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1,703 records · Page 23Linked to original sources
USGS2024

Static and dynamic strain in the 1886 Charleston, South Carolina, earthquake

During the 1886 Mw 7.3 Charleston, South Carolina, earthquake, three railroads emanating from the city were exposed to severe shaking. Expansion joints in segmented railroad tracks are designed to allow railroad infrastructure to withstand a few parts in 10,000 of thermoelastic strain. We show that, in 1886, transient contractions exceeding this limiting value buckled rails, and transient extensions pulled rails apart. Calculated values for dynamic strain in the meizoseismal region are in reasonable agreement with those anticipated from the relation between strain and moment magnitude proposed by Barbour et al. (2021) and exceed estimated tectonic strain released by the earthquake by an order of magnitude. Almost all of the documented disturbances of railroad lines, including evidence for shortening of the rails, can thus be ascribed to the effects of dynamic strain changes, not static strain. Little or no damage to railroads was reported outside the estimated 10 −4 dynamic strain contour. The correspondence between 10 −3 and 2×10 −4 contours of dynamic strain and Mercalli intensity 9 and 8, anticipated from the dependence of each quantity on peak ground velocity, suggests it may be possible to use railroad damage to quantitatively estimate shaking intensity. At one location, near Rantowles, ≈20 km west of Charleston, a photograph of buckled track taken one day after the earthquake has been cited as evidence for shallow dextral slip and has long focused a search for a causal fault in this region. Photogrammetric analysis reveals that the buckle was caused by transient contraction of <10 cm with no dextral offset. Our results further weaken the evidence for faulting in the swamps and forests south of the Ashley River in 1886, hitherto motivated by the photograph and limited macroseismic evidence for high‐intensity shaking.

South Carolina↗
USGS2026

Tracking baseflow supply dynamics using SWOT data from small groundwater-dominated lakes

In situ surface-water monitoring strategies are biased towards larger perennial streams and lakes and are generally not designed to track mechanisms of baseflow supply contributed by the dynamic storage of aquifers. Additionally, small (< 1 km 2 ) groundwater-influenced lakes and wetlands globally have little in situ monitoring infrastructure. We explored the utility of remotely sensed Surface Water Ocean Topography Satellite (SWOT) data, collected from 2023 onward, to characterise the seasonal and multi-year water-level trends of groundwater flow-through kettle lakes distributed across the permeable sediments of eastern Massachusetts, USA. This analysis indicated that water levels for kettle lakes with areas down to approximately 0.05 km 2 are resolvable in the study area. Our examination of 17 kettle lakes found that SWOT water-surface elevation data closely tracked groundwater levels in adjacent monitoring wells where available, including the timing of seasonal patterns (highest levels generally in late spring), although there was some variation between years and there was a substantial lag in the timing of high water levels for a lake located downgradient from a 30-m-thick vadose zone. Furthermore, SWOT-observed water-level increases in kettle lakes tracked with baseflow increases in two adjacent groundwater-dominated streams, as would be expected from increased hydraulic gradients. Unlike spectral remote sensing, SWOT data are generally not affected by cloud cover, resulting in a potential for groundwater-dominated lakes to be sentinels of dynamic storage patterns, including identification of baseflow drought lags, which are currently ill-defined hydrological processes. SWOT monitoring of groundwater-influenced surface waters shows potential for augmenting existing monitoring wells and streamgages as continuous monitors of groundwater levels and baseflow supply in permeable terrain.

Massachusetts↗
USGS2024

Geophysical identification of potential groundwater – surface water interactions in the Bonita Peak Mining District, San Juan County, Colorado

This report includes the results and interpretation of geophysical investigations to aid in the location, identification, and conceptual site model (CSM) development of the near surface groundwater and surface water hydrology of the Upper Cement Creek and California Gulch of the Animas Rivers within the Bonita Peak Mining Districts (BPMD). Mine influenced water (MIW) from numerous mine adits within the BPMD has altered the geochemistry and ecology of these ground and surface waters. Many studies of varying scales have investigated the geology, hydrogeology, geochemistry, and aqueous chemistry of these adits and impacted areas. Field investigations using non-invasive geophysical methods were conducted in the summer of 2019 to aid in identifying potential groundwater inputs to these streams and further the CSM of the near surface within and along these streams. Two field deployments were completed in August and September of 2019. In August 2019, Phase 1 was completed using multifrequency electromagnetic induction (EMI) and thermal infrared imaging (TIR) to measure the bulk electrical conductivity, magnetic susceptibility, and the temperature response at known and suspected groundwater seeps into the Upper Cement Creek and California Gulch stretches of these alpine streams. Results and interpretation from Phase 1 were used to co-locate stretches of these streams for further detailed fiber optic distributed temperature system (FODTS) monitoring of the temperature dynamics for submeter identification of potential groundwater seeps during Phase 2. Phase 2 included additional EMI measurements, FODTS measurements, and repeated some Phase 1 measurements for improved data quality. All these data were used for the combined qualitative interpretation identifying seep locations. The data from both Phase 1 and Phase 2 are available in the USGS data release at: https://www.sciencebase.gov/catalog/item/5f18a30082cef313ed84879b. These data include detailed near-surface electrical conductivity and magnetic susceptibility mapping, discrete TIR imaging, and several kilometers of FODTS data. These data were georeferenced and used to identify potential groundwater seeps into these streams. The results indicate a complex near surface geophysical and hydrogeologic regime. Seeps are classified and spatially correlated to the EMI, TIR, and geochemical sampling results. This report is a thorough compilation of the geophysical field efforts in the summer of 2019, the data processing, and interpretations of these data. These data alone should not be used for final interpretations of the complex hydrogeology within these alpine systems. Rather, these data should be combined with other known data from various investigations to further refine the CSM and guide decisions for future investigations, watershed protective measures, and other site decisions. Geographical information system (GIS) layers of these results are available to project managers for such integration and combined interpretations.

Colorado↗
USGS2025

The 3D Elevation Program—Supporting Rhode Island’s economy

Introduction High-resolution elevation data are critical to applications of landscape modeling and planning, both of which have a significant effect on Rhode Island’s economy. In these and other enterprises, program managers, while aiming to strike a balance between accuracy and cost, strive to obtain the best available elevation data to help them address a range of issues. Programs focused on climate change, environmental management, transportation design and asset management, aviation navigation and safety, riverine ecosystem management, wildlife habitat characterization and management, shellfish aquaculture, and the management and mapping of forests, parks and recreation areas, soils, wetlands, and impervious surfaces are also among the critical applications that meet the State’s management needs and depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Rhode Island↗
USGS2025

Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery

The U.S. Geological Survey and the U.S. Fish and Wildlife Service have developed a three-tiered strategy for monitoring eelgrass ( Zostera marina ) beds at Izembek Lagoon, Alaska, that targets different spatial and temporal scales. The broadest-scale monitoring (tier-1) uses satellite imagery about every 5 years to delineate the spatial extent of eelgrass beds throughout the lagoon. This report describes the most recent (mid-2020s) tier-1 eelgrass monitoring at Izembek Lagoon. The monitoring effort began by canvasing all satellite imagery collected during summer, under clear daytime skies and at low-tide, since the last tier-1 effort in 2006. Two eelgrass maps of Izembek Lagoon were generated by first creating maps of spectrally unique classes from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing those spectral classes with information about eelgrass conditions based on field data. Specifically, maps depicting various eelgrass metrics, such as percentage of cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons of the 2016 and 2020 Sentinel-2 maps showing eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined during 2006–20 were most prevalent in the central part of Izembek Lagoon. More recently, during 2016-20, areas of possible biomass decline were more prevalent in the southern part of the lagoon. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data allows conditions to be compared over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.

Alaska↗
USGS2024

Assessment of fresh groundwater discharge and saline surface-water intrusion at Operable Unit 2, North Chevalier Field Disposal Area (Site 11), Naval Air Station Pensacola, Florida, 2018–22

Site 11 is a former landfill at North Chevalier Field Disposal Area in Operable Unit 2 at Naval Air Station Pensacola, in northwest Florida. Site 11 is adjacent to Bayou Grande, a shallow, tidally influenced, saline estuary of the Pensacola Bay watershed. Federal and Florida regulators have expressed concern that contaminants detected in groundwater beneath the inland parts of Site 11 may discharge to Bayou Grande. In 2017, the Department of Defense, U.S. Navy, Naval Facilities Engineering Systems Command Southeast asked the U.S. Geological Survey to assess the occurrence of fresh groundwater discharge to Bayou Grande at Site 11 and to delineate to the extent practicable the location of groundwater discharge. Between 2018 and 2022, the U.S. Geological Survey used a multiple-lines-of-evidence approach that included a visual method and three physical methods based on the temperature difference between groundwater and surface water to assess groundwater discharge. One of the physically based methods also used the difference in specific conductance between fresh groundwater and brackish to saline surface water. Combined, the data indicate that fresh groundwater from across Site 11 discharges primarily along the shoreline of the northern and northeastern part of Site 11. The data also indicate that saline surface water from Bayou Grande intrudes tens of feet into the shallow aquifer beneath Site 11. The combined data indicate that the interface between fresh groundwater and saline surface water changes over space and time. Any new monitoring wells proposed for installation near the shoreline of Site 11 should include approaches to monitor the changes in the location of the freshwater/saltwater interface. Care would need to be taken to collect any groundwater samples at the correct season and tidal period to provide the highest probability of collecting a representative sample of Site 11 groundwater unaffected by saltwater.

Florida↗
USGS2025

Broadband stochastic simulation of earthquake ground motions with multiple strong phases with an application to the 2023 Kahramanmaraş, Turkey (Türkiye), earthquake

Stochastic ground motion simulation models are often less accurate at lower frequencies than at higher frequencies when fitting recorded data unless supplemented by a deterministic forward directivity velocity pulse model. Moreover, time-modulated stochastic models, which adjust ground motion amplitudes over time, typically use functions that fail to capture multiple strong-motion phases. The February 2023 Turkey (Türkiye) earthquake exhibited diverse recordings, including near-fault and far-field motions with pulse-like and non-pulse-like characteristics, along with single and multiple strong-motion phases. To better represent such a diverse set of recordings, this study enhances a fully non-stationary site-based stochastic model without combining it with a deterministic model. Improvements include a new band-pass filter with upper- and lower-frequency limits, which refines the representation of the low-frequency content. Moreover, a time-modulating function that can represent energy arrival in multiple strong phases is introduced. The reference model’s parameters are identified by fitting to the energy content, zero-level crossings, and cumulative counts of positive-minima and negative-maxima of a target accelerogram. This fitting procedure is modified to address the increased number of parameters. These improvements broaden the reference model’s applicability while preserving its simplicity, a key aspect appealing to engineering practitioners. The improved model’s applicability is demonstrated by simulating a dataset from the February 2023 Türkiye earthquake, and the accuracy is tested using a pulse-like Next Generation Attenuation Relationships for Western United States dataset. Validations are performed based on total energy, zero-level crossings, Fourier amplitude spectrum, elastic response spectra, and peak ground motion parameters. Validations are performed schematically in the time and frequency domains and quantitatively using goodness-of-fit scores, various validation-metrics errors, and inter-period correlations. Overall, the improved stochastic model can effectively simulate a set of diverse ground motion recordings, including near-fault pulse-like records, records with multiple strong phases, and far-field motions across a broad frequency range.

Kahramanmaraş↗
USGS2025

lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data. Here we introduce , a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. can be found at https://doi.org/10.5066/P1DZUR3Z

Applied Computing and Geosciences↗
USGS2026

Abandonment of the Upper Devonian Greenland Gap Group and Scherr Formation and revision of the Upper Devonian Brallier and Foreknobs Formations in the central Valley and Ridge Province

This study revises the lithostratigraphic framework of the Upper Devonian interval traditionally assigned to the Greenland Gap Group across the central Appalachian Valley and Ridge Province. The work aims to modernize and standardize lithostratigraphic nomenclature, establish a new reference section and demonstrate how the revised stratigraphy improves edge-matching of 1:24,000 scale geologic maps and supports compilation mapping at scales of 1:100,000 and larger. The revision eliminates the names Greenland Gap Group, Scherr Formation and the Minnehaha Springs Member of the Scherr Formation; reassigns all strata previously designated as Scherr Formation by Dennison (1970) to the upper Brallier Formation; and abandons the basal Mallow Member of the Foreknobs Formation, placing its strata within the upper Brallier as originally defined by Butts (1918). The contact between the Brallier and Foreknobs formations is placed at the base of the first mappable, ridge-forming package of fine- to coarse-grained, cross-bedded, sandstone beds, often containing rounded quartz pebbles with minor interbeds of shale and siltstone. This contact may be gradational in places but, even in absence of good exposure, can usually be distinguished topographically in recently produced lidar-derived imagery as having elevated relief due to the presence of more resistant, compositionally mature coarse-grained sandstone-rich strata. Applying this criterion for mapping the contact between the Brallier and Foreknobs formations has resulted in reconciliation of mismatches of geologic contacts along several 7.5-minute quadrangle boundaries in the states of Virginia, West Virginia, Maryland and Pennsylvania. A new reference section at Baker, West Virginia showcases the contacts between the Harrell Shale, Brallier Formation, Foreknobs Formation and Hampshire Formation. A digital outcrop model of the reference section is provided for future preservation.

Maryland, Pennsylvania, Virginia, West Virginia↗
USGS2026

Water use permits as of July 2024 and reported water use near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023

Starting in the early 2000s, increasing oil and gas development in western North Dakota created a need for additional water resources from surface-water and groundwater sources near the North Unit of Theodore Roosevelt National Park. To summarize the use of water in that area, the U.S. Geological Survey, in cooperation with the National Park Service, developed a map of surface-water and groundwater resources, aquifers, and water-use diversions, and plotted water-use trends from 1980 to 2023. Reported water used from permits in the map area has more than doubled since 2020, increasing from about 750 acre-feet in 2020 to about 2,300 acre-feet in 2022 and 2,000 acre-feet in 2023. Surface water provided the primary source of reported water used for the study period with an average of about 410 acre-feet per year from 1980 through 2017 and about 1,330 acre-feet per year from 2018 through 2023. After 2011, groundwater sourced from the Little Missouri River, Tobacco Garden Creek, Fox Hills, Fort Union, and Dakota aquifers became a larger portion of total annual reported water use from permits in the map area. From 1980 through 2015, water use for irrigation averaged 86 percent of the total annual reported surface-water and groundwater use in the map area. Starting in 2011, however, industrial uses became a proportionally larger total use of water, and in 2015, became the highest reported volume of water use in the map area. From 2011 to 2023, industrial use designated for water depots increased from 50 acre-feet to about 1,370 acre-feet, accounting for about 70 percent of total reported water use in the map area in 2023.

North Dakota↗
USGS2026

Repeated coral bleaching events have eroded reef accretion potential in the Florida Keys

Coral bleaching is now the primary driver of coral-reef degradation globally, threatening the persistence of coral-reef functions and the invaluable ecosystem services they support. The Florida Keys have been impacted by four severe, regional-scale coral-bleaching events, which occurred in 1997–1998, 2005, 2014–2015, and 2023. Our aim in this study was to quantify the effects of those thermal-stress events on the persistence of coral-reef structures. We leveraged long-term coral-reef monitoring data to quantify the impacts of coral bleaching on coral cover, carbonate production, and reef-accretion potential throughout the Florida Keys from 1996–2024. Our study indicates that coral bleaching drove significant declines of reef-building corals, which successively diminished regional-scale reef-accretion potential (from 1.65 ± 0.33 mm y -1 in 1996) and culminated with a regional-scale transition to net reef erosion (-0.12 ± 0.08 mm y -1 ) following the 2023 event. Coral bleaching was the primary driver of declining reef-building capacity, with the cumulative impacts of the four coral-bleaching events accounting for >75% of total declines since 1996. The 1997–1998 event alone drove ~50% of overall declines, largely due to losses of the shallow-water ecosystem engineer, Acropora palmata . More moderate impacts of thermal stress on regional reef-accretion potential in 2005 (6%) and 2014–2015 (9%) could lend some support to the hypothesis that the remaining corals were more thermally tolerant; however, the unprecedented thermal stress event in 2023 caused widespread coral-bleaching and bleaching-related mortality, and caused an additional 12% of the total decline in reef-accretion potential. Stony-coral tissue loss disease accounted for an additional 6% of the decline, with the remaining 19% unexplained. Coral bleaching has already dramatically reshaped the structure and function of coral reefs in the Florida Keys over the last three decades. With the high likelihood that thermal stress will accelerate moving forward, the persistence of Florida’s essential coral-reef functions and services is uncertain.

Florida↗
USGS2024

Separating signals in elevation data improves supervised machine learning predictions for hydrothermal favorability

A recent study identified topography (land surface elevation above sea level) as an important input dataset (feature) for predicting the location of hydrothermal systems in the Great Basin in Nevada. Yet, topography is generally a result of more than one geological process and may consequently contain multiple distinct signals. For example, the geologic evolution of the Great Basin has produced both crustal thickening (i.e., regional-scale trends in elevation) and thinning via Basin and Range extensional faulting (i.e., valley-scale topographic relief). We postulate that these geologic processes may affect the occurrence of hydrothermal systems differently. Therefore, we separate the regional trend from the valley-scale signal in the Great Basin, and then use them separately to evaluate the importance of each as predictors for hydrothermal favorability. Our prior work applying supervised machine learning (ML) using the data from the Nevada Machine Learning Project demonstrated that employing a training strategy that randomly selects negative training sites produces better performing models for predicting hydrothermal favorability than a training strategy that uses expert-selected negatives. The models created using both training strategies exhibited a west-east geographic trend in the predictions for the favorability of hydrothermal resources. These models generally predicted higher favorability in western Nevada and lower favorability in eastern Nevada. This west-east trend in predicted favorability correlates with elevation across the Great Basin, which trends higher from west to east. By separating the original elevation feature into distinct features for elevation trend (i.e., regional-scale topography) and detrended elevation (i.e., valley-scale or local relative topography), we find that models using the separated topographic signals consistently outperform competing models that use the original elevation feature. Although western Nevada still exhibits higher favorability than eastern Nevada, using separated signals for regional elevation and local structure reduces the west-east prediction trend in the region and emphasizes structures associated with hydrothermal upflow. This work emphasizes how carefully engineering features to represent geological conditions relevant to hydrothermal systems allows ML algorithms to detect important patterns for predicting hydrothermal resource favorability and leads to better model performance.

Conference Paper↗
USGS2024

Groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa

Des Moines Water Works (DMWW) is a regional municipal water utility that provides residential and commercial water resources to about 600,000 customers in Des Moines, Iowa, and surrounding municipalities in central Iowa. DMWW has identified a need for increased water supply and is exploring the potential for expanding groundwater production capabilities in the Des Moines River alluvial aquifer, where it operates two radial collector wells (RCWs). The U.S. Geological Survey, in cooperation with DMWW, completed a study of the Des Moines River alluvial aquifer and interactions of the RCWs with the aquifer; no previously published model has included the existing well locations, which is the focus of this model. A conceptual and numerical groundwater flow model have been developed to characterize the Des Moines River alluvial aquifer under existing conditions, to simulate water levels observed in the RCWs, and to provide publicly accessible hydrologic data and research that advance understanding of the regional hydrologic system and can potentially be used in the future to evaluate groundwater production scenarios. Model performance was assessed by comparing observed and simulated groundwater levels that included water level elevations, water level changes, water level inequality observations, surface water streamflow, and change in surface water volume from upstream to downstream. Water table elevation in the aquifer layers is on average slightly overestimated with average absolute value error less than 1.5 meters at both RCWs and less than 2.5 meters for all observation wells in the alluvial aquifer layers. The model also accurately simulated water tables greater than the RCW design minimum (a water level threshold at which RCW pumping is reduced) in all timesteps for which water level observation data existed. Water table elevation error was higher in other model layers that were not the focus of the study, and the model did not accurately match streamflow targets.

Iowa↗
USGS2024

The 2023 Alaska National Seismic Hazard Model

US Geological Survey (USGS) National Seismic Hazard Models (NSHMs) are used extensively for seismic design regulations in the United States and earthquake scenario development, as well as risk assessment and mitigation for both buildings and infrastructure. This 2023 update of the long-term, time-independent Alaska NSHM includes substantial changes to both the earthquake rupture forecast (ERF) and ground motion models (GMMs). The ERF includes numerous additions to the finite-fault model, considers two deformation models, and introduces updated declustering and smoothing algorithms in the gridded background seismicity model. For the Alaska–Aleutian subduction zone, megathrust earthquakes occur on an updated structural and segmentation model, and the moment magnitude (M) 8+ rupture and rate model include a logic tree branch that considers slip rates derived from geodetic models of interface coupling. The megathrust model considers multiple models of down-dip width, and magnitudes are computed using newly developed scaling relations. For subduction intraslab events and subduction interface events with M < 7, the 2023 update uses a smoothed seismicity model with rupture depths derived from Slab2. The 2023 model updates GMMs in all tectonic settings using the recently published Next Generation Attenuation Subduction (NGA-Sub) GMMs for subduction interface and intraslab events, and the NGA-West2 GMMs for active crustal settings. Collectively, additions and updates to the Alaska NSHM result in hazard increases across most of south-central Alaska relative to the previous model, published in 2007. These changes are primarily due to the adoption of updated rate models for the large-magnitude interface events and the NGA-Sub GMMs that have much higher aleatory variability (sigma), consistent with global observations, and that include models of epistemic uncertainty.

Alaska↗
USGS1998

Technique for simulating peak-flow hydrographs in Maryland

The efficient design and management of many bridges, culverts, embankments, and flood-protection structures may require the estimation of time-of-inundation and (or) storage of floodwater relating to such structures. These estimates can be made on the basis of information derived from the peak-flow hydrograph. Average peak-flow hydrographs corresponding to a peak discharge of specific recurrence interval can be simulated for drainage basins having drainage areas less than 500 square miles in Maryland, using a direct technique of known accuracy. The technique uses dimensionless hydrographs in conjunction with estimates of basin lagtime and instantaneous peak flow. Ordinary least-squares regression analysis was used to develop an equation for estimating basin lagtime in Maryland. Drainage area, main channel slope, forest cover, and impervious area were determined to be the significant explanatory variables necessary to estimate average basin lagtime at the 95-percent confidence interval. Qualitative variables included in the equation adequately correct for geographic bias across the State. The average standard error of prediction associated with the equation is approximated as plus or minus (+/-) 37.6 percent. Volume correction factors may be applied to the basin lagtime on the basis of a comparison between actual and estimated hydrograph volumes prior to hydrograph simulation. Three dimensionless hydrographs were developed and tested using data collected during 278 significant rainfall-runoff events at 81 stream-gaging stations distributed throughout Maryland and Delaware. The data represent a range of drainage area sizes and basin conditions. The technique was verified by applying it to the simulation of 20 peak-flow events and comparing actual and simulated hydrograph widths at 50 and 75 percent of the observed peak-flow levels. The events chosen are considered extreme in that the average recurrence interval of the selected peak flows is 130 years. The average standard errors of prediction were +/- 61 and +/- 56 percent at the 50 and 75 percent of peak-flow hydrograph widths, respectively.

Maryland↗
USGS2026

Simulation-based scenario ShakeMaps for large magnitude (MW6.5+) crustal earthquakes on the Seattle, Tacoma, and southern Whidbey Island faults, Washington, USA

Scenario ground‐motion maps based on empirical ground‐motion models (GMMs) provide a rapid and generally reliable means of estimating the amplitude and distribution of earthquake shaking. However, because GMMs are designed for broad applicability, they often rely on simplified representations of Earth structure, which can limit their accuracy in regions with complex source, path, and site effects. This can substantially impact the accuracy of predicted shaking in areas like western Washington State, where deep, interconnected basin structure exerts a strong influence on seismic‐wave propagation. In this study, we present a new suite of simulation‐based scenario ShakeMaps that characterize ground shaking from large‐magnitude ( ⁠ M W 6.5–7.5) earthquakes on the Seattle, Tacoma, and southern Whidbey Island faults. These maps are developed using results from recent 3D wave propagation simulations ( Stone et al. , 2022 , 2023 , 2025 ) that incorporate realistic rupture geometries, variable slip distributions, and a regional 3D seismic velocity model with shallow soils. Broadband ground motions are estimated by combining the low‐frequency (<1 Hz) deterministic seismograms from these studies with high‐frequency (1–10 Hz) stochastic seismograms. Simulated ground motions are corrected to account for the enforced minimum shear‐wave velocity and nonlinear site response. The resulting ShakeMaps represent median ground‐shaking estimates derived from multiple rupture scenarios with varying slip distributions and hypocenter locations for each fault. To extend ShakeMap coverage beyond the simulation domain (i.e., into eastern Washington, northern Oregon, and southwestern British Columbia), we scale GMM‐based ground‐motion estimates using amplification patterns observed in the simulations. These new ShakeMaps reveal the substantial influence of deep basin structure on shaking intensity, underscoring the importance of considering crustal structure complexity in regional hazard assessments for the Pacific Northwest.

Washington↗
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↗
USGS2026

The potential impact of three-dimensional distributed slip models derived from real-time GNSS data on the performance of the ShakeAlert earthquake early warning system for slab interface earthquakes

The ShakeAlert® earthquake early warning (EEW) system is designed to warn users of imminent strong ground motion with sufficient time to take protective actions. ShakeAlert currently uses three algorithms to characterize the earthquake source. One estimates the location and magnitude using the first few seconds of the P wave and, while fast, tends to underestimate magnitude for M w 7.0+ earthquakes. A second estimates the location, orientation, length, and corresponding magnitude of a line source using observed peak ground acceleration and contributes primarily to M w 5.5+ earthquakes. The third infers earthquake magnitude from peak ground displacement measured using Global Navigation Satellite System (GNSS) data and offers nonsaturating magnitudes for M w 7.0+ earthquakes. Other EEW algorithms exist that infer temporally evolving spatially variable slip on a 3D fault surface from real‐time GNSS data, information that might enable more accurate and timely alerts in the event of large‐magnitude subduction interface earthquakes. Here, we evaluate the potential contribution of one such algorithm, BEFORES ( Minson et al. , 2014 ), to improve ShakeAlert performance through a simulated real‐time implementation of Bayesian evidence‐based fault orientation and real‐time earthquake slip (BEFORES) and other ShakeAlert algorithms using data for eight M w 7.6+ earthquakes. The test results demonstrate that BEFORES can produce well‐constrained and accurate magnitude estimates as soon as or sooner than other EEW algorithms, in turn enabling it to increase the amount of warning time users receive in many cases. However, with a modified Mercalli intensity (MMI) threshold of 3.5, which is commonly used for issuing alerts, BEFORES would tend to alert large geographic regions that did not feel strong shaking (MMI 6+). This effect can be mitigated using a higher alert threshold of MMI 4.5 without negative impact on the amount of warning time obtainable with BEFORES.

Bulletin of the Seismological Society of America↗