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Estimating earthquake source depth using teleseismic broadband waveform modeling at the USGS National Earthquake Information Center

The U.S. Geologic Survey National Earthquake Information Center (NEIC) monitors global seismicity, producing a catalog of earthquake source parameters in near-real-time to provide information that can help mitigate the societal impact of earthquakes. The NEIC commonly relies on teleseismic observations to constrain earthquake source parameters (e.g., location, depth, magnitude, and mechanism) due to a lack of local and regional observations. For these ‘teleseismic’ events, depth phase (i.e., pP , sP ) arrival time observations provide the best estimate on source depth. However, depth phases are often difficult to accurately identify and/or pick. Therefore, NEIC relies on waveform modeling, such as those determined from W-phase ( M ww ), body wave ( M wb ), and regional ( M wr ) moment tensor estimations, to provide constraints on source depth. While depth estimates from these approaches are informative, higher frequency observations provide more precise estimates because depth phases are more prominently observed at higher frequencies. Here, we present NEIC’s relatively high-frequency (~0.04 to 1 Hz) teleseismic waveform modeling approach, termed Synthetic Depth Phase Modeling (SynDepth), for determining source depth. SynDepth was developed to provide NEIC with a tool that enables rapid, accurate, and quantifiable estimates of earthquake source depth in cases where locator depths are not reliable. This relatively simple and fast procedure searches over 1 km-incremented source depths and an expanding triangular source-time function to find the best-fitting solution. We compare automatic SynDepth solutions for a dataset of 1,216 earthquakes (M5.5-M7.6) between 2017 and 2021 to NEIC-derived depth estimates from other methods. Our approach provides a robust depth estimate for earthquakes lacking local arrival time data, and it minimizes the need for analyst review of depth-phase picks ( pP , sP ) or using predefined ‘fixed’ depths.

Seismological Research Letters

World minerals outlook—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029

Given the rapid expansion in the demand for mineral commodities that underpin worldwide economic growth and technological advancement, information regarding expected country-level mine production and production capacity is becoming increasingly important to industry stakeholders, end users, and policymakers. Production capacity can limit future supply, depending on how rapidly that capacity is able to expand. Current capacity can be evaluated on the basis of past production. Decreases to future capacity can be taken into account from announcements of planned shutdowns of mines or processing facilities, which are frequently publicized well in advance of such closures. Likewise, capacity expansions, which usually involve multiple stages—such as permitting, financing, and construction (all of which take time)—can also be estimated. As such, it is possible to evaluate midterm future capacity based on estimates of today’s capacities along with consideration of future investment plans. This World Minerals Outlook provides estimated capacities for cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium for 2025 through 2029. The results of this analysis indicate that two mineral commodities important to the manufacture of lithium-ion batteries—cobalt and lithium—are expected to have large capacity growth in the next few years, likely owing to expectations for increased demand for these batteries. For gallium, helium, palladium, and platinum, capacity is expected to remain stable or exhibit moderate growth. Still, these expected capacity levels are higher than current production, allowing for future production growth. The production capacity outlook is opaque for magnesium and titanium metal, which have a significant fraction of current production in nonmarket economies, such as China and Russia. Ultimately, though, where free market conditions prevail, full utilization of capacity potential for those commodities is likely to depend on supply deficits and prices that are above production costs.

Scientific Investigations Report

Joint pilot fish habitat framework

This story map will take you through the process of exploring and testing methods necessary for a higher resolution, seamless fish habitat assessment across both inland and estuarine waters through the lens of our joint pilot assessment Fish habitat assessments attempt to relate past, current, or future landscape conditions to the state of fish species occurrence, distribution, abundance, or community and habitat condition in streams, rivers, or estuaries. Previous fish habitat assessments, such as the National Fish Habitat Assessment, conducted separate and disconnected assessments for inland waters and estuaries. In this project, National Oceanic and Atmospheric Administration ( NOAA ) and U.S. Geological Survey ( USGS ) researchers created a seamless spatial framework to allow assessments that integrate influences on fish habitat from headwaters to the estuary. This effort began when the Chesapeake Bay Program Fish Habitat Action Team expressed interest in a Baywide fish habitat assessment spanning tidal salt, tidal fresh, warm non-tidal, and cold non-tidal waters. However, the complexity of the myriad of implementation details to consider when developing such an assessment necessitated the need for a tributary-specific pilot assessment. To conduct this pilot assessment, a NOAA/USGS joint partnership was formed with cooperation and support from the Chesapeake Bay Agreement and Chesapeake Bay Fish Habitat Action Team (FHAT).

Maryland

Elastic stress coupling between supraglacial lakes

Supraglacial lakes have been observed to drain within hours of each other, leading to the hypothesis that stress transmission following one drainage may be sufficient to induce hydro-fracture-driven drainages of other nearby lakes. However, available observations characterizing drainage-induced stress perturbations have been insufficient to evaluate this hypothesis. Here, we use ice-sheet surface-displacement observations from a dense global positioning system array deployed in the Greenland Ice Sheet ablation zone to investigate elastic stress transmission between three neighboring supraglacial lake basins. We find that drainage of a central lake can place neighboring basins in either tensional or compressional stress relative to their hydro-fracture scarp orientations, either promoting or inhibiting hydro-fracture initiation beneath those lakes. For two lakes located within our array that drain close in time, we identify tensional surface stresses caused by ice-sheet uplift due to basal-cavity opening as the physical explanation for these lakes' temporally clustered hydro-fracture-driven drainages and frequent triggering behavior. However, lake-drainage-induced stresses in the up-flowline direction remain low beyond the margins of the drained lakes. This short stress-coupling length scale is consistent with idealized lake-drainage scenarios for a range of lake volumes and ice-sheet thicknesses. Thus, on elastic timescales, our observations and idealized-model results support a stress-transmission hypothesis for inducing hydro-fracture-driven drainage of lakes located within the region of basal cavity opening produced by the initial drainage, but refute this hypothesis for distal lakes.

JGR Earth Surface

Stratigraphic notes—Volume 1, 2022

This is the first volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 . This first volume ("Stratigraphic notes—Volume 1, 2022") includes articles that provide guidance for those who wish to submit papers to “Stratigraphic Notes,” as well as information on how to make your manuscripts compliant for geologic names reviews and how to organize your paper’s content to facilitate inclusion of new or revised names in Geolex. This volume also includes some specific guidance on conducting geologic names reviews of geologic and hydrogeologic reports.

Professional Paper

Groundwater surveillance of swine pathogens from private wells supplying swine farms in Iowa

Biosecurity practices are essential for maintaining pig health and productivity. Despite these measures, pathogen spread still occurs. Water is one of the largest daily inputs on swine farms by volume and is not routinely tested or disinfected before it is consumed by the animals [1-3], making it a poorly understood biosecurity risk. Groundwater from privately-owned wells is a common water source for swine farms. Pathogens in the landscape, such as bacteria, viruses, and protozoa, can reach groundwater more rapidly through soil macropores, maintaining viability and facilitating transmission of pathogens into aquifers [3-13].

Iowa

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

Perspectives on transportable array Alaska background noise levels

Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.

Book chapter

State shifts in the deep Critical Zone drive landscape evolution in volcanic terrains

Understanding the near-surface environment where atmospheric and solid earth processes interact, often termed the “Critical Zone,” is important for assessing resources and building resilient societies. Here, we examine a volcanic landscape in the Oregon Cascade Range, an understudied Critical Zone setting that is host to major regional water resources, pervasive silicate weathering, and significant geohazards. We leverage a bedrock age chronosequence to show that the volcanic Critical Zone undergoes a structural shift, from depth extents of >1 km to meters, over timescales of ~1 My. We map an active groundwater volume comparable to major continental lakes, stored at the Cascade Range crest. This state shift makes volcanic landscape evolution a unique probe of deep coupling between Earth systems.

PNAS

A Lake Charr pangenome reveals highly conserved Ohnologs as drivers of phenotypic diversity

Whole-genome duplication (WGD) is hypothesized to spur evolutionary diversification by producing genome-wide duplicate gene sets (Ohnologs) that are initially functionally redundant but can diverge markedly as the effects of relaxed selection accumulate over time. However, the underlying mechanisms remain unclear, in part because genomic studies often reconstruct Ohnolog evolution over millions of years, during which subsequent mutations can obscure deep-time signals. Investigating the relationship between Ohnolog evolution and diversification on a contemporary timescale offers clearer insights. We explore this relationship in Lake Charr ( Salvelinus namaycush ), where ∼10% of genes are retained highly conserved polyploid duplicates following the Salmonid-Specific Fourth Round WGD. Using 31 chromosome-level assemblies of Lake Charr from morphologically and ecologically diverse populations, joined into a pangenome graph, we characterized 189,555 structural variants (SVs) that were significantly less likely to affect genes retained as sequence-conserved Ohnolog pairs, nuancing the hypothesis that gene redundancy, relaxed selection, and functional diversification are intertwined. However, we found that SVs affecting such conserved Ohnologs may be potent drivers of adaptive evolution. Notably, we identified a putative 938-Kb interchromosomal translocation containing 25 genes with highly conserved Ohnologs in a paralogous (but untranslocated) genomic block. This putative translocation appears to have facilitated Ohnolog divergence in ankrd11 and hp , genes putatively linked to craniofacial and lipid metabolic diversity in sympatric Lake Superior morphs. This research reveals that conserved Ohnologs previously presumed to be redundant remain a reservoir for adaptive change.

BioRxiv

GRAPES: Earthquake early warning by passing seismic vectors through the grapevine

Estimating an earthquake's magnitude and location may not be necessary to predict shaking in real time; instead, wavefield-based approaches predict shaking with few assumptions about the seismic source. Here, we introduce GRAph Prediction of Earthquake Shaking (GRAPES), a deep learning model trained to characterize and propagate earthquake shaking across a seismic network. We show that GRAPES’ internal activations, which we call “seismic vectors”, correspond to the arrival of distinct seismic phases. GRAPES builds upon recent deep learning models applied to earthquake early warning by allowing for continuous ground motion prediction with seismic networks of all sizes. While trained on earthquakes recorded in Japan, we show that GRAPES, without modification, outperforms the ShakeAlert earthquake early warning system on the 2019 M7.1 Ridgecrest, CA earthquake.

Shimane/HiroshimaPrefectures

A generalized deep learning model to detect and classify volcano seismicity

Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] ( 10.1029/2024JB029194 ) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network ( VOISS-Net ) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.

Volcanica

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

Extreme plate boundary localization promotes shallow earthquake slip at the Japan Trench

The 2011 Mw9.1 Tohoku-oki earthquake is exceptional among great earthquakes for having peak slip of ~50-70 m on the shallowest portion of the plate boundary megathrust. International Ocean Discovery Program Expedition 405 drilled multiple holes through the megathrust in the large slip region and at a Pacific Plate input site. The megathrust preferentially develops at the top or base of the pelagic clay in the input section where pronounced contrasts in physical properties are present. This results in a narrow, weak fault located at a major mechanical contact between frontal prism mud and subducted clay. Localization imposed by the input section enhances the tendency for shallow seismic slip, showing the Japan Trench may be more susceptible to ruptures with large shallow slip than margins without weak clays.

Japan Trench

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

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

Michigan

Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center ( https://doi.org/10.18739/A2RN3092P , Talucci et al., 2024).

Arctic

Fossil diatoms in Arctic marine surface sediments

Diatoms are one of the main constituents of marine phytoplankton in the Arctic, and thanks to their siliceous skeletons, diatom fossils are relatively well preserved in sediments. Due to their species-specific sensitivity to different ocean conditions, their abundance and assemblages in sediments are routinely used by paleoceanographers to reconstruct the state of the surface ocean in the past (Koç 2007). By using statistical methods, we can obtain valuable knowledge about their ecological preferences (Oksman et al. 2019) and generate quantitative reconstructions of various parameters, such as sea-surface temperature and sea-ice concentration through time (Krawczyk et al. 2021; Sha et al. 2014). The Marine Arctic Diatoms (MARDI) working group (WG) ( pastglobalchanges.org/mardi ) aims to advance knowledge on marine-diatom ecology and diatom-based reconstructions by compiling and harmonizing data from surface-sediment samples across the Arctic.

Pages Magazine

Measuring stress In high pressure deformation experiments with high speed fiber-optics

High‐pressure, high‐temperature rock deformation experiments are essential for understanding deep Earth processes, but accurately measuring stress is challenging due to the inaccuracy introduced by seal friction within the apparatus and large inertia, which affects earthquake process measurements made far from the experimental fault. To overcome these limitations, we developed and implemented a simple, compact fiber‐optic sensor based on an External Cavity Fabry–Perot Interferometer for in situ load measurement on a piston inside the pressure vessel of a Griggs‐type high‐pressure apparatus. The sensor can be used at sample temperatures up to 800°C for both slow creep and fast rupture testing with bandwidth capability from DC to 6 MHz. Two important experimental results are described: (1) the first direct measurements of seal friction in this apparatus type; these measurements record seal friction approximately one‐tenth of the confining pressure under both low (150 MPa) and high (1 GPa) pressure conditions; and (2) high‐temporal resolution capture of dynamic stress drops during stick‐slip faulting events at high‐confining pressure, revealing near‐fault wave propagation details, high‐frequency oscillations, and implying high‐transient slip rates (6–12 m/s) previously inaccessible with external sensors.

The Seismic Record