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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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USGS2020

Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center

Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations. Automatic seismic arrival detections made from standard picking methods (e.g., short‐term average/long‐term average [STA/LTA]) are fed to trained neural network models to improve automatic seismic‐arrival (pick) timing and estimate seismic‐arrival phase type and source‐station distances. These additional data are used to improve the capabilities of the NEIC associator. We compile a dataset of 1.3 million seismic‐phase arrivals that represent a globally distributed set of source‐station paths covering a range of phase types, magnitudes, and source distances. We train three separate convolutional neural network models to predict arrival time onset, phase type, and distance. We validate the performance of the trained networks on a subset of our existing dataset and further extend validation by exploring the model performance when applied to NEIC automatic pick data feeds. We show that the information provided by these models can be useful in downstream event processing, specifically in seismic‐phase association, resulting in reduced false associations and improved location estimates.

Seismological Research Letters↗

USGS2005

Monitoring eruptive activity at Mount St. Helens with TIR image data

Thermal infrared (TIR) data from the MASTER airborne imaging spectrometer were acquired over Mount St. Helens in Sept and Oct, 2004, before and after the onset of recent eruptive activity. Pre‐eruption data showed no measurable increase in surface temperatures before the first phreatic eruption on Oct 1. MASTER data acquired during the initial eruptive episode on Oct 14 showed maximum temperatures of ∼330°C and TIR data acquired concurrently from a Forward Looking Infrared (FLIR) camera showed maximum temperatures ∼675°C, in narrow (∼1‐m) fractures of molten rock on a new resurgent dome. MASTER and FLIR thermal flux calculations indicated a radiative cooling rate of ∼714 J/m 2 /s over the new dome, corresponding to a radiant power of ∼24 MW. MASTER data indicated the new dome was dacitic in composition, and digital elevation data derived from LIDAR acquired concurrently with MASTER showed that the dome growth correlated with the areas of elevated temperatures. Low SO 2 concentrations in the plume combined with sub‐optimal viewing conditions prohibited quantitative measurement of plume SO 2 . The results demonstrate that airborne TIR data can provide information on the temperature of both the surface and plume and the composition of new lava during eruptive episodes. Given sufficient resources, the airborne instrumentation could be deployed rapidly to a newly‐awakening volcano and provide a means for remote volcano monitoring.

Washington↗

USGS1997

Investigation into avian mortality in the Playa Lakes region of southeastern New Mexico: Final Report - June 1997

This Final Report is a review of work on a cooperative study undertaken by the USGS Biological Resources Division's National Wildlife Health Center (NWHC) and National Wetlands Research Center (NWRC; formerly the Southern Science Center) from 1994 through 1997. The study was initiated at the request of the Bureau of Land Management (BLM), through a request to the former National Biological Service. The Southeastern New Mexico Playa Lakes Coordinating Committee (SENMPLCC) played an important role in outlining the research needs. The initial Study Plan document, which outlines the background, objectives and methods for the first two years is available as Appendix 1. A letter indicating modifications to the Study Plan was sent to the SENMPLCC chair on April 25,1995, and is Appendix 2. An Interim Report, covering this work was completed and submitted in September 1995. The Literature Review section of the study was completed and presented to SENMPLCC in August, 1995. Following SENMPLCC review, NWHC was asked to develop a series of questions that could be posed from information gained in the initial phase (Appendix 3). The NWHC and NWRC were then directed to begin work to answer the top three questions, within the available fiscal resources. NWRC could continue with work outlined under the original Study Plan (Appendix 1), however an additional Study Plan for experiments performed by NWHC and collaborators and is available as Appendix 4.

New Mexico↗

USGS2024

Geologic input databases for the 2025 Puerto Rico – U.S. Virgin Islands National Seismic Hazard Model update: Crustal faults component

The last National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI) was published in 2003. In advance of the 2025 PRVI NSHM update, we created three geologic input databases to summarize new onshore and offshore fault source information in the northern Caribbean region between 62°–70° W and 16°–21° N. These databases, of fault sections, fault‐zone polygons, and geologic estimates of fault activity (fault‐slip rate and earthquake recurrence intervals) at specific sites, document updates to fault parameters used in prior seismic hazard models in PRVI. Fault sources were reviewed from published studies since 2003, which document substantial changes to the understanding of fault location, geometry, or activity. New fault section sources were added for features that meet the criteria of (1) length ≥7 km, (2) unequivocal evidence of recurrent tectonic Quaternary activity, and (3) documentation that is publicly available in a peer‐reviewed source. In addition, we revised several broad areal sources, such as the Mona and Anegada extensional zones. The 2003 model included three fault sections and two fault‐zone polygons (areal sources). These databases include 35 fault sections, 6 fault‐zone polygons, and 51 earthquake geology sites. To characterize fault activity rates, slip‐rate bins were assigned based on landscape expression and paleoseismic trench observations for faults without published slip‐rate sites. Additional fault sources were evaluated but not included in these databases due to a lack of published information about fault location, geometry, or recurrent Quaternary activity. The PRVI NSHM 2025 geologic input databases describe crustal faulting; the geometries and coupling of Puerto Rico subduction zone and Muertos Trough models are considered in a separate database. Updates to the fault sections, fault‐zone polygons, and earthquake geology databases can help inform the location and recurrence rate of damaging earthquakes in the PRVI NSHM implementation.

Puerto Rico, U.S. Virgin Islands↗

USGS2011

88 hours: The U.S. Geological Survey National Earthquake Information Center response to the March 11, 2011 Mw 9.0 Tohoku earthquake

The M 9.0 11 March 2011 Tohoku, Japan, earthquake and associated tsunami near the east coast of the island of Honshu caused tens of thousands of deaths and potentially over one trillion dollars in damage, resulting in one of the worst natural disasters ever recorded. The U.S. Geological Survey National Earthquake Information Center (USGS NEIC), through its responsibility to respond to all significant global earthquakes as part of the National Earthquake Hazards Reduction Program, quickly produced and distributed a suite of earthquake information products to inform emergency responders, the public, the media, and the academic community of the earthquake's potential impact and to provide scientific background for the interpretation of the event's tectonic context and potential for future hazard. Here we present a timeline of the NEIC response to this devastating earthquake in the context of rapidly evolving information emanating from the global earthquake-response community. The timeline includes both internal and publicly distributed products, the relative timing of which highlights the inherent tradeoffs between the requirement to provide timely alerts and the necessity for accurate, authoritative information. The timeline also documents the iterative and evolutionary nature of the standard products produced by the NEIC and includes a behind-the-scenes look at the decisions, data, and analysis tools that drive our rapid product distribution.

Tohoku↗

USGS2019

Regional Global Navigation Satellite System networks for crustal deformation monitoring

Regional networks of Global Navigation Satellite System (GNSS) stations cover seismically and volcanically active areas throughout the United States. Data from these networks have been used to produce high‐precision, three‐component velocity fields covering broad geographic regions as well as position time series that track time‐varying crustal deformation. This information has contributed to assessing interseismic strain accumulation and related seismic hazard, revealed previously unknown occurrences of aseismic fault slip, constrained coseismic slip estimates, and enabled monitoring of volcanic unrest and postseismic deformation. In addition, real‐time GNSS data are now widely available. Such observations proved invaluable for tracking the rapidly evolving eruption of Kīlauea in 2018. Real‐time earthquake source modeling using GNSS data is being incorporated into tsunami warning systems, and a vigorous research effort is focused on quantifying the contribution that real‐time GNSS can make to improve earthquake early warnings as part of the Advanced National Seismic System ShakeAlert system. Real‐time GNSS data can also aid in the tracking of ionospheric disturbances and precipitable water vapor for weather forecasting. Although regional GNSS and seismic networks generally have been established independently, their spatial footprints often overlap, and in some cases the same institution operates both types of networks. Further integration of GNSS and seismic networks would promote joint use of the two data types to better characterize earthquake sources and ground motion as well as offer opportunities for more efficient network operations. Looking ahead, upgrading network stations to leverage new GNSS technology could enable more precise positioning and robust real‐time operations. New computational approaches such as machine learning have the potential to enable full utilization of the large amounts of data generated by continuous GNSS networks. Development of seafloor Global Positioning System‐acoustic networks would provide unique information for fundamental and applied research on subduction zone seismic hazard and, potentially, monitoring.

Seismological Research Letters↗

USGS2012

Field experiment provides ground truth for surface nuclear magnetic resonance measurement

The need for sustainable management of fresh water resources is one of the great challenges of the 21st century. Since most of the planet's liquid fresh water exists as groundwater, it is essential to develop non-invasive geophysical techniques to characterize groundwater aquifers. A field experiment was conducted in the High Plains Aquifer, central United States, to explore the mechanisms governing the non-invasive Surface NMR (SNMR) technology. We acquired both SNMR data and logging NMR data at a field site, along with lithology information from drill cuttings. This allowed us to directly compare the NMR relaxation parameter measured during logging, T 2 , to the relaxation parameter T 2 * measured using the SNMR method. The latter can be affected by inhomogeneity in the magnetic field, thus obscuring the link between the NMR relaxation parameter and the hydraulic conductivity of the geologic material. When the logging T 2 data were transformed to pseudo- T 2 * data, by accounting for inhomogeneity in the magnetic field and instrument dead time, we found good agreement with T 2 * obtained from the SNMR measurement. These results, combined with the additional information about lithology at the site, allowed us to delineate the physical mechanisms governing the SNMR measurement. Such understanding is a critical step in developing SNMR as a reliable geophysical method for the assessment of groundwater resources.

Geophysical Research Letters↗

USGS2015

Improving conservation outcomes with a new paradigm for understanding species’ fundamental and realized adaptive capacity

Worldwide, many species are responding to ongoing climate change with shifts in distribution, abundance, phenology, or behavior. Consequently, natural-resource managers face increasingly urgent conservation questions related to biodiversity loss, expansion of invasive species, and deteriorating ecosystem services. We argue that our ability to address these questions is hampered by the lack of explicit consideration of species’ adaptive capacity (AC). AC is the ability of a species or population to cope with climatic changes and is characterized by three fundamental components: phenotypic plasticity, dispersal ability, and genetic diversity. However, few studies simultaneously address all elements; often, AC is confused with sensitivity or omitted altogether from climate-change vulnerability assessments. Improved understanding, consistent definition, and comprehensive evaluations of AC are needed. Using classic ecological-niche theory as an analogy, we propose a new paradigm that considers fundamental and realized AC: the former reflects aspects inherent to species, whereas the latter denotes how extrinsic factors constrain AC to what is actually expressed or observed. Through this conceptualization, we identify ecological attributes contributing to AC, outline areas of research necessary to advance understanding of AC, and provide examples demonstrating how the inclusion of AC can better inform conservation and natural-resource management.

Conservation Letters↗

USGS2025

Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities

Spatio-temporal changes to our world’s surface water resources are escalating. Translating how these changes impact communities and ecosystems requires time-varying data of Global Surface Water Extents (GSWE). Traditionally, GSWE mapping has been limited to static estimates, with recent efforts focusing on annual averages, frequency and occurrence of long-term variations. Building upon these foundational capabilities, we harnessed remotely sensed Sentinel-2 based near real-time Dynamic World (DW) land cover products to produce the first-of-its-kind 10 m resolution GSWE dataset representing 2015–2023. Our dataset estimated 2.5 million km 2 of permanent waters and 8 million km 2 of seasonal waters worldwide. Comparing our Sentinel-2 based data to contemporary Landsat-based GSWE, we observed that our data mapped less water within the >50% probability of occurrence range, suggesting a lower presence of open permanent water especially in high latitudes, deviating from what we previously learnt from Landsat data. Statistical analysis compared to well-established observational products and widely used GSWE datasets across some of the world’s most ecologically significant regions, including Pantanal in South America and Haor in South Asia, supports the overall physical realism of our data in predicting global open surface water dynamics. Our key contribution is a prototype Open Science operational framework that extracts routinely available DW products, runs geospatial analytics, and creates actionable water information for educators, researchers, and stakeholders at any scale of practical interest. We present examples of this operational capability through instant mapping of flood in Spain and drought in Lake Urmia, Central Asia, frequent monitoring of river extent changes at the Ganges–Brahmaputra confluence, and above all, interoperability with other existing GSWE applications.

Environmental Research Letters↗

USGS2022

Ready for real time: Performance of Global Navigation Satellite System in 2019 Mw 7.1 Ridgecrest, California, rapid response products

Global Navigation Satellite Systems (GNSSs) have undergone notable advancement in the last few decades, leading to the availability of a dataset with capabilities well beyond its original intended purpose. The proliferation of high‐rate (1 Hz or greater) GNSS receivers in areas of seismological interest now allows for routine consideration of dynamic earthquake ground motions, with centimeter‐level displacement accuracy via precise point positioning methods. Real‐time (RT) GNSS observations, from stations that are both telemetered and processed to displacement with minimal latency, have lower accuracy compared to post‐processed (PP) GNSS displacements due to imprecise knowledge of atmospheric conditions, satellite clocks, and satellite orbits in RT. Whether the quality of RT high‐rate GNSS is sufficient for use in rapid response products remains to be thoroughly examined. Here, we highlight RT GNSS displacement time series processed during the 2019 M w "> M w Mw 7.1 Ridgecrest, California, earthquake in the context of common rapid‐response products, magnitude estimation, and kinematic fault‐slip models. We discuss how these data can be used to supplement RT seismic data for rapid characterization of significant earthquakes. We find that kinematic fault‐slip models using RT GNSS data retain the general spatiotemporal characteristics of those with PP data, with subtle differences in size and amplitude of modeled slip asperities. We demonstrate the effect of these rapid seismic source models using RT GNSS data on the U.S. Geological Survey product ShakeMap—a downstream ground‐motion prediction algorithm informed by the rupture dimensions estimated in the slip model. Discrepancies in the ShakeMap estimate are minor, within ±12% change, with the most severe variation at the fault edges. Our analysis suggests that, when used in conjunction with available seismic data sources, RT GNSS is sufficient and valuable for rapid earthquake characterization.

California↗

USGS2015

Rapid characterization of the 2015 M w 7.8 Gorkha, Nepal, earthquake sequence and its seismotectonic context

Earthquake response and related information products are important for placing recent seismic events into context and particularly for understanding the impact earthquakes can have on the regional community and its infrastructure. These tools are even more useful if they are available quickly, ahead of detailed information from the areas affected by such earthquakes. Here we provide an overview of the response activities and related information products generated and provided by the U.S. Geological Survey National Earthquake Information Center in association with the 2015 M 7.8 Gorkha, Nepal, earthquake. This group monitors global earthquakes 24  hrs/day and 7  days/week to provide rapid information on the location and size of recent events and to characterize the source properties, tectonic setting, and potential fatalities and economic losses associated with significant earthquakes. We present the timeline over which these products became available, discuss what they tell us about the seismotectonics of the Gorkha earthquake and its aftershocks, and examine how their information is used today, and might be used in the future, to help mitigate the impact of such natural disasters.

Seismological Research Letters↗

USGS2019

Review of indicators for comparing environmental effects across energy sources

Robust, quantitative comparisons of environmental effects across energy sources can support development of energy planning strategies that meet growing demand while managing and minimizing undesirable effects on environmental resources. Multicriteria analyses of energy systems often use a suite of indicators to make such comparisons, but those indicators and their units of measure vary among studies. We reviewed 179 papers that described or applied energy indicators to compare environmental effects of different primary energy sources to answer four questions: (1) what environmental indicators have been used in multicriteria energy-source comparisons? (2) across studies, how consistently are these indicators used to quantify effects? (3) to what degree are different effects accounted for across energy sources and locations? and (4) how comprehensive are indicators in terms of assessing known environmental effects? For reviewed studies, we quantified the number of unique indicators and the diversity of indicators used to measure different effects. We also recorded the specific measurement units applied to quantify each indicator, the energy sources evaluated, and the continent where each study was conducted. While we found that many environmental effects of energy development have been analyzed across multiple sources, indicators were frequently measured, interpreted, and applied in ways that are not directly comparable, and some known environmental effects were infrequently assessed. We also found an emphasis on applying indicators to renewable energy sources; assessing current and potential energy sources, both renewable and nonrenewable, would greatly clarify the full suite of tradeoffs among sources and can inform energy development strategies that minimize adverse environmental effects. Overall, our review indicated that making comprehensive comparisons of the effects of energy development across sources may require efforts to standardize how effects are measured, synthesize effects literature into an open-source database, expand the range of environmental effects analyzed, and establish consistent frameworks for comparison.

Environmental Research Letters↗

USGS2020

Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data

Stream water temperature ( T s ) is a variable of critical importance for aquatic ecosystem health. T s is strongly affected by groundwater-surface water interactions which can be learned from streamflow records, but previously such information was challenging to effectively absorb with process-based models due to parameter equifinality. Based on the long short-term memory (LSTM) deep learning architecture, we developed a basin-centric lumped daily mean T s model, which was trained over 118 data-rich basins with no major dams in the conterminous United States, and showed strong results. At a national scale, we obtained a median root-mean-square error of 0.69°C, Nash–Sutcliffe model efficiency coefficient of 0.985, and correlation of 0.994, which are marked improvements over previous values reported in literature. The addition of streamflow observations as a model input strongly elevated the performance of this model. In the absence of measured streamflow, we showed that a two-stage model could be used, where simulated streamflow from a pre-trained LSTM model ( Q sim ) still benefited the T s model even though no new information was brought directly into the inputs of the T s model. The model indirectly used information learned from streamflow observations provided during the training of Q sim , potentially to improve internal representation of physically meaningful variables. Our results indicate that strong relationships exist between basin-averaged forcing variables, catchment attributes, and T s that can be simulated by a single model trained by data on the continental scale.

Environmental Research Letters↗

USGS2021

The 6 May 1947 Milwaukee, Wisconsin, earthquake

The State of Wisconsin is not known for earthquake activity. The authoritative public‐facing U.S. Geological Survey Comprehensive Catalog of earthquakes includes only three small (magnitude < 2) earthquakes in the state, all instrumentally recorded. Although other catalogs include more events in Wisconsin, experience has shown that many types of events, such as explosions and cryoseisms, have made their way into earthquake catalogs in this region. In this short report, I summarize available information about an earthquake that was felt in eastern Wisconsin at 15:27 local time on 6 May 1947. As what appears to be the largest historical earthquake in the State of Wisconsin, it is of public interest, its modest size notwithstanding. It appears that no useful instrumental records exist, due in part to a teleseismic event that occurred approximately 3 min later, generating surface waves that were recorded on early long‐period instruments in the region. Instrumental data may exist for this event but have not been found. Comparing the felt area with information from recent earthquakes in the region, I estimate an intensity magnitude of 3.8 for the event, with a subjectively estimated uncertainty range 3.5–4.1. Relatively strong effects, including reports of broken dishes in Milwaukee, and shaking described as short but especially sharp, suggest that the event may have been among the sprinkling of shallow earthquakes now known to occur in the upper Great Lakes region.

Wisconsin↗

USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗

USGS2020

The community code verification exercise for simulating sequences of earthquakes and aseismic slip (SEAS)

Numerical simulations of sequences of earthquakes and aseismic slip (SEAS) have made great progress over past decades to address important questions in earthquake physics. However, significant challenges in SEAS modeling remain in resolving multiscale interactions between earthquake nucleation, dynamic rupture, and aseismic slip, and understanding physical factors controlling observables such as seismicity and ground deformation. The increasing complexity of SEAS modeling calls for extensive efforts to verify codes and advance these simulations with rigor, reproducibility, and broadened impact. In 2018, we initiated a community code-verification exercise for SEAS simulations, supported by the Southern California Earthquake Center. Here, we report the findings from our first two benchmark problems (BP1 and BP2), designed to verify different computational methods in solving a mathematically well-defined, basic faulting problem. We consider a 2D antiplane problem, with a 1D planar vertical strike-slip fault obeying rate-and-state friction, embedded in a 2D homogeneous, linear elastic halfspace. Sequences of quasi-dynamic earthquakes with periodic occurrences (BP1) or bimodal sizes (BP2) and their interactions with aseismic slip are simulated. The comparison of results from 11 groups using different numerical methods show excellent agreements in long-term and coseismic fault behavior. In BP1, we found that truncated domain boundaries influence interseismic stressing, earthquake recurrence, and coseismic rupture, and that model agreement is only achieved with sufficiently large domain sizes. In BP2, we found that complexity of fault behavior depends on how well physical length scales related to spontaneous nucleation and rupture propagation are resolved. Poor numerical resolution can result in artificial complexity, impacting simulation results that are of potential interest for characterizing seismic hazard such as earthquake size distributions, moment release, and recurrence times. These results inform the development of more advanced SEAS models, contributing to our further understanding of earthquake system dynamics.

Seismological Research Letters↗

USGS2022

Rapid and gradual permafrost thaw: A tale of two sites

Warming temperatures and increasing disturbance by wildfire and extreme weather events is driving permafrost change across northern latitudes. The state of permafrost varies widely in space and time, depending on landscape, climate, hydrologic, and ecological factors. Despite its importance, few approaches commonly measure and monitor the changes in deep (>1 m) permafrost conditions with high spatial resolution. Here, we use electrical resistivity tomography surveys along two transects in interior Alaska previously disturbed by wildfire and more recently by warming temperatures and extreme precipitation. Long-term point observations of permafrost depth, temperature, and water content inform geophysical measurements which, in turn, are used to extrapolate interpretations over larger areas and with high spatial fidelity. We contrast gradual loss of recently formed permafrost driven by warmer temperatures and increased snowfall, with rapid permafrost loss driven by changes in air temperature, snow depth, and extreme summer precipitation in 2014.

Alaska↗

USGS2014

Operational earthquake forecasting can enhance earthquake preparedness

We cannot yet predict large earthquakes in the short term with much reliability and skill, but the strong clustering exhibited in seismic sequences tells us that earthquake probabilities are not constant in time; they generally rise and fall over periods of days to years in correlation with nearby seismic activity. Operational earthquake forecasting (OEF) is the dissemination of authoritative information about these time‐dependent probabilities to help communities prepare for potentially destructive earthquakes. The goal of OEF is to inform the decisions that people and organizations must continually make to mitigate seismic risk and prepare for potentially destructive earthquakes on time scales from days to decades. To fulfill this role, OEF must provide a complete description of the seismic hazard—ground‐motion exceedance probabilities as well as short‐term rupture probabilities—in concert with the long‐term forecasts of probabilistic seismic‐hazard analysis (PSHA).

Seismological Research Letters↗