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USGS2025

Assessing earthquake risks to lifeline infrastructure systems in the United States

The security and economic stability of the United States rely heavily on robust lifeline infrastructure systems and yet the risks to such systems are seldom quantified at the national scale. For example, while earthquake risks to buildings in the United States have been investigated at the national scale regularly, such risks to gas pipelines have rarely been investigated nationally. In this paper, we use examples from two critical infrastructure sectors to demonstrate (1) the nature of earthquake risks to lifeline infrastructure systems, (2) complexities involved in regional seismic risk assessments, and (3) how such risks change with time. We found that bridge risks can be underestimated by at least 64 % when viewed from repair costs instead of traffic demands and that regional risks can be underestimated by 19 % when spatial correlations of ground motion are ignored. Further, exceedance of traffic demand can be 50 times more likely to occur when viewed at the regional scale than when viewed at an individual bridge. Similarly, exceedance of repairs can be 180 times more likely to occur when viewed at the pipeline network level than at a segment-specific level. Finally, sensitivity analyses with the 2018 and 2023 USGS National Seismic Hazard Models indicate an increase in bridge risk of at least 24 % and an increase in exposed gas pipeline mileage of 43 %. The evolution of risks, complexities involved in assessments, and limited resources jointly underscore the need for more routine updates to nationwide seismic risk assessments of lifeline systems in the United States.

International Journal of Critical Infrastructure P↗

USGS2025

Meet the people where they are: Assessing user needs for aftershock forecast products in El Salvador, Mexico and the United States

Aftershock forecasts can help communities reduce their seismic risk by conveying how many aftershocks can be expected following a large earthquake, and how the expected number of aftershocks and their corresponding ground shaking evolves over time and space. Prior work finds that graphical forecast products may communicate such information better than only text or numbers. To identify which visual products can serve multiple user groups, we held workshops with members of several professions, including emergency managers, engineers, critical infrastructure operators, public health specialists, science communicators, and more. We conducted these workshops in El Salvador, Mexico and the United States to understand which forecast products may be effective across different countries. In these workshops, users performed small-group activities to elicit the types of aftershock forecast information that would support decisions in their respective roles and how this information would optimally be displayed. Maps of shaking hazards were frequently requested across all professions and countries, even for dissimilar forecast uses. The design of these maps, and other product needs, were differentiated by profession, country and other factors. Other forecast products, including those showing forecasts about the magnitudes and time periods of future aftershocks, also served a variety of users, but for different types of decisions. We found a greater variation in user needs by profession than by country, and that user needs also vary with time, communication channel and other contextual factors. We discuss practical implications for user-centered visual communication of operational aftershock forecasts.

International Journal for Disaster Risk Reduction↗

USGS2026

Opportunities for the U.S. Geological Survey’s National Seismic Hazard Model to improve seismic risk assessment of critical infrastructure.

As fragility and risk modeling techniques and computational capabilities evolve, complemented by moving toward more routine and systematic seismic risk assessment of all buildings and critical infrastructure, the authors pose a few critical questions to investigate how the U.S. Geological Survey (USGS) National Seismic Hazard Models (NSHMs) can be used and enhanced further to serve such issues. In this paper, we use three examples from multiple sectors to (1) identify the role of USGS NSHMs in evaluating seismic risks to critical infrastructure, (2) quantify potential impacts from NSHM enhancements (i.e., [i] hazard curves for the vertical component of ground motion, [ii] stochastic event sets, and [iii] maps of probabilistic ground failure hazards), and (3) clarify the feasibility of relevant NSHM improvements. We illuminate that NSHMs are commonly used in location-specific performance assessments, whereas earthquake effects on critical infrastructure can be widespread across large geospatial regions. Further, we found that without the NSHM extensions considered here, risk can be severely underestimated, e.g., neglecting ground failure hazards can underestimate regional loss by a factor of two or more. Although many challenges remain, we developed example prototypes to clarify the feasibility of the NSHM extensions, which can facilitate improved management of risks to critical infrastructure.

Earthquake Spectra Journal↗

USGS2026

Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database

The global demand for critical mineral commodities is rapidly increasing, making domestic production an important factor in supporting the economy and national security. Large scale, publicly available geochemical databases allow for the application of data informatics methods to interrogate critical mineral commodities data for correlations in deposit formation and distribution, particularly for identifying enrichment of multiple critical mineral commodities at the same deposit. In this study, we applied network analysis to the Critical Minerals Mapping Initiative (CMMI) ore geochemistry (Critical Minerals in Ores, CMiO) database to identify the high concentration (defined as 10× bulk crustal abundance) co-occurrence of different critical mineral commodities across a mineral system hierarchy from deposit environments to individual deposits. Identifying patterns or unique outliers in enrichment in network communities will allow for the location of secondary critical mineral commodity resources from under-utilized deposits. We find trends in the enrichment of critical mineral commodities in network-communities between the elements praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) across multiple CMiO database deposit environments and groups down to specific deposit types and sites. A separate trend in network community deposition is observed as well between iridium (Ir) and platinum (Pt) in deposit environments, groups, types, and sites. Network analysis focused on critical minerals in magmatic-hydrothermal deposits identified multiple deposit sites from different deposit types within the CMiO database with concentrations of Dy, Nd, Tb, Pr, Ir, and Pt that are at least ten times greater than the crustal average. This approach can be applied to any target element(s) or deposit(s) of interest, allowing broad investigation of co-enriched critical mineral commodities.

Journal of Geochemical Exploration↗

USGS2024

Mitigating climate change by abating coal mine methane: A critical review of status and opportunities

Methane has a short atmospheric lifetime compared to carbon dioxide (CO 2 ), ∼decade versus ∼centuries, but it has a much higher global warming potential (GWP), highlighting how reducing methane emissions can slow the rate of climate change. When considering the contribution of greenhouse gas (GHG) emissions to current global warming (2010–2019) relative to the industrial revolution (1850–1900) levels, methane contributes 0.5 °C or ∼ a third of the total. The most recent post-2023 global estimates of methane emissions by bottom-up (BU) and top-down (TD) approaches for the coal mining sector are in the range of ∼41 ± 3 Tg yr −1 and 33 ± 5 Tg yr −1 , respectively. This divergence, notwithstanding overlapping confidence intervals, is a result of differences between applied TD global inversion models and BU emission inventories. Further research can help to better refine emissions from the various contributing coal mine methane (CMM) emissions sources. The coal mining sector accounts for over 10 % of global anthropogenic methane emissions. The contribution of CMM emissions to the global budget have increased since 2000, although upward and downward regional trends have been observed.

International Journal of Coal Geology↗

USGS2026

Deaf, deafblind, and hard of hearing university student experiences with earthquake early warning in the United States: Evaluating language planning and technology access

The growing literature on deaf and hard of hearing (DHH+) populations and disasters demonstrates that emergency communication (including alerts) is not reaching global DHH + individuals with dangerous impacts for morbidity and mortality. This is the first research study in the U.S. to qualitatively explore the experiences of DHH + persons with earthquake early warning (EEW) through group-based dialogue sessions. The study investigates eight DHH + university students'past earthquake experiences, access to EEW alerts, and perceptions of ShakeAlert Ⓡ , an EEW system for detecting earthquakes and alerting residents of California, Oregon, and Washington. Findings highlight key gaps in disaster alert usability within four thematic areas: lack of messaging in participants' language(s), unclear alert messaging, deficient message delivery mechanisms for deafblind persons, and insufficient access to earthquake information and training that leads to dependence on informal information networks. Weaknesses identified in these four themes reduce DHH + trust in EEW systems and compromise the capacity of alert recipients to take swift protective action or to mentally prepare before shaking starts. The study also underscores structural factors such as insufficient linguistic representation in disaster language planning and technology design, which ignores the linguistic and sensory access needs of DHH + individuals. Building on disaster language planning frameworks, we recommend involving DHH + populations to co-develop EEW alerts. By centering DHH + perspectives, this research contributes to ongoing efforts to ensure that EEW systems reach everyone.

California↗

USGS2024

ShakeAlert® and schools: Incorporating earthquake early warning in school districts in Alaska, California, Oregon, and Washington

The U.S. Geological Survey-managed ShakeAlert® earthquake early warning system is the first public alerting system in the United States to provide rapid mass notification when an earthquake is detected. Although public alert delivery via mobile phones began in California in 2019 followed by Oregon and Washington in 2021, little is known about what might drive widespread implementation in at-risk institutional settings such as schools. For example, there has been limited research on how to best integrate earthquake early warning into existing emergency plans, alert systems, and drills to keep school children and personnel safe in an earthquake. To address this gap, in the spring of 2022, every school district superintendent in Alaska, California, Oregon, and Washington was sent a 15-min online survey. The survey assessed superintendent knowledge of ShakeAlert, preferences for alert messaging, and perceived opportunities and barriers to incorporating the system in schools. The results showed that superintendents had low awareness of ShakeAlert but held positive perceptions of the system's potential to enable life-saving protective actions. A major barrier to adoption included the perceived financial cost of implementing and maintaining the system. There were some statistically significant differences in state responses, and future research could investigate the specific needs of each state based on school district size and composition, hazard exposure, and earthquake experience. Together these findings can help inform targeted strategies to increase ShakeAlert adoption in schools and ultimately improve the safety of school children and staff during earthquakes.

Alaska, California, Oregon, Washington↗

USGS2026

Earthquake-hazard exposure of residents with potential access and functional needs in the United States

Earthquake response plans and earthquake early warning (EEW) systems designed for general populations may not consider potential access and functional needs (AFN) of individuals with physical, sensory, cognitive, or social limitations. Previous efforts to map the distribution of these populations have focused on social-vulnerability indices that ignore or oversimply these limitations. The descriptive and exploratory analysis summarized in this United States (U.S.) case study addresses this gap by identifying and integrating spatially explicit data for AFN-related residential populations, earthquake hazards, and county and county equivalents for the conterminous U.S., Alaska, Puerto Rico, and Hawaii. We focus on 13 AFN-related attributes that relate to an individual's ability to access information contained in an EEW alert, to understand and process earthquake information or observed ground shaking, and to take self-protective actions based on this information and physical cues of an earthquake. Depending on the demographic attribute, there are millions to tens of millions of U.S. residents with AFN-related attributes in areas considered to have varying likelihoods (2%, 10%, and 50%) of exceedance of a damaging earthquake in the next 50 years. Although these amounts represent low percentages at the national level, the percentage of individuals with AFN-related attributes in many counties and county equivalents substantially exceeds national percentages. No one county, county equivalent, U.S. state, or U.S. territory has the highest percentage of individuals in all AFN-related attributes; therefore, future efforts to increase individual resilience to earthquakes may benefit from understanding the local context of individuals with potential access and functional needs.

International Journal of Disaster Risk Reduction↗

USGS2026

Surface-wave relocation and characterization of the 2024–2025 dyking episode along the Fentale–Dofen segment of the Ethiopian rift

From late-December 2024 to mid-March 2025, a 50-km-long dyke intrusion triggered over 300 earthquakes (magnitude 4 to 5.9) between Fentale and Dofen volcanoes along the Northern Main Ethiopian Rift. Dyke intrusions periodically occur along the Fentale–Dofen magmatic segment and are an expression of ongoing rift extension. Preliminary analyses using interferometric synthetic aperture radar revealed extensive ground deformation (up to 60 cm), which closely matched the temporal and spatial evolution of surface manifestations and earthquake locations from global catalogues. While global catalogues are critical for real-time monitoring, the precision of locations in remote and or sparsely instrumented regions can be low. In this investigation, we present surface-wave relocation results of the dyking episode that began near Fentale volcano in December 2024. We estimate relative locations using differential traveltimes measured from regional-to-teleseismic distance surface-wave observations of earthquakes reported by the U.S. Geological Survey. Relative relocations reduce the initial region of diffuse seismicity to a 50-km-long narrow band bounding the strike of surface manifestations and the zone of maximum surface deformation. We demonstrate the precision of surface-wave relocations over incremental time periods, capturing the progression of dyking from seismic onset through seismic migration and caldera subsidence. Results showcase the utility of surface-wave relocations in the characterization of dyking episodes and provide complementary insights into the current understanding of the Fentale–Dofen volcanic plumbing system.

Geophysical Journal International↗

USGS2025

Review: The hydrogeology of critical mineral resources relevant to the energy transition

Attaining the goals of the international treaty on climate change (the Paris Agreement) will greatly increase the demand for the critical minerals required to implement clean-energy technologies. This poses both challenges and opportunities to the hydrogeologic community from several perspectives. Here, important insights that the hydrogeological sciences have to offer for mineral exploration, mineral production, and addressing environmental issues related to mining and mine decommissioning are summarized. This study focuses on copper, cobalt, lithium, and rare earths to represent the broad spectrum of critical minerals and illustrate their relevance by referring to projected demands and production rates. The current understanding of the hydrogeologic processes that form major deposits of these minerals are then summarized. Ore is defined as the naturally occurring material from which minerals of economic value can be extracted, where most ore deposits are the products of complex hydrogeologic couplings between fluid flow, heat transport, solute transport, chemical reactions, and mechanical deformation. Exploration models for the discovery of deeper, hidden deposits are potentially informed by hydrogeologic theory and hydrogeochemical processes. Hydrogeologic understanding and methods are also essential to production and recovery. Longstanding challenges are mine dewatering and (conversely) mine water supply, as well as mineral-extraction practices such as spoil heap leaching and in situ mining. New challenges arise from element extraction from subsurface brines. Finally, the quantity of water use and potential environmental impacts of mining on water quality are at the core of ‘social license’: the approval and acceptance of society to mining activities.

Hydrogeology Journal↗

USGS2024

Near-real-time earthquake-induced fatality estimation using crowdsourced data and few-shot large-language models

When a damaging earthquake occurs, immediate information about casualties (e.g., fatalities and injuries) is critical for time-sensitive decision-making by emergency response and aid agencies in the first hours and days. Systems such as the Prompt Assessment of Global Earthquakes for Response (PAGER) by the U.S. Geological Survey (USGS) were developed to provide a forecast of such impacts within about 30 min of any significant earthquake globally. However, existing disaster-induced human loss estimation systems often rely on early casualty reports manually retrieved from global traditional media, which are labor-intensive, time-consuming, and have significant time latencies. Recent approaches use keyword matching and topic modeling to identify human casualty-relevant information from social media but tend to be error-prone when dealing with complex semantics in multi-lingual text data and parsing dynamically changing and conflicting human death and injury numbers shared by various unvetted sources in social media platforms. In this work, we introduce an end-to-end framework to significantly improve the timeliness and accuracy of global earthquake-induced human loss forecasting using multi-lingual, crowdsourced social media. Our framework integrates (i) a hierarchical casualty extraction model built upon large language models, prompt design, and few-shot learning to retrieve quantitative human loss claims from social media, (ii) a physical constraint-aware, dynamic-truth discovery model that discovers the truthful human loss from massive noisy and potentially conflicting human loss claims, and (iii) a Bayesian updating loss projection model that dynamically updates the final loss estimation using discovered truths. We test the framework in real-time on a series of global earthquake events in 2021 and 2022 and show that our framework effectively automates the retrieval of casualty information faster but with comparable accuracy to those now retrieved manually by the USGS. The code associated with this work is made available at: https://github.com/SusuXu-s-Lab/Hierarchical-Earthquake-Casualty-Information-Retrieval

International Journal of Disaster Risk Reduction↗

USGS2026

USGS 2025 critical minerals review

The United States Geological Survey (USGS) provides scientific information for the Department of Interior and the nation, consistent with its original mission expressed in the Organic Act of 1879 (43 U.S.C. 31): “the classification of the public lands and examination of the geological structure, mineral resources, and products within and outside the national domain.” Legislation such as the Energy Act of 2020 and the 2022 Infrastructure Investment and Jobs Act (43 USC 31l) and recent executive actions (Executive Orders 14154 , 14153, 14241 Secretary’s Orders 3417, 3418, 3422, 3436) underscore the importance of mineral resources and focus USGS activities on mapping and assessing mineral resources, with a particular focus on those presently identified as critical, both in ground and above ground in mine wastes. This article reviews selected activities and accomplishments by the USGS Mineral Resources Program related to critical minerals in 2025. Highlights include a new List of Critical Minerals, a first-ever national mine waste inventory, international minerals partnerships, mineral resource assessment advancements, and national data collection activities and outcomes of the Earth Mapping Resources Initiative (Earth MRI). The selected contributions are not comprehensive but are intended to demonstrate USGS leadership in critical mineral mapping and assessment, the importance of domestic and global partnerships, and the breadth of research activities that are responsive to national needs and priorities.

Mining Engineering↗

USGS2026

Rare earth element potential in coal and coal ash in the U.S. Gulf Coast

United States heavy reliance on imports of critical minerals (CMs), including rare earth elements (REEs), underscores the importance of development of domestic sources. The study objective was to quantify CM and REE concentrations in coal and coal ash in the US Gulf Coast region. CM and REE concentrations were measured for 118 samples from outcrops and 14 mines in the Gulf Coast. Results show that total REE + Yttrium (REY) concentrations (dry coal basis) are comparable to those of the upper continental crust (UCC) with localized hot spots, such as the Texas Gibbons Creek mine (REY ≤ ~ 2860 ppm). When normalized to UCC REY concentration (169 ppm, dry coal basis), REY to UCC ratios for Gulf Coast coal samples range from 0.1 to 17 (median ratio 0.6). REE extractability from lignites is high (median: 63%–93%) using environmentally benign weak acid. In addition to raw coal, coal ash from power plants could also serve as an REE source with a median ratio of REY in ash relative to coal of 4; however, extractability from coal ash is generally much lower (≤ 5% using the same weak acid as in coal). The median basket price for extracted REY as oxides from coal, assuming 70% extractability, is $3.2 per tonne of coal and $186 billion based on 58 billion metric tonnes of dry coal in the Gulf Coast. REEs important for magnets (Pr + Nd + Tb + Dy) account for ~ 80% of the total value. The corresponding median basket price for extracted REY as oxides from coal ash, assuming ~ 30% extractability, is ~$4.4 per tonne of ash and $1.2 billion based on 258 million tonnes of ash. REE production from coal would likely require co-products, such as activated carbon or humic acids, to attain economic viability. Production of REEs from coal ash could offset remediation costs related to potential water contamination. This reconnaissance study shows the potential for REE production from coal and coal ash in the Gulf Coast; however, carbon coproducts and/or societal benefits would likely be required for socioeconomic viability.

Alabama, Florida, Louisiana, Mississippi, Texas↗

USGS2024

Imaging of seismic discontinuities using an adjoint method

For imaging of seismic discontinuities at depth, reverse time migration (RTM) is a powerful method to apply to recordings of seismic events. It is especially powerful when an extensive receiver array, numerous seismic sources, or both, permit adequate reconstruction of incident and scattered wavefields at depth. Reconstructing either the incident or scattered wavefield at depth becomes less accurate when relatively few recordings of seismic events are available. Here we explore an inverse scattering approach to imaging discontinuities based on an adjoint method, employing sensitivity kernels (Frechet derivatives) that represent jumps in material properties across seismic-discontinuity surfaces. When combined with ray-based requirements on scattering geometry, it constitutes a powerful approach to determining the locations and amplitudes of the discontinuities, recovering only those properties that can be resolved by a spatially limited source and/or receiver distribution. This is illustrated by synthetic examples with local sources followed by a field example in a subduction zone setting

Washington↗

USGS2024

Deep syntectonic burial of the Anthracite belt, Eastern Pennsylvania

Fluid inclusion microthermometry and Raman spectroscopy of fluid inclusions in quartz veins from the Pennsylvanian rocks of the Anthracite belt, eastern Pennsylvania support a deep burial model of coalification in favor of focused orogenic hot fluid flow. High-temperature (250 to 255 °C) trapping of CH 4 ± CO 2 saturated aqueous fluids and CH 4 ± CO 2 inclusions indicate fluid trapping at depths of 11.5 to 13.4 km under a cover of Pennsylvanian to Permian(?) syntectonic load. In the folded rocks to the south of the Anthracite belt, CH 4 ± CO 2 fluid inclusions indicate a sediment load that was up to 16.3 km thick. Re -equilibrated aqueous fluid inclusions from veins in Silurian through Devonian rocks give the same range of trapping conditions but a wide range of fluid salinities suggesting that folding, fracturing, and meteoric recharge resulted in the intermixing of fluids from throughout the stratigraphic succession.

Pennsylvania↗

USGS2025

National population exposure and evacuation potential in the United States to earthquake-generated tsunami threats

Previous efforts to characterize tsunami threats to people have focused primarily on individual scenarios in specific areas but have not recognized multiple scenarios across an entire country. This study addresses this gap by quantifying population exposure and evacuation potential in the United States to 102 earthquake-related, tsunami-hazard zones, including 92 local scenarios, 8 distant scenarios, and 2 probabilistic products. Geospatial path-distance modeling quantified evacuation potential and the influence of departure delays. We focused on residents to support other national, multi-hazard risk analyses. Millions of residents are in distant-tsunami zones, and hundreds of thousands of residents are in local-tsunami zones. In 41 scenarios, there is at least one resident that may have insufficient time to evacuate before wave arrival. Tens of thousands of residents may have insufficient time to evacuate from local tsunamis that impact the U.S. Pacific Northwest or Puerto Rican coastlines. The largest improvements in evacuation potential may come from reducing departure delays in some areas but may involve vertical-evacuation structures or changing land use in other areas.

International Journal of Disaster Risk Reduction↗

USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗

USGS2026

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire↗