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519 records · Page 15Linked to original sources
USGS2026

Rapid earthquake magnitude classification via P-wave strains from borehole strainmeters and Distributed Acoustic Sensing

Distributed Acoustic Sensing (DAS) offers a promising approach for earthquake early warning (EEW) in settings where seismic networks are costly to maintain. By repurposing fiber-optic cables as dense strainmeter arrays, DAS enables real-time earthquake detection wherever those fibers are accessible. However, poor azimuthal coverage and challenges in estimating magnitude from strain measurements remain key hurdles in applying for earthquake monitoring. Here, we develop a machine learning method to distinguish large (M≥5.4) earthquakes from smaller ones within the first 4 seconds of a strain waveform after a P-wave arrival without determining location. Using ensemble decision tree models trained on borehole strainmeter data (3.5≤M≤7.1) and tested on onshore DAS waveforms (including the 2024 M7 Offshore Cape Mendocino earthquake), we find that low-frequency (0.2–0.5 Hz) continuous wavelet transform coefficients are the strongest predictors of magnitude, in addition to strain amplitude. Both DAS and borehole strainmeters effectively capture long-period strain signals, making these findings valuable for EEW systems. Our method shows high precision compared to the real-time EEW system, ShakeAlert®, supporting the position that DAS is a viable technology for earthquake monitoring and magnitude classification.

California↗
USGS2025

Did they feel it? Legacy maroseismic data illuminates an engimatic 20th century earthquake

The challenges and the importance of preserving legacy instrumental records of earthquakes are now well-recognized (e.g., Richards & Hellweg, 2020, https://doi.org/10.1785/0220200053 ). Seismologists may not be aware of parallel challenges and opportunities with legacy macroseismic data for earthquakes in the United States. For much of the 20th century, macroseismic data were collected by a series of U.S. government agencies using a standard questionnaire distributed on postcards. Published summaries of postcards provide macroseismic data akin to modern Did You Feel It? questionnaire responses. In this paper we focus on the M 6.5 Fickle Hill, California earthquake, on 21 December 1954 (Hellweg et al., 2025) as a proof-of-concept, illustrating the potential of what we dub Did They Feel It? (DTFI) data to improve our understanding of significant 20th century U.S. earthquakes for which instrumental data are sparse. Legacy macroseismic data interpreted following modern conventions can potentially constrain traditional ShakeMaps at a level of detail and accuracy that in some respects rival maps for modern earthquakes. The updated ShakeMap for the 1954 Fickle Hill earthquake, also drawing from recently published media and first-person accounts, supports the location, depth, and stress drop value estimated from available instrumental data (Hellweg et al., 2025).

California↗
USGS2025

Metal-rich lacustrine sediments from legacy mining perpetuate copper exposure to aquatic-riparian food webs

Historic copper mining left a legacy of metal-rich tailings resulting in ecological impacts along and within Torch Lake, an area of concern in the Keweenaw Peninsula, Michigan, USA. Given the toxicity of copper to invertebrates, this study assessed the influence of this legacy on present day nearshore aquatic and terrestrial ecosystems. We measured the metal (Co, Cu, Ni, Zn, Cd) and metalloid (As) concentrations in sediment, pore water, surface water, larval and adult insects, and two riparian spider taxa collected from Torch Lake and a nearby reference lake. Overall, elevated metal and metalloid concentrations, particularly Cu, were measured in all sediment samples and some surface and pore water samples collected from Torch Lake. For instance, Cu concentrations in the Torch Lake sediment were ∼200% higher than the reference lake and all measured concentrations exceeded predicted effects concentrations by at least ninefold. Within larval insect tissues, we observed 160% higher Cu concentrations than measured in the reference lake, and Cu was the only measured element above predicted effects concentrations in Torch Lake. Adult insects collected at both lakes had similar metal concentrations irrespective of exposure levels. Yet we found 100% higher copper concentrations in Torch Lake riparian spiders, demonstrating elevated exposure risk to insectivores across the aquatic-terrestrial boundary. Our results highlight that other metals in the mixture may not be as concerning to adjacent riparian ecosystems, but copper remains a contaminant of concern in Torch Lake 60 years after mining ceased.

Michigan↗
USGS2024

Complex hydrology and variability of nitrogen sources in a karst watershed

Streams draining karst areas with rapid groundwater transit times may respond relatively quickly to nitrogen reduction strategies, but the complex hydrologic network of interconnected sinkholes and springs is challenging for determining the placement and effectiveness of management practices. This study aims to inform nitrogen reduction strategies in a representative agricultural karst setting of the Chesapeake Bay watershed (Fishing Creek watershed, Pennsylvania) with known elevated nitrate contamination and a previous documented groundwater residence time of less than a decade. During baseflow conditions, streamflow did not increase with drainage area. Headwaters and the main stem lost substantial flow to sinkholes until eventually discharging along large springs downstream. Seasonal hydrologic conditions shift the flow and nitrogen load spatially among losing and gaining stream sections. A compilation of nitrogen source inputs with the geochemistry and the pattern of enrichment of δ 15 N and δ 18 O suggest that the nitrogen in streams and springs during baseflow represents a mixture of manure, fertilizer, and wastewater sources with low potential for denitrification. The pH and calcite saturation index increased along generalized flow paths from headwaters to springs and indicate shorter groundwater residence times in baseflow during the spring versus summer. Given the substantial investment in management practices, fixed monitoring sites could incorporate synoptic water sampling to properly monitor long-term progress and help inform management actions in karst watersheds. Although karst watersheds have the potential to respond to nitrogen reduction strategies due to shorter groundwater residence times, high nitrogen inputs, effectiveness of conservation practices, and release of legacy nutrients within the karst cavities could confound progress of water quality goals.

Pennsylvania↗
USGS2026

A review and synthesis of post-wildfire shifts in hydrologic processes and streamflow generation mechanisms

Critical water supply watersheds in the western United States (WUS) are impacted by wildfires, with potential negative effects on water quality and quantity. Scientific understanding is currently insufficient to deliver estimates of wildfire consequences for water quantity that are regionally accurate. Regional variability in the directionality and magnitude of post-wildfire shifts in streamflow generation fuels uncertainty in estimates of wildfire effects on water supply. In this work we provide a narrative review of wildfire effects on hydrologic processes and the resulting changes in streamflow generation mechanisms with a focus on the WUS, incorporating other global regions when pertinent. A conceptual model summary of wildfire effects on streamflow generation emphasizes: (1) precipitation seasonality, (2) synchrony of precipitation and potential evapotranspiration, (3) net shifts in interception, evaporation, and transpiration relative to total annual precipitation, (4) vegetation changes, including compensatory uptake and type conversion, (5) degree of overlap in rainfall rates and infiltration, (6) fire extent and severity, (7) burn scar positioning (e.g. in headwaters or proximal to watershed outlet), (8) scale-dependent groundwater leakage, (9) near-surface water storage reduction, and (10) soil to groundwater connectivity. Ongoing gaps and challenges include separating the influences of precipitation variability, water withdrawals, and post-fire land management; compound and overlapping disturbances; and lack of pre-fire data. Notable future opportunities include: harnessing ever-improving gridded and remotely sensed precipitation and fire-effects data; linking geophysical, isotopic tracer, and geochemical signatures to diagnose hydrologic changes; leveraging physically based and data-driven model advancements; and analyzing streamflow generation recovery trajectories across diverse watersheds.

western United States↗
USGS2025

Invasion of perennial sagebrush steppe by shallow-rooted exotic cheatgrass reduces stable forms of soil carbon in a warmer but not cooler ecoregion

Soil organic carbon ('SOC') in drylands comprises nearly a third of the global SOC pool and has relatively rapid turnover and thus is a key driver of variability in the global carbon cycle. SOC is also a sensitive indicator of longer-term directional change and disturbance-responses of ecosystem C storage. Biome-scale disruption of the dryland carbon cycle by exotic annual grass invasions (mainly Bromus tectorum, 'Cheatgrass') threatens carbon storage and corresponding benefits to soil hydrology and nutrient retention. Past studies on cheatgrass impacts mainly focused on total C, and of the few that evaluated SOC, none compared the very different fractions of SOC, such as relatively unstable particulate organic carbon (POC) or relatively stable, mineral-associated organic carbon (MAOC). We measured SOC and its POC and MAOC constituents in the surface soils of sites that had sagebrush canopies but differed in whether their understories had been invaded by cheatgrass or not, in both warm and relatively colder ecoregions of the western USA. MAOC stocks were 36.1% less in the 0–10 cm depth and 46.1% less in the 10–20 cm depth in the cheatgrass-invaded stands compared to the uninvaded stands of the warmer Colorado Plateau, but not in the cooler and more carbon-rich Wyoming Basin ecoregion. In plots where cheatgrass increased SOC, it was via unstable POC. These findings indicate that cheatgrass effects on the distribution of soil carbon among POC and MAOC fractions may vary among ecoregions, and that cheatgrass can reduce forms of carbon that are otherwise considered stable and 'secure', i.e. sequestered.

Environmental Research Communications↗
USGS2026

The damability function: A probabilistic approach to regional landslide dam susceptibility analysis applied to the Oregon Coast Range, USA

Landslides can dam rivers and require rapid response to mitigate catastrophic outburst floods. Here, we present a workflow to map landslide dam formation susceptibility at a regional scale. We define a probabilistic function that combines river valley width and landslide volume to efficiently determine the likelihood of a landslide dam or “damability”. We combine damability values with landslide susceptibility to estimate landslide dam susceptibility. The valley width measurements are automated using a new elevation threshold-based algorithm. Landslide volume is represented as a statistical distribution from mapped landslides. We validate and apply our approach to the Oregon Coast Range, USA and find that 36 % of river stretches exceed a dam potential threshold; these are in river headwaters and steeper terrain, which in this case correlate with more resistant lithologies. We also estimate volumes of the potential dammed lakes and find that most rivers with high dam susceptibility are less likely to impound large lakes because they have low drainage areas. However, widespread susceptibility, and the potential impacts from exceptionally large landslides, suggest that this hazard should be considered in the Pacific Northwest. The damability function workflow can ingest new data and be applied more broadly to assess future landslide dam hazards.

Oregon↗
USGS2024

Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning

Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.

Michigan, Wisconsin↗
USGS2025

Integrating marine historical ecology into management of Alaska’s Pacific cod fishery for climate readiness

The Pacific cod ( Gadus macrocephalus ) fishery was closed in 2020 after a rapid decline in biomass caused by the marine heat waves of 2014–2019. Pacific cod are exceptionally thermally sensitive and management of this fishery is now challenged by increasingly unpredictable climate conditions. Fisheries monitoring is critical for climate readiness, but short-term monitoring data may be inadequate for recognizing and anticipating change under rapid climate changes. We propose an interdisciplinary, marine historical ecology framework that looks to long-term records (local and traditional knowledge, history, archaeology, and paleoclimatology) to capture a long range of ecological variability and provide historical context for management. In order to connect to contemporary fisheries management, this framework must be built on a common vocabulary and an understanding of the key metrics used in fisheries stock assessments. Here, we propose metrics derived from Pacific cod stock assessment and synthesize information relevant to understanding the effects of past warming periods on cod populations across the Gulf of Alaska and Bering Sea. This case study provides a framework for thinking about how to use these historical records in the context of fisheries management under rapidly changing climate conditions.

Alaska↗
USGS2026

Continental-scale prediction of hydrologic signatures and processes

Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures.

conterminous United States↗
USGS2026

Reassessing water availability in the Nile River Basin using satellite-based irrigation water use accounting

Existing estimates of irrigation areas and water use in the Nile River Basin vary widely and are based on inconsistent data and methodologies. This study leverages advances in remote sensing to provide an up-to-date and consistent basin-wide reassessment of water use in the Nile River Basin. Land cover and actual evapotranspiration data from 2013 to 2022 were used to quantify irrigated areas, irrigation water use, and the average naturalized water yield. Across the basin, 7.1 million hectares of irrigated land consume an average of 72.5 ± 2.6 billion cubic meters (BCM) of blue water annually. Egypt and Sudan together account for 92% of the irrigated area and 97% of the irrigation water use. The basin’s average naturalized yield, evaluated at Dongola station, is determined to be between 108 and 114.4 ± 3.2 BCM. Although conservative, this updated analysis indicates the basin’s average naturalized yield is 14%–20% higher than the previous naturalized yield estimate (95 BCM) and 29%–36% higher than the commonly cited observed flow of 84 BCM, which is frequently treated as the total basin-wide available water. Importantly, the study underscores that the 84 BCM represents flow at the Aswan gauging station after upstream consumptive uses, not the total water available in the basin under naturalized conditions. This distinction is critical for accurate water accounting, planning, and governance in this water-scarce basin. This study demonstrates the value of open-source remote sensing resources in data-scarce regions while emphasizing the need for region specific validation and bias correction for improved accuracy.

Nile River Basin↗
USGS2025

Cave records reveal recent origin of North America’s deepest canyon

We explore how and when Hells Canyon, North America’s deepest river gorge (~2,400 m deep), formed, addressing these fundamental questions first posed by W. Lindgren [ The Gold Belt of the Blue Mountains of Oregon (1901)]. Existing hypotheses about the canyon’s formation and timing of incision remain speculative due to a lack of direct constraints and geomorphic analysis in the canyon. Herein, we combine cosmogenic nuclide dating of cave-bound river deposits, river profile analysis, and numerical modeling to provide the first direct age constraints and systematic analysis of incision processes at work in Hells Canyon. Our study reveals a significant drainage capture triggered rapid incision at ~2.1 ± 1.0 Ma, establishing the Snake River’s modern route into the Columbia River system. The increased drainage area and subsequent increase in stream power resulted in the rapid incision of Hells Canyon and the formation of tributary knickpoints (KPs) that decrease in elevation away from the capture location. Cosmogenic dating of cave deposits indicates incision rates increased from ~0.01 to ~0.16 mm y −1 . Numerical modeling of the stream capture supports these observations, demonstrating how abrupt drainage area increase drives rapid river incision. Our findings from Hells Canyon provide a well-constrained example of how drainage capture can dramatically shape the evolution of a major river gorge.

Idaho, Oregon, Washington↗
USGS2026

Baseflow and snowmelt sustained streamflow in the Upper Colorado River Basin, 1986-2020

The Upper Colorado River Basin (UCRB) faces substantial water availability limitations. Although most streamflow originates as snowmelt, the partitioning of snowmelt between surface runoff and groundwater recharge and subsequent groundwater discharge to streams is highly uncertain. On average, over half of the streamflow in the UCRB is estimated to originate from groundwater discharge to streams, highlighting the importance of baseflow in sustaining surface water. However, the historical patterns of baseflow and streamflow, along with their variability over space and time and their specific sources, remain unknown at the basin scale. This study addresses those gaps by characterizing the sources and transport pathways of both baseflow and streamflow in the UCRB at a seasonal timestep from 1986 to 2020, including the lagged delivery of subsurface water to streams beyond the current season, using coupled models of baseflow and streamflow. Between 1986 and 2020, on average 63% of UCRB streamflow originated from baseflow. About half of this baseflow took longer than one season to reach streams, and outside the snowmelt season, baseflow was the dominant source of streamflow. Snowmelt was a key source of both baseflow and streamflow. Current season snowmelt contributed 33% of streamflow via runoff, and 22% of the 29% of streamflow that originated as current season baseflow via subsurface flow to streams. Over the study period, baseflow index (BFI) declined in headwaters and increased at mid-elevations. Springtime increases in BFI demonstrate the increasingly important role baseflow plays in water supply. Identifying the sources, locations, and timing of water that contributed to the UCRB outlet can inform management of water resources in the basin.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2026

Magnetic storms and geoelectric hazards

Magnetic storms induce geoelectric fields at Earth's surface that can interfere with grounded long-line systems. The September 1859 storm disrupted global telegraph operations, the March 1989 storm caused a blackout in Canada and interfered with electric-power-transmission systems in the United States, and other storms have had related impacts. The geographic and temporal dependence of geoelectric fields are functions of both geomagnetic variation and local surface impedance, which differ considerably across different geological regions. These dependencies can be mapped across the contiguous United States by combining magnetotelluric impedance tensors with ground magnetometer time series. This review illustrates such mapping for the 1989 storm and shows that power-system interference was experienced where surface impedance is high, and when and where geoelectric fields were intense. Statistical analyses indicate that storms comparable to that of March 1989 occur roughly once every four solar cycles. Ongoing developments in numerical modeling and real-time monitoring are anticipated to enable prediction of geoelectric hazards. ▪ Magnetic storms can induced electric fields in the solid Earth that interfere with electric-power-transmission systems. ▪ Geoelectric hazards depend on the storm-time geomagnetic disturbance and the electrical conductivity structure of Earth. ▪ Historically, impacts on telecommunication and power-transmission systems in the United States have been concentrated in the East and Midwest. ▪ The future occurrence of a magnetic superstorm could cause widespread disruption of electric-power-transmission systems.

Annual Review of Earth and Planetary Sciences↗
USGS2026

Uranium—Deposits, production and resources, market dynamics, and supply chain risks

Introduction Interest in nuclear power for the generation of electricity has risen with the increase in the need for more diverse baseload power, enhanced energy security, and the development of new technologies, such as small modular reactors (SMRs), which could provide power for remote areas, industrial applications, and artificial intelligence (AI) data centers. In 2024, the U.S. Department of Energy received $2.7 billion in congressional funding to bolster the domestic uranium production and nuclear fuel supply chain and address reliance on imports from foreign suppliers. In 2025, the U.S. Government issued several Executive and Secretary’s orders aimed at revitalizing the U.S. nuclear sector. If SMRs are to be as widely deployed in the United States and worldwide as envisioned, demand for uranium (nuclear reactor fuel) will likely increase. After the Fukushima nuclear accident in 2011, the market spot price of uranium began a decline, followed by a decrease in U.S. and global uranium exploration and mine development expenditures that led to a uranium supply deficit until 2020, when prices started to recover, prompting a resurgence in uranium exploration and development. In January of 2024, the uranium spot price rose to a 17-year high $106 (U.S. dollars) per pound of U3O8 (triuranium oxide, commonly known as “yellowcake”), which is expected to increase uranium exploration, mine development, and uranium production domestically and worldwide.

Fact Sheet↗
USGS2025

Lithium from magma to mine in an early Yellowstone hotspot caldera

Renewable energy technologies rely on the extraction of metals not historically in high demand, such as lithium (Li), for which ore deposit models are incompletely understood. One of the world’s largest Li deposits is hosted in lake sediments of the 16.4 Ma McDermitt caldera, which formed during the early stages of Yellowstone hotspot volcanism in the western United States. Eruptive and posteruptive mobility of Li are major challenges in elucidating deposit formation. Melt inclusions preserved in quartz crystals provide a means to assess pre-eruptive magmatic Li contents. Concentrations of Li determined by ion microprobe for melt inclusions in a McDermitt rhyolite lava are 400−1350 ppm, compared to 20−70 ppm Li in matrix rhyolite glasses. Synthesis with melt inclusion data for eight additional calderas demonstrates a recurrence of Li-rich rhyolitic magmas (200−2000 ppm Li) in the western part of the Yellowstone hotspot track. However, unlike the multicyclic caldera complexes with overlapping fault networks that may have compromised Li retention, the McDermitt caldera remained a closed hydrologic system throughout its evolution. Modeling indicates 100 km 3 of resurgent magma could yield 25−150 Mt Li in a magmatic fluid and supports accumulation of Li-rich magmatic fluid in a closed intracaldera lake, followed by evaporative concentration and sequestration of Li within clay minerals to generate the McDermitt deposit.

Idaho, Nevada, Oregon, Wyoming↗
USGS2025

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↗
USGS2024

Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico

Hurricane Maria induced about 70 000 landslides throughout Puerto Rico, USA, including thousands each in three municipalities situated in Puerto Rico's rugged Cordillera Central range. By combining a nonlinear soil-depth model, presumed wettest-case pore pressures, and quasi-three-dimensional (3D) slope-stability analysis, we developed a landslide susceptibility map that has very good performance and continuous susceptibility zones having smooth, buffered boundaries. Our landslide susceptibility map enables assessment of potential ground-failure locations and their use as landslide sources in a companion assessment of inundation and debris-flow runout. The quasi-3D factor of safety, F 3 , showed strong inverse correlation to landslide density (high density at low F 3 ). Area under the curve (AUC) of true positive rate (TPR) versus false positive rate (FPR) indicated success of F 3 in identifying head-scarp points (AUC = 0.84) and source-area polygons (0.85 ≤ AUC ≤ 0.88). The susceptibility zones enclose specific percentages of observed landslides. Thus, zone boundaries use successive F 3 levels for increasing TPR of landslide head-scarp points, with zones bounded by F 3 at TPR = 0.75, very high; F 3 at TPR = 0.90, high; and the remainder moderate to low. The very high susceptibility zone, with 118 landslides km −2 , covered 23 % of the three municipalities. The high zone (51 landslides km −2 ) covered another 10 %.

Puerto Rice↗