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486 records · Page 10Linked to original sources
USGS2025

Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows

In 2020, a wildfire burned across Glenwood Canyon in Colorado, USA. A history of postfire debris flows in the region and a hazard assessment for the burn area indicated that potentially life-threatening debris flows could be triggered by rainfall within months of a wildfire. As a result, four government agencies evaluated strategies to help mitigate hazards, including the loss of human life, that may be associated with debris-flow events. After the fire, 26 large debris flows occurred in the summer of 2021 and three sediment-laden flows occurred in the summer of 2023, but there were no major injuries or fatalities reported. We found that integrating hazard assessment/ forecasting, monitoring, and adaptation scenarios was a successful strategy for reducing postfire debris-flow risks to human life (including injuries and fatalities). Weather forecasts and estimates of debris-flow triggering rainfall thresholds, likelihood, and volume were used to anticipate the timing, location, and magnitude of debris-flow events. Rainfall monitoring and detailed recordkeeping of storms that triggered debris flows were used to validate and update debris-flow warning thresholds that varied with time following the wildfire. Although the governmental agencies working in this burn area had distinct and differing agency mandates, they were able to integrate information to reduce the risk of debris-flow events to human life.

Colorado↗
USGS2024

Utilization of stochastic ground motion simulations for scenario-based performance assessment of geo-structures

Probabilistic seismic performance assessments of engineered structures can be highly sensitive to the seismic input excitation and its variability. In the present study, the scenario-based performance assessment recommended by Federal Emergency Management Agency (FEMA) P-58 guidelines is adopted to estimate seismic fragility of concrete dams for various seismic hazard scenarios. Due to the scarcity of recorded ground motions and thereby their poor representation of uncertainties, stochastic ground motion simulation methods are utilized to obtain the required input excitations. Moreover, to understand the uncertainty in ground motion simulation models, two broadband stochastic simulation models are used to generate input excitations representing six seismic hazard scenarios defined by earthquake magnitude, source-to-site distance, and soil conditions. Optimal intensity measure parameters for each scenario are identified using a systematic procedure that considers criteria such as efficiency, practicality, proficiency, sufficiency, and hazard compatibility. Fragility curves and surfaces are derived using the cloud analysis technique, taking into account various damage measures and limit state functions. The study finds that the derived fragility curves are particularly sensitive to the selection of earthquake scenarios, the choice of records, and the methods used to calculate fragility curves, with less sensitivity observed to different engineering demand parameters. Given this sensitivity, particularly to ground motion selection, the study highlights the necessity of incorporating both model-to-model variability (epistemic uncertainty) and record-to-record variability (aleatory uncertainty), alongside the established material and modeling uncertainties, in the probabilistic seismic assessment.

Reliability Engineering and System Safety (RESS)↗
USGS2024

Triggering the 2022 eruption of Mauna Loa

Distinguishing periods of intermittent unrest from the run-up to eruption is a major challenge at volcanoes around the globe. Comparing multidisciplinary monitoring data with mineral chemistry that records the physical and spatio-temporal evolution of magmas fundamentally advances our ability to forecast eruptions. The recent eruption of Mauna Loa, Earth’s largest active volcano, provides a unique opportunity to differentiate unrest from run-up and improve forecasting of future eruptions. After decades of intermittent seismic and geodetic activity over 38 years of repose, Mauna Loa began erupting on 27 November 2022. Here we present a multidisciplinary synthesis that tracks the spatio-temporal evolution of precursory activity by integrating mineral and melt chemistry, fluid inclusion barometry, numerical modeling of mineral zoning, syn-eruptive gas plume measurements, the distribution and frequency of earthquake hypocenters, seismic velocity changes, and ground deformation. These diverse data indicate that the eruption occurred following a 2-month period of sustained magma intrusion from depths of 3–5 km up to 1–2 km beneath the summit caldera, providing a new model of the plumbing system at this very high threat volcano. Careful correlation of both the geochemistry and instrumental monitoring data improves our ability to distinguish unrest from the run-up to eruption by providing deeper understanding of the both the monitoring data and the magmatic system—an approach that could be applied at other volcanic systems worldwide.

Hawaii↗
USGS2026

Evolution of arsenic speciation during thermal treatment simulating wildfire heating in arsenic-rich sediments

Understanding arsenic transformations during wildfires can help better constrain the environmental impacts of increased wildfire intensity, frequency, and burned area. Previous studies have monitored the evolution of metal(loid) speciation at specific time/temperature endpoints, hampering the comprehension of the dynamic transformations of metal(loid)s during wildfires. Here, a novel approach, namely in situ time-resolved X-ray absorption near edge structure (TR-XANES) spectroscopy, was used for the first time to monitor the heat-induced redox transformations of arsenic (As) in two As-rich sediments with different characteristics. No arsenic transformations were observed in either sediment at room temperature or when the sediments were heated to a maximum temperature of 400 ºC. When heated to a maximum temperature of 600 or 700 ºC, As underwent complex, dynamic, and partially reversible redox transformations, the extent of which varied with sediment properties, initial As speciation, and heating temperature and duration. In the case of sediments initially containing As(V) and a low sulfide/sulfate ratio, the As(V) was reduced to As(III) over a short period of time, followed by immediate reoxidation of As(III) to As(V). The extent of the transient As reduction increased with increasing maximum temperature. The final As speciation at the end of the heating experiment was not substantially different from that at the beginning of the experiment. In contrast, in sediments that were best described by a more complex combination of reference compounds (As(V) coprecipitated with or adsorbed on iron oxide, arseniosiderite, arsenopyrite) with a high sulfide/sulfate ratio, As(V) phases were reduced to As(III) and As(III) was further reduced to As(-I) (at 700 ºC, only), followed by delayed reoxidation of As(-I) to As(III) (at 700 ºC, only) and reoxidation of As(III) to As(V). Approximately 9% and 26% of all As remained as As(III) ( i.e., was not reoxidized to As(V)) at the end of the experiment when heated to a maximum temperature of 600 and 700 ºC, respectively, which is higher than the relative abundance of As(III) in the native sediment. These fire-induced As transformations can potentially enhance As mobilization to surface water and groundwater, posing risks to environmental and human health.

California↗
USGS2026

Low-frequency earthquakes track the motion of a captured slab fragment

Accurate tectonic models are essential for assessing seismic hazard and fault interactions. However, the plate configuration at the complex Mendocino triple junction, where the San Andreas Fault and the Cascadia subduction zone meet, remains uncertain. We analyzed fault slip associated with a recently identified zone of tectonic tremor and low-frequency earthquakes (LFEs) near the southern edge of the subducting Gorda slab. Based on tidal sensitivity and P-wave first motions, we show that the LFEs are generated by dipping, strike-slip motion. This suggests that a former Farallon slab fragment, now captured by the Pacific plate, is translating northward beneath westernmost North America. This geometry effectively extends the slab interface fault, challenging prevailing interpretations of slab window formation and creating a potential unaccounted earthquake hazard in this region.

Science↗
USGS2025

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California↗
USGS2025

U.S. Geological Survey geomagnetic variometer data: Capitalizing on seismic infrastructure

The U.S. Geological Survey’s Geomagnetism Program is collaborating with the Earthquake Hazards Program and Global Seismographic Network Program to densify magnetic field observations. This collaboration focuses on the installation of magnetometers, or magnetic variometers, at existing seismic stations. Along with improving the density of space weather observations for hazard monitoring, these data can be used to correct colocated magnetic field induced noise in seismic data. Such corrections are especially useful during time periods of large magnetic storms where the magnetic field‐induced instrument noise can be of similar amplitude to earthquake ground‐motion records.

contiguous United States↗
USGS2024

Introduction to recommended capabilities and instrumentation for volcano monitoring in the United States

Introduction The National Volcano Early Warning System (NVEWS) was authorized and partially funded by the U.S. Government in 2019. In response, the U.S. Geological Survey (USGS) Volcano Hazards Program asked its scientists to reflect on and summarize their views of best practices for volcano monitoring. The goal was to review and update the recommendations of a previous report (Moran and others, 2008) and to provide a more detailed analysis of capabilities and instrumentation for monitoring networks for U.S. volcanoes. This Scientific Investigations Report and its chapters reflect those USGS scientists’ views and summaries and will serve as a guide for future network upgrades funded through NVEWS. Given the well-documented hazards posed by volcanoes to population centers and aviation (for example, Blong, 1984; Scott, 1989; Neal and others, 1997, 2019; Guffanti and others, 2010; Shroder and Papale, 2014; Prata and Rose, 2015; Palmer, 2020), volcano monitoring is critical for ensuring public safety and for mitigating the impacts of volcanic activity. Accurate and timely forecasts are facilitated by well-designed monitoring networks that are in place long enough to allow for background behavior to be recognized and understood. Because precursory signals may be limited and unrest may progress rapidly to an eruption, our goal is to deploy monitoring systems that enable detection of the reactivation of dormant volcanoes as early as possible, allowing for public safety and risk mitigation. NVEWS planning is also informed by the results of Ewert and others (2005, 2018), whereby 161 U.S. volcanoes are currently categorized and ranked commensurate with their relative threat. In each chapter, author(s) considered the need for some redundancy of instrumentation and telemetry, given the likelihood of occasional equipment failure, particularly in extreme and remote environments. Establishing digital telemetry networks requires advanced planning, sighting, radio-shot testing, and, inevitably, troubleshooting in the field. This is harder to achieve rapidly during a crisis; thus, an important goal for monitoring U.S. volcanoes is to establish digital telemetry backbones with redundancy and extra capacity to absorb additional instruments should a volcano begin to exhibit signs of unrest (fig. A1). The National Telecommunications and Information Administration (NTIA) imposed new regulations in the United States, eliminating the use of older analog radios for many purposes, which had been one previous means for redundant data delivery. However, the resulting conversion from analog to digital systems usefully enables stations to accommodate new and multivariate real-time data streams (for example, Global Navigation Satellite System [GNSS] receivers, infrasound arrays, gas spectrometers, visible and infrared cameras, and broadband seismometers). We note that other USGS and broader national and international hazard programs can leverage NVEWS instrumentation plans. Examples of this include the following: Improved seismic coverage of volcanoes will increase the capability of the USGS Earthquake Hazards Program to detect and locate earthquakes, estimate ground shaking, and provide timely early warnings through the ShakeAlert Earthquake Early Warning System (Given and others, 2018). The National Oceanic and Atmospheric Administration’s Tsunami Program will benefit from additional seismic stations, particularly within the sparsely instrumented Aleutian Islands, Northern Mariana Islands, and American Samoa. Infrasound stations can detect signals from landslides, debris flows and lahars, floods, and weather events, providing benefits to the National Weather Service and the USGS Landslide Hazards Program.

Scientific Investigations Report↗
USGS2025

Estimated average annualized tsunami losses for the United States

Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels. Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below. ■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events. ■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin. ■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest. ■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats. ■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin. ■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea. Several historical events stand out because of their catastrophic impacts. ■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005). ■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982). ■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023). ■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024). ■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011). More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis. This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.

Alaska, California, Hawaii Oregon, Washington↗
USGS2025

Rainfall thresholds for postfire debris-flow initiation vary with short-duration rainfall climatology

The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris-flow initiation are commonly expressed as rainfall intensity-duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass-movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff-generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris-flow initiation thresholds vary systematically with short-duration rainfall-intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much-needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field-based hazard assessment. Furthermore, if the observed variation in thresholds reflects long-term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris-flow likelihood.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the southern Appalachian orogen

The first quantitative mineral resource assessment for undiscovered lithium pegmatite deposits in the southern Appalachian region of the United States was conducted. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical and mineral occurrence data. Lithium pegmatite prospectivity of the tracts was ranked with simplified mappable criteria, including proximity to Paleozoic felsic intrusions and major lithotectonic structures, stream sediment geochemical anomalies, and pegmatite occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. These estimates were integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was applied to convert the probabilistic estimates of contained lithium into recoverable material. The identified lithium pegmatite resources for the Carolina Lithium and Kings Mountain deposits, North Carolina, contain 1589 thousand tons (kt) of Li 2 O. The median contained undiscovered resource for the southern Appalachian orogen was estimated to be 2240 kt Li 2 O. At 90% confidence, the region contains at least 130 kt Li 2 O, and 10,700 kt at 10% confidence. After applying economic filters, the median recoverable contained resource was 1430 kt Li 2 O, corresponding to approximately 201 years of current lithium imports for consumption in the United States. North and South Carolina are likely to contain most of these resources. Coarse data resolution and intra-state variations in the geological data contribute to uncertainty of undiscovered lithium pegmatite resources. Continued efforts to harmonize disparate geospatial datasets with updated or new information can improve the accuracy and precision of estimated undiscovered lithium pegmatite resources in the study area and at broader scales.

Alabama, Georgia, Maryland, North Carolina, South ↗
USGS2025

The abandoned mine inventory of the United States—A brief summary

The Infrastructure Investment and Jobs Act of 2021 required the Secretary of the Interior to establish a program to inventory abandoned hard-rock mines in the United States. The Department of the Interior’s Office of Environmental Policy and Compliance asked the U.S. Geological Survey’s Mineral Deposit Database project (USMIN) to use existing data sources to build an inventory of all individual abandoned mine features in the United States. In addition to feature locations, this new database documents the surface land management agency, associated physical and environmental hazards, and any completed mitigation efforts. This information will improve risk assessment and support land management efforts, including hazard mitigation, ecosystem restoration planning, and reclamation. This fact sheet provides a brief overview of USMIN’s collaborative efforts with Federal, State, and Tribal agencies to build a comprehensive and authoritative national inventory of abandoned mine features.

Fact Sheet↗
USGS2025

Site-specific, extended ShakeMaps for earthquake engineering applications

The U.S. Geological Survey (USGS) routinely produces ShakeMaps of shaking intensity across the globe. Due to practical constraints, the number of response spectral periods was limited to three standard periods (0.3, 1.0, and 3.0 sec). We have recently developed the tools that are necessary to expand this functionality to include 22 periods (matching the current U.S. National Seismic Hazard Model periods) as well as the orientation-independent components (e.g., “RotD50”). We refer to ShakeMap products that include these extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool called the “ShakeMap Sampling Tool” (SST) that gives all the estimated shaking metrics for a specific location (or list of locations). Additionally, we develop a web application where users can input locations of interest and view/download the SST results. We further familiarize users with the concept of “Composite ShakeMaps.” For earthquakes sequences such as a mainshock and larger foreshocks and aftershocks, this provides a map of the maximum value of each shaking metric, which is useful for overall loss estimates, the full extent of ground failure triggering potential, and a better portrayal of the repeated shaking levels at a given point for a series of earthquakes. Such a site-specific shaking history facilitates earthquake forensics at building or infrastructure sites for which damage may be of concern, as described in the Disproportionate Damage Earthquake trigger specified in the IEBC (2018, Section 405.2.2) and in developing ATC-145 guidelines (Guidelines for Post-Earthquake Assessment, Repair, and Retrofit of Buildings). The composite ShakeMap can be combined with the SST for a variety of earthquake-hazard applications, such as systematically inferring triggering shaking estimates at specific sites of geotechnical interest for landsliding, liquefaction, and lateral-spreading hazards.

Kahramanmaraş↗
USGS2026

Ground-motion aleatory-variability models for Puerto Rico and the U.S. Virgin Islands

I develop independent logic trees for aleatory variability for crustal and subduction-zone (interface and intraslab) earthquakes for seismic hazards analyses in Puerto Rico and the U.S. Virgin Islands (PRVI) from existing suites of ground-motion models (GMMs) and from ground-motion datasets, including a regional PRVI dataset. The aleatory variability models are parameterized using a partially nonergodic partitioning of standard deviation that consists of independently developed between-event ( ), site-to-site ( ), and event-corrected single-station ( ) standard deviation components. The effects of nonlinear site response on aleatory variability are incorporated through additional terms that modify the standard deviation components. Because one goal of this work is to develop independent logic trees for aleatory variability that synthesize the aleatory variability models from GMMs, I make use of the functional forms of the input GMMs. The PRVI dataset contains a limited number of stations with high-quality site metadata and does not contain records from earthquakes with magnitudes greater than 6.1, so I choose not to develop the aleatory variability models from the regional dataset alone. Instead, the standard deviation components from regional ground-motion data are evaluated against the components derived from GMMs and from available global datasets, and regionalized standard deviation components are incorporated where there is evidence that regional effects exhibit substantial differences. The resulting logic trees for aleatory variability consist of models of and that are consistent with semiempirical GMMs for active crustal and subduction-zone regimes, and two alternative models of , including one model that exhibits site-to-site variability informed by PRVI data, with values that exceed global models. The aleatory variability models may be considered in future hazards assessments in PRVI to simplify the hazard calculations, to incorporate regional ground-motion variability effects, and to enable direct logic-tree weighs of aleatory variability.

Puerto Rico, U.S. Virgin Islands↗
USGS2024

Geologic map of the northwest flank of Mauna Loa volcano, Island of Hawai‘i, Hawaii

Mauna Loa, the largest active volcano on Earth, has erupted 34 times since written descriptions became available in A.D. 1832. The most recent eruption of Mauna Loa occurred on November 27, 2022, after a 38 year hiatus; it lasted for 12 days. Some eruptions began with only brief seismic unrest, whereas others followed several months to a year of increased seismicity. Once underway, Mauna Loa’s eruptions can produce lava flows that may reach the sea in less than 24 hours, severing roads and utilities. For example, lava flows that erupted from the Southwest Rift Zone in 1950 advanced at an average rate of 9.3 kilometers per hour (5.8 miles per hour); all three lobes reached the ocean within ~24 hours. Near the eruptive vents, the flows likely traveled even faster. In terms of eruption frequency, pre-eruption warning, and rapid flow emplacement, Mauna Loa has great volcanic-hazard potential for the Island of Hawai‘i. Volcanic hazards on Mauna Loa can be anticipated, and risk substantially mitigated, by documenting its past activity to refine our knowledge of the hazards, and by alerting the public and local government officials of our findings and their implications for hazards assessments and risk. The map of the north and west flanks of Mauna Loa shows the distribution and relation of volcanic and surficial sedimentary deposits. It incorporates previously reported work published as generalized small-scale maps and a more detailed map. Within the mapped area, lava has flowed from three different source regions: the Northeast Rift Zone (22 percent), the summit (64 percent), and radial vents (14 percent). All three have different points of origin which, in turn, affect the flow characteristics and periodicity of activity. The map area includes the uppermost part of the NERZ and extends from the highest elevation––13,040 feet at the south end of the Kokoolau quadrangle, just below the summit caldera––to the sea northwest and west of the summit. Lava that erupts from the north and west flanks typically flows to the west, northwest, or north, depending on the vent location. Both morphologic lava flow types—‘a‘ā and pāhoehoe—are present. Pāhoehoe units tend to spread out or widen in low-slope regions, such as in the saddle regions between Mauna Loa and Mauna Kea or between Mauna Loa and Hualālai. In comparison, ʻaʻā flows generally produce narrower flow lobes that have higher relief. This map is the fifth in a series of five maps that will cover Mauna Loa volcano. NOTE: Map sheet 1 contains lines and type with overprint. This feature may be turned on or off in the Adobe Acrobat page display preferences.

Hawaii↗
USGS2026

Dynamic coupling between faulting, rifting and magmatism during 2021-2025 unrest on Reykjanes Peninsula, Iceland

Interactions among faulting, earthquakes, and eruptions are fundamental to plate tectonics and hazard forecasting yet rarely observed along mid-ocean ridges. On Iceland's Reykjanes Peninsula, seismotectonic–volcanic unrest resumed after nearly 800-year hiatus, providing an opportunity to observe these interactions during 2021–2025 activity. By integrating high-resolution seismicity, focal mechanisms, satellite geodesy, surface deformation, and eruption data, we document ∼4 m of total extension accommodated through 14 rifting episodes. The largest, in 2023, involved graben reactivation and diking, with seismic swarms and earthquake faulting that matched the surface ruptures, where strike-slip faulting preceded normal-faulting earthquakes and extension. The accrued extension was released by extension fractures triggered by magma accumulation. Long-term observations show no correlation between erupted magma volume, seismicity, and crustal extension. This highlights dynamic relation between rifting, faulting, and magmatism in transtensional settings and their implications for hazard assessment.

Reykjanes Peninsula↗
USGS2024

Coastal Science Navigator companion guide—Discover the U.S. Geological Survey coastal science products you need

The Coastal Science Navigator is an online gateway to a wide variety of U.S. Geological Survey (USGS) coastal change hazards-related information, data, and tools relevant to stakeholders’ scientific and decision-making needs. The products within the Coastal Science Navigator provide data related to past, present, and future threats to our coastlines. The filter search allows users to see all available products and identify relevant options by time scale, geographic scope, coastal hazard theme, and other filters. The guided search suggests products based on users’ answers to a short series of questions. A comprehensive summary is available for each product. The idea for the Coastal Science Navigator arose in 2020 in response to stakeholder feedback identifying the need for a central source for USGS coastal science information. It was published in July 2023 and initially included 55 products. Regular updates are planned to integrate other existing and new products. This guide introduces some of the many coastal change hazards-related products available through the USGS. In it, we showcase the products included in the Coastal Science Navigator’s initial publication in July 2023. While it is not representative of all the information, tools, and data available, we hope it serves as a compelling snapshot of what the USGS has to offer and encourages you to explore the Coastal Science Navigator to discover more of the products you need. To navigate this guide, the products have been organized by the time scale they are best suited for—past, present, or future—although many products cover multiple time scales. An additional section features software, one of the many product types available as filters within the Coastal Science Navigator. Other products include downloadable data, websites, and geonarratives (web pages that combine text, images, and interactive maps into narratives you can scroll through). Featured geographic scopes are also highlighted within this guide, detailing some of the many regions in which the USGS conducts research and illustrating another way to filter products within the Coastal Science Navigator.

Circular↗
USGS2026

Efficient physics‐informed ground‐motion simulations with reduced‐order models: CyberShake implications and high‐resolution site terms for southern San Andreas fault earthquakes

Recent advances in Probabilistic Seismic Hazard Analysis (PSHA) leverage physics‐based ground‐motion simulations to estimate seismic hazard, such as the CyberShake project. However, computational costs quickly escalate when performing PSHA for numerous faults or sites and can become prohibitively expensive. To reduce computational demands, CyberShake uses reciprocity and interpolates physics‐informed corrections from simulations conducted at fewer locations, but the accuracy of these interpolations remains poorly quantified. To quantify the interpolation accuracy, we derive high‐resolution, frequency‐dependent site terms for southern California and compare them with interpolated site terms using the CyberShake approach. We accomplish this by performing a set of earthquake point‐source simulations distributed along the nonplanar fault geometry for the southern San Andreas fault (SSAF) extending from Bombay Beach to Lake Hughes. Using SeisSol, we simulate three minutes of viscoelastic seismic wave propagation for these sources and store the horizontal‐component Green’s functions for 480,000 sites. We then use a scientific machine learning approach based on interpolated proper orthogonal decomposition to construct an accurate reduced‐order model of the Green’s functions to efficiently predict effective amplitude spectra (EAS) for finite‐source rupture models of SSAF earthquakes. Using minimum curvature interpolation with tension, as used in CyberShake, we compare the interpolated site terms against our high‐resolution site terms. We identify local discrepancies with EAS differing by up to a factor of approximately three. Furthermore, we identify locations where unexpectedly high or low ground motions are missed when using the interpolated dataset for these earthquakes. We estimate that our approach may be used within CyberShake to reduce the time‐to‐solution by a factor of 336 for the entire earthquake rupture forecast. Our analysis of physics‐based site terms provides more insight into the seismic hazard due to SSAF ruptures and guides future developments by combining high‐performance computing and reduced‐order modeling techniques for PSHA.

California↗