Using monitoring and partnerships to provide management-relevant information about Chesapeake Bay rivers
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Chesapeake Bay watershed↗
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Results for “Reviews in Fish Biology and Fisheries”
Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.
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Long-Term Oceanographic Observations in Western Massachusetts Bay Offshore of Boston, Massachusetts: Data Report for 1989-2000
No abstract available.
Data Series↗
Reconciling bias in moderate magnitude earthquake ground motions predicted by numerical simulations
Recent studies found a significant underprediction in ground motion intensity measures for finite-fault simulations of moderate magnitude events in southern California relative to established ground motion models. This study aims to understand the source(s) of this bias by evaluating ground motion residuals. For this, simulations have been performed for a total of 27 well-recorded earthquakes in southern California. Systematic efforts have been employed to identify the source(s) of bias by ruling out factors that are insignificant. Preliminary findings indicate that the magnitude-area scaling used in the simulations is the likely major cause of the observed bias. Adjustment in the source attributes on event-by-event basis is underway to study if the observed bias can be reconciled.
Conference Paper↗
Quantitative risk of earthquake disruption to global copper and rhenium supply
Earthquakes have the potential to substantially affect mining operations, potentially leading to supply chain disruptions and adversely affecting the global economy. This study explores the quantification of earthquake risk to copper and rhenium commodity supply by examining the spatial concentration of high earthquake hazard areas and the commodity-specific mining, smelting, and refining operations across the globe. Because many of the largest facilities are concentrated geographically near the highly seismic regions of South America, East Asia, and the Pacific, there is a potential for cascading effects on the entire supply chain. The analysis indicates that the expected annual disruption of global production is 0.3–1.1 percent for copper mines, 1.8–4.0 percent for smelters, and 1.5–3.3 percent for refineries. Expected annual disruption of global rhenium production capacity is 0.32–1.32 percent. The research highlights that the potential lost revenue from earthquake disruptions is from $315 million to $1.29 billion for copper mining, $1.92 billion to $4.33 billion for copper smelting, $2.06 billion to $4.52 billion for copper refining, and $337,000 to $1.40 million for rhenium production capacity.
Open-File Report↗
Extreme precipitation variability and soil texture controls on water-table response
Extreme precipitation events (EPEs), a key class of hydrometeorological extremes, are intensifying globally under climate change; however, their effects on water-table dynamics across varying soil textures remain poorly understood. To better understand the impacts of EPEs, we conducted one-dimensional modeling to evaluate water-table response time, displacement, recession time, and total recharge under EPEs of 0.20 m, 0.40 m, and 0.60 m amounts, applied over 1-, 7-, and 20-day durations across twelve soil textures. The results show that coarse soils (i.e., sand) respond within days, while fine soils (i.e., clay) may take over 200 days. Water-table displacement ranged from 0.30 to 1.64 m and increased with EPE magnitude. The time it took for water tables to recede ranged from 1.2 to 3.0 years. A first-order estimate of total possible recharge, calculated from porosity and displacement, ranged from 17% (clay) to 97% (sand), averaging ~63% across soil textures. These findings highlight that recharge is primarily governed by EPE magnitude and soil properties, not event duration. This modeling effort provides new insight into how soil texture modulates groundwater response to extreme precipitation, informing future water budget and resilience assessments.
Water↗
A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping
Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.
Remote Sensing of Environment↗
Bayesian ETAS modeling for the Pacific Northwest: Uncovering effects of tectonic regimes, regional differences, and swarms on aftershock parameters
The Pacific Northwest (PNW) of North America has high seismic hazard due to numerous earthquake sources under populated areas. It hosts several tectonic regimes and subregional seismic zones that are hypothesized to have different patterns of earthquake and aftershock occurrence. It is also predisposed to earthquake swarms, which can complicate the statistical modeling of these patterns. We present the first statistical seismicity model of the PNW catalog using the epidemic‐type aftershock sequence (ETAS) framework. We develop a Bayesian inference procedure that provides a stable estimation of both ETAS parameters and their uncertainties for different sets of PNW earthquakes, even those with very sparse catalogs. The Bayesian approach allows us to investigate how parameter estimates change between the intraslab and crustal tectonic regimes, the northern and southern PNW, and when swarms are included and excluded from the catalog. We also utilize our Bayesian framework to calculate parameter estimates under different prior beliefs about PNW seismicity, as well as to propagate catalog measurement errors into ETAS parameter estimates. We discuss the implications of parameter differences across the region for aftershock forecasting for the PNW.
Pacific Northwest↗
S/P amplitude ratios with Distributed Acoustic Sensing and application to earthquake focal mechanisms
Distributed acoustic sensing (DAS), which transforms a fiber optic cable into an array of high frequency strainmeters, has the potential to help us characterize earthquakes with a dense sampling of measurements. While earthquake focal mechanisms are frequently determined using P -wave polarities and S / P amplitude ratios with inertial seismometers, the dense sampling of DAS over potentially large portions of the focal sphere can aid our solutions. Here, we consider ∼200 regional earthquakes and thousands of S / P measurements on a DAS cable colocated with a network of inertial seismometers near Arcata, California. We demonstrate the S / P ratio measurements made on DAS are similar to those made on the inertial seismometers and can be used to constrain focal mechanism solutions.
California↗
Quantitative subsurface characterization illuminates the origin of the Quaternary Mississippi River Valley alluvial aquifer
The Mississippi River Valley alluvial aquifer (MRVA) is vital to U.S. food security and global agricultural supply. However, quantitative understanding of its Quaternary origin, architecture, and hydrologic function remains incomplete. Here we develop a three-dimensional hydrostratigraphic model to characterize the deposition of clay and silt, fine-medium sands, and graveliferous sands using lithologic data from 75,000 boreholes compiled across the Lower Mississippi Valley and a geostatistical method—interval kriging. We find that cyclic glacial entrenchments, evidenced by remnants of pre-Wisconsinan postglacial sediments, alongside geodynamic activities shaped the MRVA basal configuration. Stratal weakening from faulting and salt diapirism enhanced glacial incision and thereby produced abrupt aquifer thickening. We demarcate the top of graveliferous sands as the regional marker of the Pleistocene-Holocene transition. The MRVA hydrostratigraphy reveals hydrologic function and geologic controls on groundwater storage and quality, advancing the assessment of aquifer sustainability under a changing climate, with implications for alluvial aquifers globally.
Arkansas, Illinois, Kentucky, Louisiana, Mississip↗
Quantitative evaluations of earthquake early warning performance using “Did You Feel It?” and post-alert surveys
We examine responses to the U.S. Geological Survey’s “Did You Feel It?” (DYFI) survey and its companion earthquake early warning (EEW) questionnaire to assess the performance of the U.S. ShakeAlert EEW system directly from the alert recipients’ perspectives. ShakeAlert rapidly detects earthquakes and develops alert information, but as official alert delivery partners issue these alerts, it is thus difficult to determine how many people were alerted and when. We investigate DYFI reports for six California earthquakes that had EEW alerts and substantial responses to the DYFI EEW questionnaire. Comparisons of ShakeAlert predictions to reported intensities demonstrate that magnitude estimation accuracy is not necessarily indicative of ground-motion prediction accuracy. Perceived warning time distributions indicate that estimating maximum-expected warning times using the S-wave arrival is a reasonable assumption when discussing public EEW performance. However, we also find many reports of shorter warning times, late alerts, and missed alerts than expected based on ShakeAlert publication times, suggesting alert delivery latencies are substantial and highly variable. The novelty of our analysis is that we demonstrate that the DYFI EEW survey provides useful EEW efficacy information—independent of the specific alerting pathway—that can be used to inform our choices for conveying EEW performance.
California↗
Avak Creek oil occurrence, North Slope, Alaska: Newly discovered oil seep on Native lands, near village of Utqiagvik
An unknown occurrence of oil was detected near Avak Creek on Native lands on the North Slope of Alaska. Determining the source of oil was imperative for allowing stakeholders (Federal, State, and local government agencies and the landowner, an Alaska Native corporation) to make timely and informed decisions and mount a mitigation response, if required. The regional and local geological framework of the Avak Creek site was constructed using seismic surveys, well data, and basin modeling results, to identify local petroleum systems, map structural geometry and faults, define source rock thermal maturity distributions, and infer likely oil-migration pathways. Molecular hydrocarbon fingerprints (biomarkers, diamondoids, compound-specific isotopes) of the oil were compared to those of local and regional oil seeps, exploration well tests, and produced oils. Biomarker acid distributions characterized the history and extent of petroleum biodegradation. Integrating subsurface and geochemical parameters, the oil is interpreted to be a natural seep generated locally, predominantly from the Brookian Lower Cretaceous Hue Shale/gamma-ray zone, rather than an anthropogenic source of pollution. Results highlight sophisticated analytical technologies used to characterize complex, compositionally altered hydrocarbons. Results also advance our understanding of Brookian source rock distribution, subsurface petroleum migration pathways, and Arctic Alaska petroleum systems.
Alaska↗
Arctic speleothems reveal nearly permafrost-free Northern Hemisphere in the Late Miocene
Arctic warming is happening at nearly four times the global average rate. Long-term trends of permafrost dynamics cannot be estimated directly from monitoring of present-day thaw processes, requiring paleoclimate-proxy information. Here we use cave carbonates (speleothems) from a northern Siberian cave to determine when the Northern Hemisphere was mostly permafrost-free. At present, thick continuous permafrost in this region prevents speleothem growth. In a series of partially eroded caves, speleothems grew during the late Tortonian stage (8.68 ± 0.09 Ma), a time when the geographic position of this site was already similar to today. Paleotemperatures reconstructed from speleothems show that mean annual air temperatures (MAAT) in the region were + 6.6°C to + 11.1°C, when contemporary global MAAT were ~ 4.5 °C higher than modern. Our findings provide direct evidence that warming to Tortonian-like temperatures would leave most of the Northern Hemisphere permafrost-free. This may release up to ~ 130 petagrams of carbon, enhancing further warming.
Siberia↗
Near-fault amplification and ground motion variability during the 2019 Ridgecrest, California sequence
We estimate ground-motion variability near the 2019 M 7.1 Ridgecrest earthquake sequence. Accurate seismic hazard estimation requires understanding ground-motion spatial correlations, yet many studies lack the dense station coverage needed to resolve small-scale variability. The 2019 M 7.1 Ridgecrest earthquake sequence presents a unique opportunity to examine ground motions and their spatial correlations at a range of interstation distances. The permanent seismic network was augmented with hundreds of temporary stations including several fault-crossing nodal arrays. We compute the event ( δE i ) and within-event ( δW ij ) residuals from the observed peak ground velocity and peak ground acceleration data to isolate potential sources of ground-motion variability. We then compare δW ij between station pairs that record an event to understand the semivariance of the ground motion versus interstation distance. By fitting an exponential model to the semivariances, we determine a correlation range of 25 km for the Ridgecrest region. Although the exponential model fits the broad-scale increase of semivariance with interstation distance, we also observe smaller-scale trends. We find that ground motions are less correlated for station pairs that are near or across faults that ruptured during the 2019 Ridgecrest sequence. We also find large, positive median δW ij with relative values 2–3 times larger than nearby stations for individual stations’ near-fault traces. Near-fault amplification and greater ground-motion variability can delineate fault zones and may locally increase the seismic hazard.
California↗
Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States
Historically, Myotis septentrionalis (Northern Long eared Bat) was among the most common forest-interior species in North America. Largely due to high mortality from white-nose syndrome, this species has experienced severe population declines across its range. To create an updated species distribution map representing summer occupancy probabilities from 2017 to 2022, we integrated stationary acoustic data with live-capture data from the database of the North American Bat Monitoring Program into a multi-scale, multi-method occupancy modeling framework. Our results provide data-driven predictions with quantified uncertainty for summer occupancy probabilities for Northern Long-eared Bats at 2 spatial scales across the range of the species, while also accounting for inherent observation biases (e.g., imperfect detection).
Journal of North American Bat Research↗
Probing lower-crustal fault properties with frequency-dependent tidal tremor triggering
The way seismicity responds to periodic stress perturbations offers crucial insights into the processes that can trigger an earthquake. Laboratory and theoretical analyses have shown that the period of imposed forcing and source properties affect the sensitivity to triggering, but frequency-dependent triggering of tectonic faults is poorly understood. The rate of low-frequency earthquakes (LFEs) near Parkfield, California has been found to be strongly correlated with solid earth tides. Tidal forcing acts over multiple frequencies, and the sensitivity to tidal triggering of LFEs therefore provides a unique opportunity to probe the physics of earthquake triggering and underlying fault properties. Here, we find that the response of LFEs to solid earth tides at diurnal and semi-diurnal frequencies is highly variable but spatially coherent along the San Andreas Fault. Using rate-state friction modeling, we find that the variation of the amplitude of tidal modulation is mainly affected by the spatial variation of the background effective normal stress, whereas the spatially varied tidal modulation at diurnal and semi-diurnal frequencies is mainly affected by the fault frictional property. The spatial variations of the LFE response reveal a heterogeneous lower-crustal geologic structure and complex physical faulting processes below the rupture zone of eventual great earthquakes.
California↗