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135 records · Page 2Linked to original sources
USGS2024

Aftershock forecasting

Aftershocks can compound the impacts of a major earthquake, disrupting recovery efforts and potentially further damaging weakened buildings and infrastructure. Forecasts of the probability of aftershocks can therefore aid decision-making during earthquake response and recovery. Several countries issue authoritative aftershock forecasts. Most aftershock forecasts are based on simple statistical models that were first developed in the 1980s and remain the best available models. We review these statistical models, and the wide-ranging research to advance aftershock forecasting through better statistical, physical, and machine learning methods. Physics-based forecasts based on mainshock stress changes can sometimes match the statistical models in testing, but don’t yet outperform them. Physical models are also hampered by unsolved problems such as the mechanics of dynamic triggering and the influence of background conditions. Initial work on machine learning forecasts shows promise, and new machine learning earthquake catalogs provide an opportunity to advance all types of aftershock forecasts.

Annual Review of Earth and Planetary Sciences↗
USGS2024

Wave propagation in layered soil deposits

Recent advances in the general theory of viscoelastic waves and rays in layered media provide a rigorous mathematical framework for site-specific, soil-response models used for earthquake resistant design. The advances provide general closed-form anelastic solutions for the classic problems of the response of a stack of soil layers to S and P waves, ray theory for reflected and refracted waves, Rayleigh- and Love-Type surface waves, and head waves. These general solutions valid for anelastic media regardless of the amount of material damping yield new insights regarding the characteristics of seismic waves and their ray paths that are not provided by conventional models. They provide corresponding numerical ground-response models and ray-tracing computation algorithms that account for changes in velocity and attenuation of anelastic waves associated with changes in inhomogeneity of the waves induced by anelastic soil and soil-rock boundaries. These anelastic effects manifest themselves as variations in amplitude response, amplitude attenuation, raypath location, and travel time as observed at the Earth’s surface. Implications of these anelastic effects for soil-response models used for earthquake resistant design are provided herein.

Conference Paper↗
USGS2025

Potential for continental scientific drilling to inform fault mechanics and earthquake science

Our understanding of fault mechanics and earthquake processes remains limited, largely due to minimal direct observations near active faults at seismogenic depths. This lack of data restricts our ability to accurately assess and mitigate both natural and human-induced seismic hazards. However, recent advancements in drilling capabilities and downhole sensing technologies offer an opportunity: the ability to observe the physical conditions within a volume near active fault zones. In this contribution, we highlight how scientific drilling can provide access to the near-fault environment, enabling measurements of the stress, temperature, fluid pressure, and rock properties at depths where ruptures initiate, propagate, and arrest. These observations are essential to refine models of earthquake nucleation and dynamic rupture, bridging gaps between laboratory experiments, numerical simulations, and surface observations. These insights can advance fundamental understanding in earthquake science but also support the development of more effective seismic hazard assessments and risk mitigation strategies.

Seismica↗
USGS2026

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation↗
USGS2025

Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization

Seawater intrusion (SWI) affects coastal landscapes worldwide. Here we describe the hydrologic pathways through which SWI occurs - over land via storm surge or tidal flooding, under land via groundwater transport, and through watersheds via natural and artificial surface water channels—and how human modifications to those pathways alter patterns of SWI. We present an approach to advance understanding of spatiotemporal patterns of salinization that integrates these hydrologic pathways, their interactions, and how humans modify them. We use examples across the East Coast of the United States that exemplify mechanisms of salinization that have been reported around the planet to illustrate how hydrologic connectivity and human modifications alter patterns of SWI. Finally, we suggest a path for advancing SWI science that includes (a) deploying standardized and well-distributed sensor networks at local to global scales that intentionally track SWI fronts, (b) employing remote sensing and geospatial imaging techniques targeted at integrating above and belowground patterns of SWI, and (c) continuing to develop data analysis and model-data fusion techniques to measure the extent, understand the effects, and predict the future of coastal salinization.

Water Resources Research↗
USGS2024

Streamflow depletion caused by groundwater pumping: Fundamental research priorities for management-relevant science

Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.

Water Resource Research↗
USGS1998

Satellite imagery of the north-central Gulf of Mexico, June 1993-May 1997

This CD contains imagery collected by the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar-orbiting weather satellites. The AVHRR provides almost daily coverage of a site at a resolution of approximately 1 km. The data types included are sea surface temperature (SST), water reflectance (REF), and a false-color infrared overview (FCI).

Alabama, Florida, Louisiana, Mississippi↗
USGS2026

The Great Lakes Geologic Mapping Coalition—Working collaboratively to understand the geology of the Great Lakes Region

Introduction The Great Lakes Geologic Mapping Coalition (GLGMC), commonly referred to as the “Coalition,” is a partnership between the U.S. Geological Survey (USGS), the U.S. States of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin and the Canadian province of Ontario. The member States receive funding for geologic mapping work from the USGS National Cooperative Geologic Mapping Program (NCGMP), whereas Ontario participates as a nonfunded partner. The mission of the GLGMC is to produce three-dimensional (3D) geologic maps that depict unconsolidated sediments and near-surface bedrock in the Great Lakes region of North America. Geologic maps are the basis of most earth science investigations and help support resource exploration (energy, minerals, groundwater), natural hazard mitigation, infrastructure development, and land-use planning, all of which can be used to advance economic development and strengthen national security in the Great Lakes region. During the last few million years, the Great Lakes region has experienced repeated glacial advances and retreats, leaving behind extensive sediments, abundant natural resources, and widespread effects on the underlying bedrock geology (Swezey and others, 2022). Linked by shared histories of past glaciations, industrial agriculture, and legacy automotive, coal, steel, and manufacturing industries, the GLGMC member States collaborate to improve the understanding of the 3D distribution of the sediments overlying the region’s bedrock (fig. 1). Developing a comprehensive subsurface 3D framework of this glaciated terrain can provide earth science data to policymakers at all levels. These insights facilitate informed decisions on the exploration, use, and protection of vital resources, such as critical minerals, industrial materials, and aquifers, thereby supporting economic prosperity and the well-being of the citizens of this region. Since its inception in 1998, the Coalition has completed more than 100 geologic mapping projects across the Great Lakes region. Each project aims to deliver geologic maps, 3D datasets, and other information that improves understanding of the geology of the Great Lakes region, with an emphasis on economic and water resources. Key deliverables include 3D geologic maps and models typically portraying sediment thickness, often derived from top-of-bedrock and borehole data. These products are developed through a combination of fieldwork, subsurface modeling, and the collection and analysis of rock and sediment cores. To support Coalition goals, member States collaborate with scientists working on related STATEMAP, EDMAP, and FEDMAP projects. Coalition scientists also engage with Tribal Nations in the Great Lakes region to ensure that Tribal interests pertaining to Coalition work are addressed. Through this collaboration, the Coalition unites the efforts of State, Federal, and Tribal Nation stakeholders to advance geologic data production and enhance understanding of the geologic resources of the Great Lakes region.

Illinois, Indiana, Michigan, Minnesota, New York, ↗
USGS2026

Making many out of one: Synthetic geologic deformation model distributions for use in USGS NSHM25‐PRVI Puerto Rico-U.S. Virgin Island update

A key use‐case of geologic slip rates is within deformation models used in probabilistic seismic hazard analyses. Field‐derived geologic slip rates have formed the cornerstone of deformation models in such applications for decades. Recent advancements in seismic hazard analyses have expanded the use of faults for which geologic slip rates are not well constrained using categorical slip rate estimates. Because of these advancements, application of a geologic deformation model for use in 2025 U.S. Geological Survey National Seismic Hazard Model Puerto Rico‐U.S. Virgin Islands (NSHM25‐PRVI) proved challenging due to: (1) a lack of field‐based geologic slip rates, and (2) a lack of epistemic uncertainty distributions within a broad range of estimated slip rates. Preliminary versions of the NSHM25‐PRVI model sampled these slip rate bins in a coincident manner along preferred and extreme value branches, which yielded untenable correlations in mean hazard results. To minimize the influence of correlated uncertainties amid these challenges, we develop a synthetic epistemic uncertainty distribution for deformation rate on each crustal fault. Each fault has a weighting schema across four possible distribution shapes: uniform, normal, triangular favoring local minima, and triangular favoring local maxima. The synthetic distributions are then sampled several times for each logic tree branch. The results provide a more realistic distribution of rates across the study region as compared with using correlated extrema sampling. This exploration of our method in a small region like PRVI can pave the way for larger‐scale, more complicated applications (e.g., western United States).

Puerto Rico, US Virgin Islands↗
USGS2025

Fiber-optic sensing for earthquake hazards research, monitoring and early warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

California, Oregon, Washington↗
USGS2025

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↗
USGS2025

Enhanced geothermal systems electric-resource assessment for the Great Basin, southwestern United States

The U.S. Geological Survey recently (2025) completed a provisional assessment of the geothermal-electric resources associated with high-temperature, low-permeability rock formations of the Great Basin, Southwestern United States. If sufficient technological advances to commercialize enhanced geothermal systems occur, then a current best provisional estimate for electric-power generation capacity of 135 gigawatts electric are available from the upper 6 kilometers of the Earth’s crust. This estimate is a potential substantial increase of the installed geothermal electricity-generating capacity from <1 to 10 percent of current total U.S. power production capacity.

California, Idaho, Nevada, Oregon, Utah↗
USGS2024

U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33

Executive Summary Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak to the need for nationwide interest and investment in earthquake hazard characterization and risk reduction. Authorized under the Earthquake Hazards Reduction Authorization Act, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) provides the scientific information, situational awareness, and knowledge necessary to reduce deaths, injuries, and economic losses from earthquakes and earthquake-induced tsunamis, landslides, and soil liquefaction. The EHP supports activities in three focused topical areas: (1) earthquake monitoring, (2) hazard assessment, and (3) applied research, using the results of each—and the coordination among them—to further support risk translation and communication in regions at risk nationwide. For earthquake monitoring, the Advanced National Seismic System (ANSS), a cooperative effort of USGS networks, university partner regional seismic networks, and real-time geodetic networks, collects and analyzes data on earthquakes; issues timely, reliable notifications of their occurrence and impacts; and provides data for earthquake research, hazard, and risk assessment as a foundation for building an earthquake-resilient Nation. The USGS-operated ShakeAlert Earthquake Early Warning system is a recent addition to EHP’s ANSS infrastructure. In the realm of earthquake hazard assessment, the EHP contributes to earthquake risk mitigation strategies by developing the National Seismic Hazard Model and maps, and other related products, that describe the likelihood and potential effects of earthquakes nationwide, especially in the urban areas of highest risk. The EHP also conducts research on the causes, characteristics, and effects of earthquakes and prioritizes work that directly increases the accuracy and precision of earthquake hazards assessments, earthquake forecasts, and earthquake monitoring and situational-awareness products and that supports the Nation’s earthquake mitigation practices. Bridging the EHP’s efforts across research, hazard assessments, and earthquake monitoring is a broad and comprehensive collection of earthquake information products, including the National Seismic Hazard Model, ShakeAlert, and other products describing impact, such as ShakeMap and PAGER (Prompt Assessment of Global Earthquakes for Response), which have been developed and integrated into EHP’s real-time monitoring systems. EHP funds external partners to carry out many important collaborative activities through an active external grants program—one of the largest in the USGS—and through cooperative agreements with other partners such as the university-operated regional seismic networks, funded as part of the ANSS. To continue its support of earthquake hazard characterization and risk reduction, the EHP aims to strengthen its foundational products and practices while positioning itself to respond to the evolving needs of the Nation and follow best practices of the scientific community. This document describes a strategy for the program to ensure it can meet these demands. The foundational priorities outlined in this strategy represent those activities that remain critical to the core functionality of the program and those that can be supported under current fiscal year 2024-level appropriations. Priorities described as aspirational are important for future growth, and to maintain the program’s position as a leading global resource in earthquake science, but would require increases in appropriated funding to be fully realized. Across the program’s portfolio of activities, several major themes have been identified as the most critical activities to advance EHP science over the coming decade. Together, these activities provide the framework necessary to integrate critical hazard characterization and risk reduction activities across the program. They provide the structure for research to advance the understanding of where, when, and why earthquakes occur and how we can use improved knowledge to drive short-term and actionable forecasts of seismic activity. They expand the usefulness of critical earthquake products and advance the sophistication of those products to keep pace with the rapidly evolving needs of an ever-expanding user base while maintaining the position of the USGS as a global leader in earthquake science. Focus on system-level science. Establish an automated earthquake-processing pipeline. Enhance the accuracy and reliability of the ShakeAlert Earthquake Early Warning system and plan for extension to other regions. Implement time-dependent earthquake forecasting. Develop physically realistic models. Expand computational capacity. This science strategy is organized into three primary sections. The first section provides an overview of the EHP and its budget, governance, and program council. Readers familiar with the program may wish to focus on the second section, which describes the core of the science strategy, including priorities across each of the EHP’s major program activities in monitoring, hazard assessment, and targeted research. The third section outlines science priorities that cut across program activities, including those involving collaborations external to the EHP.

American Samoa, Guam, Northern Marianas Islands, U↗
USGS2026

Simulated ground motion dataset in the Azores Plateau, Portugal, on rock and soil sites

Building on a previously developed bedrock dataset, this study extends the Azores Plateau ground motion simulations to include soil-amplified records and introduces a comprehensive validation framework. Soil amplification is modeled using one-dimensional soil profiles. A stochastic source-based approach is employed to generate the dataset, incorporating randomization of input-model parameters to account for the aleatory uncertainty in seismic activity. The accuracy of the dataset is verified through a comprehensive validation framework, showing that the randomization effectively captures variance and inter-period correlation observed in records. This work provides a robust dataset for advancing seismic hazard and risk assessment in the Azores Plateau.

central and eastern Azores islands↗
USGS2010

Divisions of geologic time—Major chronostratigraphic and geochronologic units

Effective communication in the geosciences requires consistent uses of stratigraphic nomenclature, especially divisions of geologic time. A geologic time scale is composed of standard stratigraphic divisions based on rock sequences and is calibrated in years. Over the years, the development of new dating methods and the refinement of previous methods have stimulated revisions to geologic time scales. Advances in stratigraphy and geochronology require that any time scale be periodically updated. Therefore, Divisions of Geologic Time, which shows the major chronostratigraphic (position) and geochronologic (time) units, is intended to be a dynamic resource that will be modified to include accepted changes of unit names and boundary age estimates. This fact sheet is a modification of USGS Fact Sheet 2007-3015 by the U.S. Geological Survey Geologic Names Committee.

Fact Sheet↗
USGS2025

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↗
USGS2026

Perspectives and insights gained from applying landscape ecological approaches to the Upper Mississippi riverscape

Advances in remote sensing, spatial data collection, hydraulic and geospatial models, and the maturation of landscape ecology during the early 2000s spurred the concept of rivers as landscapes or ‘riverscapes’. Since that time, the Upper Mississippi River Restoration (UMRR) Program - one of the world’s longest running large-river ecosystem restoration and monitoring programs - has applied landscape ecological principles to the Upper Mississippi River System (UMRS). I examine spatial patterns of aquatic nutrient concentrations, submersed aquatic vegetation, and fish and mussel communities, finding that within-river patterns are often patchy in nature, likely resulting from how nutrient processes and community traits interact with spatial variability in hydraulic exchange patterns. Local-scale patchy spatial patterns in the UMRS are embedded in system-scale longitudinal gradients and a hierarchical view of the river has provided a foundation for strategic river restoration planning. Key Words: Aquatic Habitat, hydraulic connectivity, patch, restoration, riverscape

BioScience↗