistical agreement between PECs and MECs was strongest for insecticides, followed by fungicides and herbicides. Principal component analysis utilizing optical fluorescence and ancillary water quality data identified wastewater and urban runoff sources. Pesticides that indicated relatively larger sources from WWTPs included dinotefuran, fipronil, carbendazim, thiabendazole, and prometon whereas imidacloprid, azoxystrobin, propiconazole, tebuconazole, and diuron were more related to urban runoff. In addition, PECs generally comprised a low proportion of MECs, which indicates possible dominant loading sources beyond WWTP discharges. Cumulative potential toxicity was higher for sites with greater ACCWW and/or located in developed areas. Imidacloprid, fipronil, and carbendazim accounted for the largest portion of predicted potential toxicity across sites. The chronic aquatic life toxicity benchmarks for freshwater invertebrates were exceeded for 82 % of the imidacloprid detections ( n = 28) and 47 % of the fipronil detections ( n = 19). These results highlight the ecological implications of pesticide contamination from WWTP discharges and also the potential legacy effects from accumulated soil and groundwater sources. Pesticide management strategies that mitigate both current and historical impacts may improve the health of aquatic ecosystems.

Potomac River watershed↗

USGS2025

USGS—An Unparalleled Scientific Asset

The U.S. Geological Survey (USGS) delivers information critical to powering our economy, managing our natural resources, and keeping Americans safe and healthy. 1 Mapping the Nation $21B Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B. $25.6B in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS. $13.5B in annual benefits is generated by the USGS's 3D Elevation Program. Securing America’s Energy Independence 44% USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation. 29.4B barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments. Protecting Americans’ Health and Safety $424B in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk. USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption. $4.5B is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property. Supporting National Security $3.1B The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list. Enhancing Our Lands and Waters $21B in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation. USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone. $45B USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy. Fostering American Prosperity $4.1T Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued. 45,000 metric tons Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply. Guarding American Food Security $70.2B USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production. $11.8B USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry. 1 Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.

General Information Product↗

USGS2024

The U.S. Geological Survey Ohio Water Microbiology Laboratory

The U.S. Geological Survey Ohio Water Microbiology Laboratory is a part of the Ohio-Kentucky-Indiana Water Science Center. The mission of the laboratory is to provide microbiological data of public health significance from surface waters, groundwaters, and sediments for a variety of study objectives. The laboratory conducts internal projects, works with external cooperators, and assists U.S. Geological Survey offices and National programs. The laboratory offers guidance, study design, and data interpretation expertise to collaborators, all following rigorous quality control and quality assurance procedures.

Fact Sheet↗

USGS2025

Four-band image mosaic of the Colorado River Corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition

In May 2021, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four spectral bands (red, band 1; green, band 2; blue, band 3; and near infrared, band 4) with a ground resolution of 20 centimeters, are available as 16-bit unsigned-integer GeoTIFF files in Sankey and others (2024) (available online at https://doi.org/10.5066/P9BBGN6G ). The image files are projected in the State Plane Coordinate System, using the central Arizona zone (202) with the North American Datum of 1983 National Adjustment of 2011. The assessed spatial accuracy for these data is based on 47 ground-control points that were independent from the ground-control points used by the contractor for aerotriangulation and is reported at the 95-percent confidence level as 0.514 meter (m) and a root mean square error of 0.297 m. The intended uses of this dataset are primarily in support of scientific research and monitoring applications. Examples of these applications include high-resolution spatial and temporal change detection of the river channel, geomorphic landforms, riparian vegetation, and backwater and nearshore habitat, as well as other ecosystem-wide mapping. These imagery data also serve as reference material for field science mission planning, as base data for field data collection including community science activities, and as a highly detailed guide for technical boat operation during science activities such as reconnaissance for nighttime missions and navigating rapids during low flows.

Arizona, Nevada, Utah↗

USGS2026

Mountain goat declines in a protected, interior, native population

A shifting climate poses threats to alpine-adapted species including mountain goats. We used long-term (12 years) citizen science monitoring data and Bayesian N-mixture modeling to estimate population trends and drivers of population metrics among mountain goats in Glacier National Park (GNP). Median goats per site ( n = 37 sites) declined by 45% (95% credible interval [CRI] = 32%, 57%) from 77.8 (95% CRI = 64.4, 95.1) in 2008 to 42.3 (95% CRI = 34.3, 52.2) in 2019, with consistent declines from 2008 until 2015, when the number of estimated goats stabilized. The decline exceeds IUCN criteria for classifying a population as vulnerable, >30% declines over only two generations. Across years, relatively few goats occupied northwestern GNP. Goat numbers declined the most at northeastern sites, trended toward decline in most southern sites, and increased at only two west-central sites. The proportion of permanent snow and glaciers, the presence of natural mineral licks, and habituation strongly increased the initial abundance of goats in the area. Weather variables had the greatest influence on population growth rates, particularly precipitation between May 15 and June 15 of the previous summer, the neonatal period. Lower growth occurred with less snow water equivalent and lower mean winter temperature, early summer temperature, and early summer precipitation. Projected reductions of permanent snow, increasing spring and summer temperatures, and insufficient and variable spring precipitation raise concerns for the future of native goats in this region. Our analyses reveal ways to improve detection rates of goats during surveys, which is important for optimizing the precision of estimates and the power to detect future trends. Detection increased with goat habituation, retention of observers with experience, use of binoculars, and conducting surveys at lower temperatures and earlier dates. Improving detection will be particularly important given the lower number of goats currently observed in the park. Research to estimate park-wide population size, evaluate genetic structure and diversity, assess changing habitat, human recreation levels and forage, and forward-project climate effects on persistence will be crucial to understanding the context of these results and conserving this iconic, metapopulation at the southern edge of the distribution of native mountain goats.

Montana↗