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USGS2026

Coastal and Marine Hazards and Resources Program decadal science strategy 2020–2030

Overview The decadal science strategy of the Coastal and Marine Hazards and Resources Program (CMHRP) of the U.S. Geological Survey for 2020 to 2030 describes the CMHRP's vision and mission and the strategic framework needed to support key program goals: Conduct research and develop science-based tools that lead to safer, more productive coastal communities and improved stewardship of natural resources.

Circular↗
USGS2025

Engineering and risk research—A strategic vision for extending USGS earthquake science to risk assessment and mitigation

As a part of the U.S. Geological Survey (USGS) Natural Hazards Mission Area, the Engineering and Risk Project (ERP) of the Geologic Hazards Science Center conducts civil engineering research to extend natural hazards science to risk assessments. The ERP includes predominantly, but not exclusively, staff funded by the USGS Earthquake Hazards Program. A major focus of the ERP is to deliver actionable information to decisionmakers that helps promote the safety, security, and economic well-being of the Nation. The report discusses briefly the ERP’s evolution and scope, its organization structure, describes key products and deliverables, their efforts to engage with external partners, and its strategy and vision in conducting range of engineering and risk research. The research topics outlined in this report, as developed by the ERP, may be used to facilitate project planning activities during the next 10 years and serve as a longer-term planning resource for the USGS Earthquake Hazards Program and Geologic Hazards Science Center.

Circular↗
USGS2025

Factors regulating the potential for freshwater mineral soil wetlands to function as natural climate solutions

There are increasing global efforts and initiatives aiming to tackle climate change and mitigate its impacts via natural climate solutions (NCS). Wetlands have been considered effective NCS given their capacity to sequester and retain atmospheric carbon dioxide (CO 2 ) while also providing a myriad of other ecosystem functions that can assist in mitigating the impacts of climate change. However, wetlands have a dual impact on climate, influencing the atmospheric concentrations of both CO 2 and methane (CH 4 ). The cooling effect associated with wetland CO 2 sequestration can be counterbalanced by the warming effect caused by CH 4 emissions from wetlands. The relative ability of wetlands to sequester CO 2 versus emit CH 4 is dependent on a suite of interacting physical, chemical, and biological factors, making it difficult to determine if/which wetlands are considered important NCS. The fact that wetlands are embedded in landscapes with surface and subsurface hydrological connections to other wetlands (i.e., wetlandscapes) that flow over and through geochemically active soils and sediments adds a new layer of complexity and poses further challenges to understanding wetland carbon sequestration and greenhouse gas fluxes at large spatial scales. Our review demonstrates how additional scientific advances are required to understand the driving mechanisms associated with wetland carbon cycling under different environmental conditions. It is vital to understand wetland functionality at both wetland and wetlandscape scales to effectively implement wetlands as NCS to maximize ecological, social, and economic benefits.

Wetlands↗
USGS2025

Towards mobile wind measurements using joust configured ultrasonic anemometer for applications in gas flux quantification

Small uncrewed aerial systems (sUASs) can be used to quantify emissions of greenhouse and other gases, providing flexibility in quantifying these emissions from a multitude of sources, including oil and gas infrastructure, volcano plumes, wildfire emissions, and natural sources. However, sUAS-based emission estimates are sensitive to the accuracy of wind speed and direction measurements. In this study, we examined how filtering and correcting sUAS-based wind measurements affects data accuracy by comparing data from a miniature ultrasonic anemometer mounted on a sUAS in a joust configuration to highly accurate wind data taken from a nearby eddy covariance flux tower (aka the Tower). These corrections had a small effect on wind speed error, but reduced wind direction errors from 50° to >120° to 20–30°. A concurrent experiment examining the amount of error due to the sUAS and the Tower not being co-located showed that the impact of this separation was 0.16–0.21 ms − 1 "> ms − 1 , a small influence on wind speed errors. Lower wind speed errors were correlated with lower turbulence intensity and higher relative wind speeds. There were also some loose trends in diminished wind direction errors at higher relative wind speeds. Therefore, to improve the quality of sUAS-based wind measurements, our study suggested that flight planning consider optimizing conditions that can lower turbulence intensity and maximize relative wind speeds as well as include post-flight corrections.

Alaska↗
USGS2024

Reference 1D seismic velocity models for volcano monitoring and imaging: Methods, models, and applications

Seismic velocity models of the crust are an integral part of earthquake monitoring systems at volcanoes. 1D models that vary only in depth are typically used for real‐time hypocenter determination and serve as critical reference models for detailed 3D imaging studies and geomechanical modeling. Such models are usually computed using seismic tomographic methods that rely on P ‐ and S ‐wave arrival‐time picks from numerous earthquakes recorded at receivers around the volcano. Traditional linearized tomographic methods that jointly invert for source locations, velocity structure, and station corrections depend critically on having reasonable starting values for the unknown parameters, are susceptible to local misfit minima and divergence, and often do not provide adequate uncertainty information. These issues are often exacerbated by sparse seismic networks, inadequate distributions of seismicity, and/or poor data quality common at volcanoes. In contrast, modern probabilistic global search methods avoid these issues only at the cost of increased computation time. In this article, we review both approaches and present example applications and comparisons at several volcanoes in the United States, including Mount Hood (Oregon), Mount St. Helens (Washington), the Island of Hawai’i, and Mount Cleveland (Alaska). We provide guidance on the proper usage of these methods as relevant to challenges specific to volcano monitoring and imaging. Finally, we survey‐published 1D P ‐wave velocity models from around the world and use them to derive a generic stratovolcano velocity model, which serves as a useful reference model for comparison and when local velocity information is sparse.

Seismological Research Letters↗
USGS2026

Escherichia coli monitoring and assessment in 2022 and 2023 after beach restoration at Lake St. Clair Metropark Beach, Macomb County, Michigan

Lake St. Clair Metropark Beach in Michigan has a history of closures because of elevated Escherichia coli ( E. coli ) concentrations in its recreational waters. To reduce closures, restoration projects were implemented in 2021 to deter waterfowl from congregating on the beach. In this study, the U.S. Geological Survey, in cooperation with the Michigan Department of the Environment, Great Lakes, and Energy and in collaboration with Huron-Clinton Metroparks and the Macomb County Health Department, monitored E. coli from 2022–23 in surface water, shallow groundwater, and sediment at Lake St. Clair Metropark Beach. Results were compared to data from a prerestoration (2018–19) study. A significant decrease in daily geometric mean E. coli concentrations in surface water was observed postrestoration, but the number of high concentration events increased. This resulted in more frequent beach closures postrestoration. Surface-sediment E. coli concentrations significantly decreased after restoration, and waterfowl populations generally decreased from 2021 to 2023, suggesting that the deterrence measures could be influencing E. coli concentrations in surface sediments and surface water. Groundwater E. coli concentrations were orders of magnitude higher than those in surface water and revealed no change correlated with restoration. Seepage measurements indicated that groundwater occasionally discharges into surface water, potentially providing a transport mechanism for E. coli to reach the lake. Continued monitoring and consideration of environmental factors could help to better understand the beach system.

Michigan↗
USGS1990

Large springs in the Valley and Ridge Province in Tennessee

Approximately 2,700 miscellaneous discharge measurements for 171 large springs in 28 counties of East Tennessee, predominantly within the Valley and Ridge physiographic province, were analyzed statistically and results tabulated to summarize data useful to the Appalachian Valleys-Piedmont Regional Aquifer System Analysis study. The number of measurements at each spring ranged from 1 to 65. Information from each spring includes station numbers, latitude, longitude, spring name and where data are sufficient, an estimate of the mean discharge and the discharge exceeded by 75%, 50%, and 25% of the miscellaneous measurements. Data are referenced to locations on a 1:1,000 ,000-scale map. The highest mean spring discharge was 32.2 cu ft/sec (14,5000 gallons/min).

Tennessee↗
USGS2025

U.S. Geological Survey global seabed mineral resources

The U.S. Geological Survey (USGS) provides science and data on seabed mineral resources and ecosystems, as well as on the potential hazards associated with extraction. The Nation relies on minerals for infrastructure, technology, manufacturing, and energy production. Critical minerals are essential to the economic and national security of the United States and have a supply chain vulnerable to disruption. For decades, USGS scientific innovation has contributed to the delineation of seabed mineral resources, the mechanisms of seabed mineral formation, and the environmental impacts of resource extraction. Since 1962, the USGS has also led scientific inquiries into the potential for deep sea mining. By providing impartial science on seabed minerals and their environmental setting in the deep oceans, the USGS enables decision-makers to evaluate the best practices for mineral resource development.

Fact Sheet↗
USGS2026

Regional models for postfire debris-flow likelihood and rainfall thresholds across the western United States

The U.S. Geological Survey (USGS) uses an empirical model developed with logistic regression (the ‘M1’ model) to rapidly assess debris-flow likelihood and to identify quantitative rainfall thresholds for debris flows after wildfire in the western United States. The M1 model was calibrated to a debris-flow inventory from southern California (United States) and has been applied throughout the western United States. Limited spatial coverage in the calibration dataset has motivated evaluation of M1 model accuracy outside the calibration region (e.g., the Sierra Nevada or the eastern Cascade Range, United States). Previous test cases showed that M1 overpredicts debris-flow likelihood and underpredicts rainfall thresholds for some locations (e.g., Arizona, northern California, Colorado, New Mexico, United States). We sought to improve the regional applicability of a debris-flow likelihood model by expanding the debris-flow inventory used for calibration, testing multiple potential models and generating an updated model framework. The updated inventory includes 3788 observations from 67 burned areas paired with short duration rainfall ratios. The updated model framework consists of a modified model structure and sets of coefficients calibrated separately to the entire updated inventory and to subsets of the inventory that intersect three Environmental Protection Agency (EPA) Level 2 ecoregions (Mediterranean California, Upper Gila Mountains and Western Cordillera). Comparisons of predictions from the updated models with observed rainfall and debris-flow activity show that the updated models outperform the M1 model by ~15%–60% and improve the uniformity of predictive performance across the western United States. The updated models also reduce false positive rates relative to M1 and generate rainfall thresholds that are better aligned with relative differences in regional climatology and debris-flow activity.

Arizona, California, Colorado, Idaho, Montana, Nev↗
USGS2026

Final project peport for “Mapping riparian vegetation response to climate change on the San Carlos Apache Reservation and Upper Gila River watershed to inform restoration priorities: 1935 to present – Phase 2: Focus on tamarisk vegetation”

Riparian ecosystems play a critical role in supporting wildlife habitats, maintaining water quality, and sustaining ecological resilience in arid landscapes. In the Upper Gila River level-4 Hydrologic Unit Code (HUC-4; Identification Number – 1504) watershed of Arizona and New Mexico, and across areas of the San Carlos Apache Tribe of the San Carlos Apache Reservation (hereafter, Tribe/Tribal – entity; or Reservation - place), riparian ecosystems have been substantially altered by the widespread expansion of tamarisk ( Tamarix spp.), an invasive and non-native riparian species. Tamarisk has high water use and increased flammability, making it a growing concern as droughts intensify across the southwestern United States (U.S.). Recent research indicates that tamarisk is increasingly stressed under prolonged drought conditions, which can elevate wildfire risk and further degrade riparian habitat. In response, the U.S. Geological Survey (USGS) Western Geographic Science Center, in collaboration with the Tribe, developed remote sensing–based tools to map riparian vegetation composition and monitor vegetation condition over time. These tools enable accurate identification of tamarisk extent, detection of vegetation stress, and comparison with native species such as cottonwood and willow. This information directly supports restoration and management actions, including targeted tamarisk removal, protection of endangered species habitat, and prioritization of areas for native vegetation recovery. The tools also provide insight into how riparian vegetation responds to changing climate and hydrologic conditions, strengthening long-term planning for riparian forest management. Findings from this work demonstrate that riparian vegetation responses vary across river systems, indicating differences in plant composition and hydro-climatic conditions. Tamarisk on both the Gila and San Carlos Rivers generally exhibit greater declines in greenness in response to higher temperature as well as lower precipitation and river flow, while cottonwood ( Populus fremontii ) and willow (Salix spp.) are particularly sensitive to changes in discharge along the San Carlos River and respond more directly to both high and low flows, with more moderate responses to precipitation and temperature. By providing actionable, science-based information, this research supports climate adaptation planning, wildfire risk reduction, and improved riparian ecosystem health, with benefits that extend beyond the Reservation to regional water and wildlife conservation efforts.

Arizona, New Mexico↗
USGS2025

Niobium-rich minerals from the Sheep Creek carbonatite-related deposits, Montana, USA

The Sheep Creek area in southwest Montana contains a number of small, tabular, carbonatite-related deposits that are rich in Nb- and REE-minerals. Two of the “vein-dikes” were mined at a small scale for Nb in the late 1950s. The most abundant Nb-bearing minerals are columbite-(Fe), nioboaeschynite-(Ce), baotite, and two varieties of Ti-Nb-Fe-oxide. An early oxide with Ti/Nb (atomic) near unity later broke down to a mixture of columbite + TiO2 with distinctly lower Nb content. Zircon intergrown with the Nb-REE minerals was dated by U-Pb methods to 116±2 Ma. This age is in agreement with previous dating (Th-Pb on monazite, Re-Os on molybdenite), and indicates that the Sheep Creek deposits are early Cretaceous in age.

Montana↗
USGS2026

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters↗
USGS2024

Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland

Mineral-rich hardgrounds, such as ferromanganese (FeMn) crusts and phosphorites, occur on seamounts and continental margins, gaining attention for their resource potential due to their enrichment in valuable metals in some regions. This study focuses on the Southern California Borderland (SCB), an area characterized by uneven and heterogeneous topography featuring FeMn crusts, phosphorites, basalt, and sedimentary rocks that occur at varying depths and are exposed to a range of oxygen concentrations. Due to its heterogeneity, this region serves as an optimal setting for investigating the relationship between mineral-rich hardgrounds and benthic fauna. This study characterizes the density, diversity, and community composition of macrofauna (>300 μm) on hardgrounds as a function of substrate type and environment (depth and oxygen ranges). Rocks and their macrofauna were sampled quantitatively using remotely operated vehicles (ROVs) during expeditions in 2020 and 2021 at depths above, within, and below the oxygen minimum zone (OMZ). A total of 3,555 macrofauna individuals were counted and 416 different morphospecies (excluding encrusting bryozoans and hydrozoans) were identified from 82 rocks at depths between 231 and 2,688 m. Average density for SCB macrofauna was 11.08 ± 0.87 ind. 200 cm −2 and mean Shannon-Wiener diversity per rock (H′ [loge] ) was 2.22 ± 0.07. A relationship was found between substrate type and macrofaunal communities. Phosphorite rocks had the highest H′ of the four substrates compared on a per-rock basis. However, when samples were pooled by substrate, FeMn crusts had the highest H′ and rarefaction diversity. Of all the environmental variables examined, water depth explained the largest variance in macrofaunal community composition. Macrofaunal density and diversity values were similar at sites within and outside the OMZ. This study is the first to analyze the macrofaunal communities of mineral-rich hardgrounds in the SCB, which support deep-ocean biodiversity by acting as specialized substrates for macrofaunal communities. Understanding the intricate relationships between macrofaunal assemblages and mineral-rich substrates may inform effects from environmental disruptions associated with deep-seabed mining or climate change. The findings contribute baseline information useful for effective conservation and management of the SCB and will support scientists in monitoring changes in these communities due to environmental disturbance or human impact in the future.

California↗
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↗
USGS2026

Estimating aftershock risk for entry into earthquake-damaged buildings

We present a simple method to estimate the risk of experiencing strong shaking from aftershocks during entry into earthquake-damaged buildings. We compute wait times until the probability of strong ground shaking from aftershocks reaches a predefined risk threshold; for example, a 0.4 percent probability of experiencing Modified Mercalli Intensity 7 or greater shaking during the planned building entry. We also develop a relation between aftershock probability and the probability of strong shaking, so that users can reference the U.S. Geological Survey aftershock forecast during an ongoing aftershock sequence to determine if the risk threshold has been met. We apply our method to active continental regions (for example, the Western United States), stable continental regions (for example, the Central and Eastern United States), and subduction zones (for example, Cascadia or Alaska).

Open-File Report↗
USGS2024

Parsimonious high-resolution landslide susceptibility modeling at continental scales

Landslide susceptibility maps are fundamental tools for risk reduction, but the coarse resolution of current continental-scale models is insufficient for local application. Complex relations between topographic and environmental attributes characterizing landslide susceptibility at local scales are not transferrable across areas without landslide data. Existing maps with multiple susceptibility classifications under-represent landslide potential in moderate and gently sloping terrain. We leverage an extensive landslide database ( N = 613,724), a high-resolution digital elevation model (10-m), and high-performance computing resources, to develop a new nationwide susceptibility map for the contiguous United States, Hawaii, Alaska, and Puerto Rico. We calculate four alternative linear and nonlinear thresholds of topographic slope and relief using an objective split-sample calibration. We down-sample our results to a 90-m grid to account for uncertainty in the digital elevation model and landslide position, and evaluate these thresholds' ability to differentiate areas of greater susceptibility. The less conservative nonlinear model optimally balances our priorities of capturing observed landslides (99%) while minimizing area covered by susceptible terrain (43%). Independent evaluation with four statewide landslide inventories ( N = 172,367) reinforces our model selection but highlights spatially variable performance. Therefore, we propose a novel approach to susceptibility classification using the concentration of landslide-prone terrain within each down-sampled grid. While landslides are possible within any cells containing susceptible terrain, those with the highest concentration capture the majority of observed landslides. Our new map characterizes landside susceptibility more consistently than prior models; our transparent classification approach also provides flexibility for accommodating different tolerances in risk reduction measures.

AGU Advances↗
USGS2026

Regional variations in sea ice and primary productivity in the Bering Sea during Marine Isotope Stage 11

Marine Isotope Stage (MIS) 11 (424-374 ka) has long been an analog for Holocene climate, because it is the most recent interglacial period with similar orbital conditions. However, there is significant global and regional variability in the climate response to MIS 11 warmth. Here, we review sediment core records from across the Bering Sea to investigate changes in paleoceanographic conditions during Marine Isotope Stages 12-10. Sea ice was present over much of the Bering Sea during MIS 11, but today, none of the sites investigated are ever ice-covered. This suggests that sea ice regimes in the Bering Sea during MIS 11 were different to those of the Holocene. There are also regional differences in the response of sea ice to MIS 11 warming. At the Umnak Plateau, Southeastern Bering Sea, sea ice concentrations decline during deglaciation, but they remain high at the slope sites until Peak MIS 11. Sea ice re-advances over the Umnak Plateau during peak interglacial warmth, at the same time that it declines over the slope sites. Late MIS 11 is characterized by high concentrations of seasonal sea ice at the Umnak Plateau, whilst sea ice at the slope sites fluctuates between consolidated and unconsolidated ice cover. This east-west dichotomy may be explained by changes in the behavior of the Aleutian Low. Productivity increases dramatically during deglaciation due to increased upwelling and sea level rise bringing fresh nutrients into the oceans. This is characterized by increased diatom productivity, increased terrestrial carbon deposition, and laminations at all sites.

Alaska↗