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USGS2025

Modeling interconnected minerals markets with multicommodity supply curves: Examining the copper-cobalt-nickel system

Demand for many of the metals used in the energy transition is expected to grow rapidly. Many of these are by-products, often considered critical because their production responds weakly to prices and is instead tied to the economics of the host mineral. We present a model of prices and production for jointly produced commodities that accounts for interconnectivity between host and by-product markets at the mine level. We demonstrate this method using the copper–cobalt–nickel system, in which approximately 99% of cobalt is a by-product of copper or nickel mining. Our results show that the model more accurately captures the economic benefits of diversified mine outputs than previous approaches. Furthermore, changes in demand drivers for any two commodities produce non-linear effects on production and price. We challenge the prior best-practice assumption that cobalt cannot impact the copper or nickel markets. Recognizing the importance of both copper and cobalt for future electrification, we emphasize that incentivizing the copper industry to reduce cobalt supply risks could inadvertently undermine copper supply.

Nature Communications↗
USGS2025

Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration

Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.

Water Resources Research↗
USGS2026

Estimating habitat availability for Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) to inform reintroduction planning in the middle Snake River basin, USA

Anadromous fishes have been blocked from the middle Snake River basin since the construction of flood control, irrigation, and hydroelectric projects during the 19 th and 20 th centuries, culminating with the construction of Hells Canyon Dam (river kilometer [rkm] 398) in 1967. Seven large watersheds in the blocked area of the basin are under consideration for Pacific salmon reintroduction. The primary objective of this study was to identify and characterize potential reintroduction sites with high-quality rearing and spawning habitat for Chinook salmon ( Oncorhynchus tshawytscha ) and steelhead ( O. mykiss ) upstream of the Hells Canyon Complex in Idaho, Oregon, and Nevada, USA. We created and tested habitat models to predict rearing presence/absence, rearing abundance, and spawning presence/absence using channel morphology, hydrology, and stream temperature variables obtained from regional peer-reviewed datasets. Habitat models were trained with salmonid presence and abundance records collected in the lower Snake River basin (downstream of Hells Canyon Dam), where anadromous fish can currently access, from 1993 to 2011. Model performance was tested with set-aside data comprised of randomly selected reaches and independent environmental DNA data. An index model was created in the middle Snake River basin for each species by combining results from the habitat models. Modeling covariates differed by species and life stage and included different combinations of August stream temperature, summer flow, channel slope, and quadratic terms for temperature and slope. The habitat models predicted high versus low Chinook salmon and steelhead probability and abundance with 66% to 85% accuracy depending on species and life stage. The index models predicted a total of 2,887 km of Chinook salmon habitat and 2,434 km of steelhead habitat in the blocked area. The three basins in the blocked area with the greatest amount of predicted habitat were the Powder River, South Fork Payette River, and North Fork Payette River for Chinook salmon, and the Powder River, South Fork Boise River, and South Fork Payette River for steelhead. The modeling approach presented here is complementary to other planning efforts for Chinook salmon and steelhead reintroduction in the blocked area of the Snake River basin, and similar approaches may be useful for reintroduction planning in other systems.

Idaho, Nevada, Oregon, Utah, Washington, Wyoming↗
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↗
USGS2024

A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (𝑀 w ) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from 𝑀 w 3.5–4.5 earthquakes but includes three well-recorded 𝑀 w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (𝑉 S30 ) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The 𝑉 S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments.

California↗
USGS1990

Recharge rates and aquifer hydraulic characteristics for selected drainage basins in middle and east Tennessee

Quantitative information concerning aquifer hydrologic and hydraulic characteristics is needed to manage the development of ground-water resources. These characteristics are poorly defined for the bedrock aquifers in Middle and East Tennessee where demand for water is increasing. This report presents estimates of recharge rate, storage coefficient, diffusivity, and transmissivity for representative drainage basins in Middle and East Tennessee, as determined from analyses of stream-aquifer interactions. The drainage basins have been grouped according to the underlying major aquifer, then statistical descriptions applied to each group, in order to define area1 distribution of these characteristics. Aquifer recharge rates are estimated for representative low, average, and high flow years for 63 drainage basins using hydrograph analysis techniques. Net annual recharge during average flow years for all basins ranges from 4.1 to 16.8 in/yr (inches per year), with a mean value of 7.3 in. In general, recharge rates are highest for basins underlain by the Blue Ridge aquifer (mean value11.7 in/yr) and lowest for basins underlain by the Central Basin aquifer (mean value 5.6 in/yr). Mean recharge values for the Cumberland Plateau, Highland Rim, and Valley and Ridge aquifers are 6.5, 7.4, and 6.6 in/yr, respectively. Gravity drainage characterizes ground-water flow in most surficial bedrock aquifer in Tennessee. Accordingly, a gravity yield analysis, which compares concurrent water-level and streamflow hydrographs, was used to estimate aquifer storage coefficient for nine study basins. The basin estimates range from 0.002 to 0.140; however, most estimates are within a narrow range of values, from 0.01 to 0.025. Accordingly, storage coefficient is estimated to be 0.01 for all aquifers in Middle and East Tennessee, with the exception of the aquifer in the inner part of the Central Basin, for which storage coefficient is estimated to be 0.002. Estimates of aquifer hydraulic diffusivity are derived from estimates of the streamflow recession index and drainage density for 75 drainage basins; values range from 3,300 to 130,000 ft^2/d (feet squared per day). Basin-specific and site-specific estimates of transmissivity are computed from estimates of hydraulic diffusivity and specific-capacity test data, respectively. Basin-specific, or areal, estimates of transmissivity range from 22 to 1,300 ft^2/d, with a mean of 240 ft^2/d In general, areal transmissivity is highest for basins underlain by the Cumberland Plateau aquifer (mean value 480 ft^2/d) and lowest for basins underlain by the Central Basin aquifer (mean value 79 ft^2/d). Mean transmissivity values for the Highland Rim, Valley and Ridge, and Blue Ridge aquifer are 320,140, and 120 ft^2/d respectively. Site-specific estimates of transmissivity, computed from specific-capacity data from 118 test wells in Middle and East Tennessee range from 2 to 93,000 ft^2/d with a mean of 2,600 ft^2/d Mean transmissivity values for the Cumberland Plateau, Highland Rim, Central Basin, Valley and Ridge, and Blue Ridge aquifers are 2,800,1,200, 7,800, 390, and 65Oft Id, respectively.

Tennessee↗
USGS2024

Groundwater and surface-water interactions in the Lower Duwamish Waterway, Seattle, Washington

The U.S. Geological Survey (USGS), in cooperation with the Washington State Department of Ecology (Ecology), conducted a study to describe the current understanding of the regional groundwater system of the lower Duwamish River valley and groundwater and surface-water interactions in the lower Duwamish Waterway. The lower Duwamish Waterway is the final 5-mile (mi) reach of the Duwamish River before it empties into Elliott Bay in Puget Sound near Seattle, Washington. A nearshore site (hereinafter referred to as “Nearshore Site” to distinguish the particular site from general discussions of nearshore areas) along the western shoreline of the Duwamish River, about 1.5 mi upstream from the river mouth, was selected for focused groundwater data collection by USGS. Data loggers were deployed in seven groundwater wells and one stilling well in the Duwamish River to measure specific conductance, temperature, and depth at 15-minute intervals for a period of about 2 years. At the Nearshore Site during 2020–22, water levels in the shallow wells were 3–8 feet (ft) higher than water levels in the deep wells, providing evidence for a low-permeability layer between the shallow and deep aquifers in this area. The shallow wells had a pronounced seasonal variability, with high water levels in winter and low water levels in summer. Data from the deep wells showed far less seasonal variability, with slight increases in winter and a near-constant water level from spring to autumn. The deep wells had a strong hydraulic connection to the Duwamish River, as evidenced by the synchronous water-level variability during the tidal cycle, whereas the shallow wells had minimal to no tidal response. The potentiometric maps developed for the Nearshore Site and surrounding areas indicate large differences in groundwater-flow directions for the shallow and deep aquifers at low and high tides. For the shallow aquifer, flow is toward the lower Duwamish Waterway near the Nearshore Site, regardless of the tidal condition. For the deep aquifer, a potentiometric trough forms parallel to the shoreline during high tide, indicating that groundwater flow converges from the uplands to the west and the Duwamish River to the east. The geometry of the potentiometric surfaces between the nearshore-most well and the shoreline is complex and is further confounded by intermittent shoreline armoring and other buried infrastructure, which could serve as either a barrier or a conduit to flow. Groundwater and surface-water interactions in the lower Duwamish Waterway are inherently complex as a result of three overarching factors. First, water levels in the lower reaches of the Duwamish River vary daily by 11–16 ft because of tides from Puget Sound, which create large swings in the hydraulic gradient in the nearshore groundwater system. Second, the density and chemical composition of water in the Duwamish River change daily with the tides and seasonally, which constrains how river water entering the nearshore sediments interacts with discharging groundwater. Third, the nearshore subsurface and shoreline conditions are heterogenous because of extensive shoreline armoring over the past century, which governs the flow of groundwater and infiltrating river water. These unique features of groundwater and surface-water interactions in the lower Duwamish Waterway thus govern the transport of terrestrial contaminants to the lower Duwamish Waterway. Furthermore, the heterogenous aquifer properties in the lower Duwamish Waterway contribute to spatially and temporally dynamic contaminant-transport processes.

Washington↗
USGS2024

Parameter ESTimation with the Gauss–Levenberg–Marquardt algorithm: An intuitive guide

In this paper, we review the derivation of the Gauss–Levenberg–Marquardt (GLM) algorithm and its extension to ensemble parameter estimation. We explore the use of graphical methods to provide insights into how the algorithm works in practice and discuss the implications of both algorithm tuning parameters and objective function construction in performance. Some insights include understanding the control of both parameter trajectory and step size for GLM as a function of tuning parameters. Furthermore, for the iterative Ensemble Smoother (iES), we discuss the importance of noise on observations and show how iES can cope with non-unique outcomes based on objective function construction. These insights are valuable for modelers using PEST, PEST++, or similar parameter estimation tools.

Groundwater↗
USGS2024

Federal lands greenhouse gas emissions and sequestration in the United States: Estimates for 2005–22

In 2016, the Secretary of the U.S. Department of the Interior requested that the U.S. Geological Survey (USGS) produce a publicly available and annually updated database of estimated greenhouse gas emissions associated with the extraction and use of fossil fuels from Federal lands. The first report in this series included emissions estimates from 2005 to 2014 and were reported for 29 States and two offshore areas. Native American and Tribal lands were not included in that analysis. This report recalculates those previous years (2005–14) with updated data and methods and extends the estimates to 2022. Nationwide emissions from fossil fuels produced on Federal lands in 2022 were 1,081.2 million metric tons of carbon dioxide equivalent (MMT CO 2 Eq.) for CO 2 , 33.4 MMT CO 2 Eq. for methane (CH 4 ), and 4.3 MMT CO 2 Eq. for nitrous oxide (N 2 O). Compared to 2005, the 2022 totals represent decreases in emissions for all three greenhouse gases (by 17 percent for CO 2 , 37 percent for CH 4 , and 30 percent for N 2 O). Emissions from fossil fuels produced on Federal lands represent, on average, 21.8 percent of U.S. emissions for CO 2 , 6.1 percent for CH 4 , and 1.3 percent for N 2 O over the 18 years included in this estimate. The trends and relative magnitudes of the greenhouse gas emissions estimated are roughly parallel to the Federal lands fossil fuel production volumes. In 2021, Federal lands of the conterminous United States stored 70,424 MMT CO 2 Eq. in terrestrial ecosystems. Soils stored most of the terrestrial ecosystem carbon (66 percent), followed by live vegetation (25 percent), deadwood (5 percent), and litter (4 percent). Carbon sequestration on Federal lands was highly variable over time, owing primarily to interannual variability in climate and weather, and variability in land use and land cover (LULC) change and disturbances, among these are wildfires and logging. Between 2005 and 2021, Federal lands sequestered an average of 83 MMT CO 2 Eq./yr. By subtracting the cumulative effects of LULC and disturbance-related CO 2 losses to the atmosphere from the total, we estimate that ecosystems at the national level sequestered CO 2 at an annual mean rate of 17 MMT CO 2 Eq./yr in a term called the net ecosystem exchange (NEE). This annual NEE sequestration value represents about 1.4 percent of average fossil fuel emissions over the same period. The USGS estimates presented in this report represent an accounting for the emissions resulting from fossil fuel extraction on Federal lands and the end-use combustion of those fuels, as well as for the sequestration of carbon in terrestrial ecosystems on Federal lands. A combined net CO 2 emissions estimate, which is the difference between the emitted and sequestered CO 2 from both the fossil fuel and ecosystems estimates, provides context for evaluating the greenhouse gas contributions of activities on these lands. The estimates included in this report can provide context for future energy decisions, as well as a basis to track change in the future.

Scientific Investigations Report↗
USGS2026

A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries

The duration, magnitude, and frequency of heatwaves are predicted to increase in the coming decades, a combination that can reduce the survival of many fish species. Across the world, there is broad interest in identifying thermal refuge for heat-intolerant fish species and exploring opportunities to enhance or protect these areas. Because deeper groundwater maintains a relatively constant temperature, groundwater-influenced areas along streams can provide cool-water refuge for fish during periods of extreme heat. A targeted approach was developed for identifying existing cold-water zones and areas of substantial groundwater discharge in four high priority Lake Ontario tributaries. Our approach included: (1) predicting where groundwater discharge is most likely with a simple geospatial model and (2) using model predictions to select field sites for intensive high-resolution study, including ground-based mapping of groundwater features (springs, seeps, tributaries) as well as drone-based optical and thermal infrared surveys. Results from field sites were used to both verify model performance and map different types and aerial extents of thermal anomalies. Geospatial modelling successfully predicted regions of widespread groundwater upwelling, later verified and mapped by field and drone surveys. Comparison of model and field survey results further highlighted specific geospatial layers, such as soil/bedrock types and topographic wetness index, as being particularly useful for predicting groundwater influence on streams in the study area. In addition, a comparison of geospatial model results with a model of fish abundances along the studied streams showed significant positive correlations for many heat-intolerant fish species over a wide geographic area. The approach developed in this study can be applied to other watersheds to highlight areas of probable groundwater discharge and could be used by fishery and water resource managers to support cold-water fish habitat management decision-making and resource conservation.

New York↗
USGS2026

A practical decision tool for marine bird mortality assessments

Given the rise in anthropogenic, environmental, and disease events contributing to marine bird mortality, there is a critical need to improve the rigor of mortality assessments. Deficits in data collection and mortality estimation can hinder a manager’s ability to document the scale of events and assess population level impacts. Therefore, to inform decisions required during activities, such as conservation status assessments or harvest management, organizations may choose to incorporate mortality assessments into response plans. Resources, capacity, and assets to assess mortality vary across jurisdictions (federal, state, Indigenous, local, etc.), and clear guidance to support mortality assessments is often unavailable or not clearly addressed. Here, we present a decision support tool to help managers identify and evaluate survey options to assess bird mortality in a diverse array of scenarios. The objective of the decision tool is to improve data collection and availability, which will increase the ability to estimate mortality robustly, given situation-specific attributes and constraints. This decision tool is designed to guide the response when a mortality event is initially encountered and offers suggestions for assessment and reporting procedures in the absence of other guidance or to complement existing protocols. The decision tool is also meant to inform decision making for response determination and resource allocation. The tool facilitates examination of options for further assessment and monitoring, which users determine by examining questions pertaining to species prioritization, determination of mortality minimum spatial extent, and the potential magnitude of impacts on affected species. Finally, identification of appropriate survey methods that address imperfect detection when a complete census is not possible are determined by exploring location, spatial and temporal extent, and the type of species affected. Ultimately, this decision tool aims to facilitate and improve the standardization of mortality assessments, equipping managers with a practical resource to navigate the decision-making process for marine bird mortality estimation.

Ornithological Applications↗
USGS2025

Chemical and isotopic fractionation during melt inclusion formation

Melt inclusions are used to study the origin and evolution of magmas. The extent to which they represent equilibrium melt compositions, however, critically hinges on the ratio of crystal growth rate to diffusion rate in melts. If the rate of crystal growth is limited by the supply of nutrients and the dissipation of unwanted components, the trapped melt will be depleted in compatible elements and enriched in incompatible elements. Despite widespread recognition of the potential for melt inclusions to trap disequilibrium compositions, their identification remains a challenge. Here, we demonstrate how stable isotopes provide a solution to this problem. Melt inclusions in basaltic tephra from Kīlauea volcano, Hawai‘i, display Mg isotope fractionation up to 0.49‰ ( 26 Mg/ 24 Mg) relative to bulk rock. These observations indicate that kinetic processes, such as chemical diffusion, are at play, as equilibrium mineral-melt isotope fractionation at high temperatures is an order of magnitude smaller. We propose that the heavy Mg isotopic compositions of the melt inclusions were generated by the faster diffusion and thus preferential incorporation of 24 Mg by the growing olivine, leaving the slower diffusant ( 26 Mg) behind. The incompatible elements (e.g., Ca, Ti, and K) are predicted to display similarly large fractionations when boundary layer effects are significant. These findings show that stable isotopes can be a useful tool in identifying disequilibrium compositions in melt inclusions.

Geology↗
USGS2026

Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state

Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.

Louisiana↗
USGS2024

Earthquake relocations delineate discrete a fault network and deformation corridor throughout Southeast Alaska and Southwest Yukon

Deformation in southeastern Alaska and southwest Yukon is governed by the subduction and translation of the Pacific-Yakutat plates relative to the North American plate in the St. Elias region. Despite notable historical seismicity and major regional faults, studies of the region between the Fairweather and Denali faults are complicated by glacial coverage and the remote setting. In the last decade, significant improvements have been made to the density of regional broadband seismometer networks. We relocate more than 5,000 earthquakes between 2010 and 2021 in the region of southeastern Alaska and southwestern Yukon utilizing these improved seismic networks. With reductions in catalog uncertainty, particularly in depth, we quantify the thickness of the seismogenic layer in the crust throughout the region and locate seismicity on a shallow network of upper-crustal faults. Relocated earthquakes, combined with an updated focal-mechanism catalog, permit estimating and classifying motion of active faults. This includes mapping the Totschunda-Fairweather “Connector” fault, which plays an important role in explaining regional deformation, and identifying new faults like the Kathleen Lake fault. We draw similarities between our seismic observations and simplified conceptual models of regional tectonics, which describe a dominant transpressional regime and localized slip partitioning. Our results support a hypothesis where current deformation is taking place on a well-defined and evolved network of shallow faults in the corridor between the Totschunda-Fairweather “Connector” and Denali faults.

Alaska, Yukon↗
USGS2025

Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows

In 2020, a wildfire burned across Glenwood Canyon in Colorado, USA. A history of postfire debris flows in the region and a hazard assessment for the burn area indicated that potentially life-threatening debris flows could be triggered by rainfall within months of a wildfire. As a result, four government agencies evaluated strategies to help mitigate hazards, including the loss of human life, that may be associated with debris-flow events. After the fire, 26 large debris flows occurred in the summer of 2021 and three sediment-laden flows occurred in the summer of 2023, but there were no major injuries or fatalities reported. We found that integrating hazard assessment/ forecasting, monitoring, and adaptation scenarios was a successful strategy for reducing postfire debris-flow risks to human life (including injuries and fatalities). Weather forecasts and estimates of debris-flow triggering rainfall thresholds, likelihood, and volume were used to anticipate the timing, location, and magnitude of debris-flow events. Rainfall monitoring and detailed recordkeeping of storms that triggered debris flows were used to validate and update debris-flow warning thresholds that varied with time following the wildfire. Although the governmental agencies working in this burn area had distinct and differing agency mandates, they were able to integrate information to reduce the risk of debris-flow events to human life.

Colorado↗
USGS1989

Techniques for simulating flood hydrographs and estimating flood volumes for ungaged basins in east and west Tennessee

A dimensionless hydrograph developed for a variety of basin conditions in Georgia was tested for its applicability to streams in East and West Tennessee by comparing it to a similar dimensionless hydrograph developed for streams in East and West Tennessee. Hydrographs of observed discharge at 83 streams in East Tennessee and 38 in West Tennessee were used in the study. Statistical analyses were performed by comparing simulated (or computed) hydrographs, derived by application of the Georgia dimensionless hydrograph, and dimensionless hydrographs developed from Tennessee data, with the observed hydrographs at 50 and 75% of their peak-flow widths. Results of the tests indicate that the Georgia dimensionless hydrography is virtually the same as the one developed for streams in East Tennessee, but that it is different from the dimensionless hydrograph developed for streams in West Tennessee. Because of the extensive testing of the Georgia dimensionless hydrograph, it was determined to be applicable for East Tennessee, whereas the dimensionless hydrograph developed from data on streams in West Tennessee was determined to be applicable in West Tennessee. As part of the dimensionless hydrograph development, an average lagtime in hours for each study basin, and the volume in inches of flood runoff for each flood event were computed. By use of multiple-regression analysis, equations were developed that relate basin lagtime to drainage area size, basin length, and percent impervious area. Similarly, flood volumes were related to drainage area size, peak discharge, and basin lagtime. These equations, along with the appropriate dimensionless hydrograph, can be used to estimate a typical (average) flood hydrograph and volume for recurrence-intervals up to 100 years at any ungaged site draining less than 50 sq mi in East and West Tennessee.

Tennessee↗
USGS2025

Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA

In landscapes recently impacted by continental glaciation, landslides may occur where topographic relief has been generated by the drainage of glacial lakes and ensuing post-glacial fluvial network development into unconsolidated glacially derived sediments and exhumed bedrock. To investigate linkages among environmental variables, post-glacial landscape development, and landslides, we created a landslide inventory of nearly 10,000 landslides in five regions of the formerly glaciated low-relief state of Minnesota, USA. Multivariate logistic regression indicates the importance of slope angle, lithology, and the development of stream valleys to landslide distribution. Areas underlain by fine-grained glaciolacustrine and nearshore deposits that are incised by streams are particularly prone to shallow (<1-2 m depth) landslides. Landslides also occur in a wide range of glacial and fluvial deposits, and as rockfall in layered Paleozoic sedimentary rocks in central and southern Minnesota and Precambrian igneous and sedimentary rocks in northeastern Minnesota. Although no more than 1-2% of the studied regions are susceptible to landslides, they can pose risk to life and safety, damage infrastructure, and impact water quality. The combination of recently generated low-relief steep slopes, extensive unconsolidated sediments, and layered sedimentary bedrock make this formerly glaciated landscape more susceptible to landslides than current national-scale models indicate.

Minnesota↗
USGS2024

The new self-anchored suspension (SAS) San Francisco Bay Bridge- Its response to a small earthquake

This paper presents a summary of previously published work (Celebi 2023) related to the new Self-Anchored Suspension (SAS) bridge that went into service within the last decade as a replacement for the older truss bridge spanning between Yerba Buena Island and Oakland, California, within the San Francisco Bay Area. During the October 19, 1989 M6.9 Loma Prieta earthquake, which occurred ~100 km south of the Bay Bridge, a section of the upper deck of the truss bridge fell onto the lower deck – thus closing this important lifeline between San Francisco and Oakland. The SAS is unique, self-anchored, and suspended by a single tower that is pivotal in trafficking the cable and hanger system to support the decks. The SAS bridge is extensively instrumented by the California Geological Survey’s Strong Motion Instrumentation Program (CSMIP). There are approximately 85 channels of accelerometers in the seismic monitoring system that recorded the October 14, 2019 Mw4.6 Pleasant Hill earthquake. The data allow a complex but identifiable coupled response of the deck, tower, and cable system. Both acceleration and displacement time-history data are used to extract significant frequencies using system identification methods, including spectral analyses. Results are compared to those from finite-element-model (FEM) analyses carried out during the design and analysis process of the bridge in 2002 (Nader et al. 2002). There are differences between FEM analyses results and those from the low amplitude shaking caused by a seismic event. An apparent frequency (period) of the SAS bridge is assessed (approximately 5.2 seconds). In a plot of deck length versus period, there is an almost linear relationship with periods of other regular suspension bridges, such as the Golden Gate Bridge and the Carquinez Bridge, both in the San Francisco Bay.

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