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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↗
USGS1998

Ground-water flow in the surficial aquifer system and potential movement of contaminants from selected waste-disposal sites at Cecil Field Naval Air Station, Jacksonville, Florida

As part of the Installation Restoration Program, Cecil Field Naval Air Station, Jacksonville, Florida, is considering remedialaction alternatives to control the possible movement of contaminants from sites that may discharge to the surface. This requires a quantifiable understanding of ground-water flow through the surficial aquifer system and how the system will respond to any future stresses. The geologic units of interest in the study area consist of sediments of Holocene to Miocene age that extend from land surface to the base of the Hawthorn Group. The hydrogeology within the study area was determined from gamma-ray and geologists' logs. Ground-water flow through the surficial aquifer system was simulated with a seven-layer, finite-difference model that extended vertically from the water table to the top of the Upper Floridan aquifer. Results from the calibrated model were based on a long-term recharge rate of 6 inches per year, which fell in the range of 4 to 10 inches per year, estimated using stream hydrograph separation methods. More than 80 percent of ground-water flow circulates within the surficial-sand aquifer, which indicates that most contaminant movement also can be expected to move through the surficial-sand aquifer alone. The surficial-sand aquifer is the uppermost unit of the surficial aquifer system. Particle-tracking results showed that the distances of most flow paths were 1,500 feet or less from a given site to its discharge point. For an assumed effective porosity of 20 percent, typical traveltimes are 40 years or less. At all of the sites investigated, particles released 10 feet below the water table had shorter traveltimes than those released 40 feet below the water table. Traveltimes from contaminated sites to their point of discharge ranged from 2 to 300 years. The contributing areas of the domestic supply wells are not very extensive. The shortest traveltimes for particles to reach the domestic supply wells from their respective contributing areas ranged from 70 to 200 years.

Florida↗
USGS2024

Cold blood in warming waters: Effects of air temperature, precipitation, and groundwater on Gulf Sturgeon thermal habitats in a changing climate

Objective In a changing climate, the effects of air temperature, precipitation, and groundwater on water temperature and thermal habitat suitability for Gulf Sturgeon Acipenser desotoi , listed as threatened under the U.S. Endangered Species Act, are not well understood. Hence, we incorporated these factors into thermal habitat models to forecast how Gulf Sturgeon may be affected by wide‐ranging climate change scenarios in 2024–2074. Methods Using data from the Choctawhatchee River, Florida, we developed precipitation‐ and groundwater‐corrected air–water temperature models, compared their accuracy with that of conventional air–water temperature models used in fisheries management, and projected future Gulf Sturgeon thermal habitat suitability for normal physiological functioning and fieldwork (i.e., population sampling and telemetry surgeries) in summer (May–August) under 16 climate change scenarios. Result Precipitation‐ and groundwater‐corrected models were more accurate than conventional air–water temperature models (mean improvement in adjusted R 2 = +0.45; range = +0.09 to +0.75). Water temperature was projected to warm at widely variable rates across climate change scenarios encompassing different air temperature, precipitation, and groundwater regimes. Importantly, Gulf Sturgeon summer aggregation areas were cooler and influenced more by precipitation and groundwater and less by air temperature than were non‐aggregation areas. If precipitation and groundwater—as drivers of cooling—become warm in a changing climate, summer aggregation areas were projected to exhibit thermal habitat degradation equivalent to or greater than that of non‐aggregation areas. Conclusion Our results add hydrological context to the premise that aggregation areas provide cool water and energetic savings for Gulf Sturgeon during summer, underscoring the importance of protecting these habitats through groundwater conservation, water quality monitoring, and riparian/watershed habitat management. Our findings indicate that identifying thermally appropriate times for fieldwork activities will be increasingly important and time‐restricted as climate change intensifies. However, our research provides managers with a portfolio of water temperature models and an accurate, cost‐effective, management‐relevant approach to forecasting thermal habitat conditions for Gulf Sturgeon and other species in a changing climate.

Alabama, Florida↗
USGS2024

A comparative analysis of OpenET for evaluating evapotranspiration in California almond orchards

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in soils, age, and variety. It also compares OpenET ensemble evapotranspiration (ET) data with applied irrigation and precipitation records over an additional 148 almond orchards located in the Central Valley of California. Results show OpenET models, including the ensemble ET value, produced reasonable and actionable ET values, with overall coefficient of determination (R 2 ) and mean absolute error values of 0.73- and 0.95-mm d −1 at the daily time step, respectively. However, given the temporal sampling of Landsat (8-day revisit) and the interpolation methods used, the assessed ET models had difficulty in capturing short-term variability in almond ET; for example, the rapid decline in measured ET observed as a response to lack of irrigation preceding and during almond harvest. The study also drew attention to the spatial complexity in scenarios where irrigated orchards are surrounded by hot/dry areas, causing discrepancies between measured and modeled ET values. In comparison with irrigation records, OpenET ensemble ET was capable of quantifying water input (applied irrigation + precipitation) in almond orchards to within 13 % when evaluating monthly data. Initial results presented here reinforce the idea that RSET models, such as in OpenET, are powerful tools, yet their application requires nuanced understanding and careful consideration of local conditions.

California↗
USGS2024

Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings

Accounting for uncertainties in seismic site response is crucial to improving the performance of one-dimensional (1D) ground response analyses (GRAs) at downhole array recording sites. In addition to site effects, uncertainties in 1D-GRAs can also be contributed from the seismic source and/or path. Though often representing not more than one percent of the distance (path) from the source, site conditions are known to have an enormous influence on ground shaking. In this study, we focus on the site shear-wave velocity ( V S ) structure, which is the main ingredient for estimating the variability of site response. As such, V S can manifest aleatory uncertainties related to the effects of small-scale spatial heterogeneities within the near surface, thus V S can substantially modify ground shaking during earthquakes. We apply a novel V S randomization approach to propagate the small-scale heterogeneities of V S to estimate seismic site response within a non-stationary probabilistic framework. The randomization approach generates samples of V S profiles that are used to perform several 1D-GRAs and obtain an averaged site response and related variability. The proposed method is implemented on data recorded at two downhole array sites with different subsurface soil conditions: a soft soil site on Treasure Island (California, United States of America) and a rock outcrop site in Cadarache (South-East France). We show that synthetic surface-to-borehole transfer functions from 1D-GRAs provide an acceptable fit to the empirical transfer functions from low-motion earthquake records and succeed in reproducing most of the site-specific seismic response variability. The remaining mismatch between transfer functions is likely due to insufficient precision on the seismic bedrock and the impedance contrast. The variability in site response is discussed with emphasis on the role of V S small-scale heterogeneities, attenuation, and input motion incidence angle in ground motion variability for the site and soil conditions at both locations.

California↗
USGS2025

Grammar to graph—An approach for semantic transformation of annotations to triples

Data annotation is the process of labeling data to show the outcome that a related data model should predict. In this study, annotation data were transformed into semantic graph triples, mainly for use with the Resource Description Framework (RDF), a type of entity-relationship-attribute data model for graph databases. The transformation of annotation data to semantic graph triples provides complex linguistic meaning with data handling advantages such as reduced data storage needs, improved logical specification of relations between objects, and reusable classes and properties that support logic and inference. A grammar-based framework in graph form supports user questions and queries. The words defining approximately 334 topographic feature types compiled by the U.S. Geological Survey were tokenized as units of analysis and grouped by part of speech. Their dependency relations were identified for this study using natural language processing libraries. Dependency concepts are used as structured semantic relations among part-of-speech classes. Tokens, units equivalent to words, form instances of classes and were quantified within a tabular output format using PostgreSQL data storage software. Table data were logically aligned as triples following a mapping file and stored with an ontology file using Ontop virtual triplestore software. A grammar ontology schema for the data was synchronized to match queries whose results validated the graph’s structure. The text analysis produced 8 part-of-speech classes of content words for object representations and 4 classes of function words for operational applications. Dependency relations formed 27 ontology properties for topographic subgraph structures. Token occurrences shaped overall ontology salience and formed a lexicon of syntactic terms for subgraph objects and properties. The schema ontology of class and property population shapes formed the lexicon of English terms. SPARQL Protocol and RDF Query Language (SPARQL) was used with the lexicon to conform data to RDF guidelines. This study confirms the hypothesis that although linguistic logic varies from description logic, its approximation applies to ontology design. Property and query use case patterns extracted from the analysis support queries concerning complex topographic relations and patterns normally embedded within text definitions. The method used in this study could be applied to text forms in other domains, such as survey notes.

Scientific Investigations Report↗
USGS2024

Influence of inherited structure on flexural extension in foreland basin systems: Evidence from the northern Arkoma basin and southern Ozark dome, USA

Extensional faults are key components of foreland basin systems. They form within the upper crust in response to flexure of the lithosphere and accommodate subsidence within the foredeep and forebulge depozones. Such faults are excellent proxies for orogenic system evolution and control the distribution of natural resources and hazards. However, the spatiotemporal evolution of flexural extension has not been documented previously at a regional scale, thereby limiting our understanding of underlying geodynamic controls. Here, we resolve late Paleozoic flexural extension in the northern Arkoma basin and southern Ozark dome, USA. We synthesize a large database of previous mapping, existing research, subsurface data, and geophysical data into 3D geologic and 2D kinematic models. Mesh surfaces representing several key horizons from the Carboniferous Period (ca. 335-306 Ma) were constructed. These surfaces were built from oil and gas well tops (n = ∼10,000) and surface geologic map contacts using an advanced kriging method. The mesh surfaces are offset by a complex 3D fault network, allowing detailed analysis of along-strike and down-dip variations in fault displacement. Analysis of the 3D model reveals a regular and repeated fault segmentation pattern wherein E -W striking, left- and foreland-stepping en échelon normal faults are segmented by inherited NE striking basement faults. Maximum vertical separation along the E -W normal faults is generally focused between the inherited NE-trending faults. This suggests that the inherited basement faults delocalized extensional strain during late Paleozoic normal faulting. Maximum vertical separation and fault localization may correlate to areas with high-amplitude positive magnetic anomalies interpreted as Mesoproterozoic granitic rocks. Speculative covariance of magnetic anomalies and fault displacements implies that the relatively strong basement granite concentrated stress, leading to localized faulting within the relatively thin sedimentary cover. Lastly, we show that flexural extension migrated southeast to northwest from the Chesterian-Morrowan (ca. 335-319 Ma) to the Desmoinesian (ca. 306 Ma). The migratory flexural extension may be explained by diachronous loading during Pangean assembly, or by synchronous loading but variable load compensation due to inherent factors.

Arkansas, Oklahoma↗
USGS2025

A geospatial analysis of water-quality threats from orphan wells in principal and secondary aquifers of the United States

Throughout the history of oil and gas production in the United States, millions of wells have been drilled for exploration and energy production. Hundreds of thousands of unplugged wells are no longer actively producing and are currently under orphan status, with no responsible party obligated for plugging. Orphan wells can pose threats to water resources by providing pathways for contaminants such as hydrocarbons and brines to migrate into water-supply aquifers. In this study, we investigate the potential threats to groundwater resources posed by orphan wells at the national scale. Water-quality data is extremely sparse in relation to orphan wells nationally and may not be suitable for identifying contamination from oil and gas development. We used geospatial and statistical methods to evaluate which principal and secondary aquifer systems may be most susceptible to contamination from orphan wells. Analysis involved three sets of susceptibility factors including: 1) factors related to the number and density of orphan wells; 2) factors that can threaten well integrity and contribute to transport of contaminants; and 3) factors related to groundwater withdrawal rates and the affected populations/communities in the event of water quality disturbances. From a dataset of 117,672 documented orphan wells, 64,203 fall within a principal aquifer system, while the remainder fall within a secondary aquifer system. By assessing the combination of well integrity and hydrogeologic factors within these aquifer systems, five groupings of principal aquifers were identified, where groups ranged from aquifer systems with high numbers of orphan wells, multiple well integrity threats and high withdrawals, to aquifers with a relatively low number of orphan wells, limited well integrity threats and minimal water use. Three regions of the country emerge containing aquifers with higher susceptibility to contamination from orphan oil and gas wells. These regions include 1) The Appalachian Basin (including the Pennsylvanian Aquifer System), 2) The Gulf Coast Aquifers (including the Coastal Lowlands Aquifer system) and 3) The California Aquifers (including the California Coastal Basin Aquifer system). This work is the first multivariate geospatial investigation of orphan wells and groundwater resources on a national scale, and sheds light on which aquifers are most susceptible to groundwater contamination from orphan wells.

Science of the Total Environment↗
USGS2024

The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 ( m / z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r 2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r 2 = 0.93), praseodymium (Pr) (r 2 = 0.94) and samarium (Sm) (r 2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Journal of Geochemical Exploration↗
USGS2024

Framework for implementing damping scaling factors in U.S. Geological Survey National Seismic Hazard Models

Traditionally, probabilistic seismic hazard analysis (PSHA) has focused on calculating ground motion hazard curves for elastic, 5%-damped pseudo spectral accelerations, Sa(T,5%), which are used as the basis for engineering design parameters and targets for ground motion selection and modification. However, structures and geotechnical systems can exhibit a wide range of damping ratios both above and below the 5% level, depending on the construction material, structural system, nonstructural elements, or subsurface soil properties. When spectral parameters at such damping levels are required for certain applications, 5%-damped accelerations have traditionally been extracted from PSHA-based hazard curves and adjusted outside of the hazard integral using damping scaling factors (DSF) such as those from Newmark & Hall (1982). Recent advances in the development of more rigorous and comprehensive damping scaling models (e.g., Rezaeian et al., 2014; Rezaeian et al., 2021) have allowed for the modeling of means and standard deviations of DSFs as functions of earthquake source and path properties for crustal, intraslab, and subduction interface tectonic environments. These DSF models can be applied to ground motion model (GMM) estimates of Sa(T,5%) for a given earthquake rupture scenario to produce a corresponding mean and standard deviation Sa at a specified damping ratio β, Sa(T,β). In this study, the DSF models of Rezaeian et al. (2014) and Rezaeian et al. (2021) are implemented within the U.S. Geological Survey National Seismic Hazard Model (NSHM) PSHA framework to calculate probabilistic hazard curves for spectral accelerations at damping ratios from 0.5% to 30%. The DSF models are applied directly to the mean and standard deviation of Sa(T,5%) predictions from each GMM in the NSHM logic tree. Resulting hazard curves and uniform hazard and risk spectra for Sa(T,β) are presented for several geographic locations and compared with corresponding spectra estimated using current design practices by applying the same DSFs outside of the PSHA calculation. Key differences between the two methods for estimating Sa(T,β) are discussed, and potential strategies are presented for the implementation and usage of the hazard-consistent Sa(T,β) in building codes. Comparing the results to those from DSFs used in current design practices that are mainly based on Newmark & Hall (1982) is not explored in this study.

Conference Paper↗
USGS2026

Regional characterization of coal resources in the Gulf Coast Coal Region—In support of coal as a potential source for critical minerals and rare earth elements

There is increasing interest in extracting critical minerals (CM), including rare earth elements (REE), from coals in the United States to address the overreliance on imported REE. The Gulf Coast and the Fort Union regions are the two major lignite-bearing regions within the United States. Recent REE and CM studies of the lignite in these regions have indicated that the coals may be a viable source material for REE and CM extraction. To evaluate in-place coal as a potential source of REE and CM, the coal resources need to be quantified. This study presents the results of a regional analysis of Gulf Coast Coal Region lignite and bituminous coal resources that might be available as potential sources of REE and CM. The resource analysis used kriging methods to develop isopleth maps of cumulative coal thickness throughout the region using data from drill holes and measured mine and outcrop sections for a total of 31,181 data points. The estimated total remaining coal resource in the Gulf Coast Coal Region is about 83 billion metric tons in the upper 90 meters (approximately 300 feet) of the subsurface. The current estimate of remaining coal resources includes approximately 1.88 billion metric tons of coal that have been extracted in the region since 1983. Texas accounted for 39 percent (32 billion metric tons) of the remaining total resource, followed by Mississippi (24 percent, 20 billion metric tons ), Louisiana (14 percent, 12 billion metric tons), Tennessee (10 percent, 8.5 billion metric tons), and Arkansas (6 percent, 5.1 billion metric tons). Alabama, Georgia, Kentucky, and Missouri each accounted for less than 5 percent of the total resource; Georgia had the smallest resource estimated at 7 million metric tons. Here we report the first known statewide lignite resource estimates for Georgia, Kentucky (820 million metric tons), and Missouri (1,800 million metric tons). A comparison of the results of this study with those of previous Gulf Coast Coal Region and Fort Union Coal Region resource studies is difficult because each study used different data sources, assessment methodologies, overburden depths, and qualifying coal thicknesses.

Alabama, Arkansas, Florida, Georgia, Illinois, Lou↗
USGS2026

2025 USGS National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands: Overview of model and hazard results

The U.S. Geological Survey recently updated the National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The first version of the PRVI NSHM was released in 2003, and therefore this 2025 update includes over 20 years of new geologic, geophysical, and engineering data, methods, and models. Updates follow similar efforts performed in the recent 2023 50-state NSHM. However, this is the first NSHM in which we: (1) apply an inversion methodology to subduction interface fault sources in the earthquake rupture forecast (ERF) model; (2) develop scaled backbone median ground-motion models and independent aleatory variability models that are applied in the ground-motion characterization (GMC) model; and (3) calculate epistemic uncertainty related to alternative scenarios in the ERF and GMC models for all grid points in the study region. Long-term time-independent mean hazard calculations were performed for peak ground acceleration and 5%-damped pseudospectral acceleration at 21 spectral periods from 0.01- to 10.0-s, for eight National Earthquake Hazards Reduction Program site conditions ranging from V S30 = 150 to 1500 m/s, and for 2%, 5%, and 10% in 50-year probabilities of exceedance (return periods of 2475, 975, and 475 years, respectively). Epistemic uncertainty, in the form of selected percentiles, is also provided for a suite of test sites and all grid points in the study region for limited periods, site conditions, and probabilities of exceedance. Selected results, including comparisons with the 2003 PRVI NSHM, are shown and discussed for selected periods, site conditions, and probabilities of exceedance. When comparing the 2025 PRVI NSHM with the 2003 PRVI NSHM, hazard is generally higher at shorter periods and lower at longer periods, as a result of updates in both ERF and GMC models. The 2025 PRVI NSHM is applicable for return periods greater than ∼475 or less than ∼10,000 years.

Puerto Rico, U.S. Virgin Islands↗
USGS2024

Estimating groundwater level records using MOVE.1 and computing monthly percentiles from estimated groundwater records in Massachusetts

The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, performed record extensions on groundwater levels at select wells using the Maintenance of Variance Extension type 1 (MOVE.1) method. The groundwater levels estimated from these record extensions were used to compute monthly percentiles to improve future determinations of a groundwater index. In Massachusetts, 27 of 29 short-record study wells with continuous groundwater levels between 0.8 and 8.1 years were suitable for record extensions; 37 long-record index wells were used to extend the groundwater level records at the study wells. The index well selected to pair with a study well was chosen based on Pearson correlation coefficient values; cross-correlation between the two wells; geologic and topographic similarity; and smallest distance spanning the wells. Each study well and its corresponding index well have 1 or more years of concurrent, overlapping data; a Pearson correlation coefficient that exceeded a threshold value of 0.8; and a similar aquifer type and hydrologic characteristics. Of the 29 study wells, 2 showed poor correlations with all index wells and were not considered for record extensions. Performance metrics used to assess the accuracy of the MOVE.1 models indicated that most models provided reasonable estimates of groundwater levels. Root mean square error values ranged from 0.097 to 2.292 feet, with a median of 0.536 foot. Nash-Sutcliffe efficiency coefficient values ranged from 0.623 to 0.996, with a median value of 0.759. Generally, study wells in close geographical proximity to their index well resulted in stronger model performance. The average length of groundwater level records was extended by 14.1 years to a new average of 18.1 years. The estimated groundwater level records from the MOVE.1 models resulted in an increase in the range of highest and lowest groundwater levels at 23 of 27 wells. The increase in range of groundwater levels was between 0.08 to 7.95 feet. Monthly percentiles for State drought indices were computed from the estimated MOVE.1 records and observed records through December 31, 2021. Percentiles computed from estimated records show an average groundwater level about 1.0 foot lower than observed data at the 2d percentile and 0.1 foot lower at the 30th percentile.

Massachusetts↗
USGS2025

Protected from Pterygoplichthys? Predicting thermal habitat suitability for nonnative armored catfish in the Suwannee River

Objective Nonnative fishes can modify ecosystems and harm economies when they are introduced to new environments. Climate change is likely to assist the spread and establishment of some nonnative fishes (e.g., warmwater species), but spatiotemporal gaps in water temperature monitoring and modeling may prevent ecologists and managers from forecasting thermal habitat suitability for these taxa. The purpose of this study was to develop a predictive model of winter water temperatures and thermal habitat suitability for two priority nonnative armored catfish, Vermiculated Sailfin Catfish Pterygoplichthys disjunctivus and Orinoco Sailfin Catfish P. multiradiatus , in the Suwannee River, Florida and Georgia. Methods Precipitation- and groundwater-corrected air–water temperature models were developed and evaluated using a model selection procedure to predict water temperatures at four sites in the Suwannee River. These models were chosen because they blend the simplicity of air–water temperature models with the accuracy of hydrometeorological models to create an efficient, economical, management-relevant approach for analyzing and forecasting water temperature. Results Most of the top-performing water temperature models (92%) had precipitation or groundwater corrections to air–water temperature formulations. Projected mean and maximum water temperatures increased as simulated climate change intensified. All four Suwannee River sites studied were projected to be thermally hospitable to the survival of Vermiculated Sailfin Catfish. Lower river sites, noticeably warmer than upper river sites, were conducive to the survival of Orinoco Sailfin Catfish throughout the winter months. The upper river sites were too cold for Orinoco Sailfin Catfish survival in some climate-change scenarios, but the Suwannee River has an abundance of constant-temperature springs that are likely hospitable to Vermiculated Sailfin Catfish and Orinoco Sailfin Catfish throughout the year. Conclusions The findings suggest that winter water temperatures will likely not be a barrier to the survival of Pterygoplichthys catfish in the Suwannee River, amplifying the importance of conservation and management approaches to inhibit their spread and establishment. If the Pterygoplichthys population remains small and isolated and decision makers are able to devote required staff time and resources to managing these species, removal and eradication at local if not broader scales may be reasonable goals. This study provides a water temperature modeling approach that can aid ecologists and managers in prioritizing sites to prevent the introduction, slow the dispersal, eradicate, and control Pterygoplichthys catfish and other nonnative fishes in the Suwannee River and beyond.

Florida, Georgia↗
USGS2025

Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity

Since the vast majority of carbon dioxide (CO 2 ) storage resources in the United States are in deep saline aquifers, optimizing the use of these saline storage resources could be crucial for efficient development of geologic CO 2 storage (GCS) resources and basin- or larger-scale deployment of GCS in the country. Maximum CO 2 injection rates can be enhanced by extracting brine from the CO 2 storage unit. However, disposal of the extracted brine is both a technological and economic challenge. The lowest-cost option would likely be reinjection of the extracted brine into another formation above or below the CO 2 storage unit. Therefore, it is important to estimate brine injectivity as it will constrain the potential to increase CO 2 injectivity at an injection site that has access to multiple geologic storage units where either CO 2 or brine can be injected. Using a simulation-optimization framework, coupled with a non-isothermal, multiphase CO 2 -water-salt equation-of-state module, we developed a computationally efficient method for evaluating optimization of simultaneous CO 2 injection, brine extraction, and brine (re)injection at hypothetical injection sites deployed across a geologic basin. The Illinois basin is ideal for testing our methodology because it contains multiple geologic storage units with seals in between them to isolate injection of CO 2 in one unit from interfering with the injection of either brine or CO 2 in another unit above or below it. In addition, we investigated the relative effects of variation in key geologic parameters as well as two reservoir structures (hydrogeologic heterogeneity/anisotropy and homogeneity/isotropy) on CO 2 injectivities and enhancement of CO 2 injectivity through extracting brine. Results suggest that permeability, depth, and especially thickness of the storage unit could be the most influential parameters determining CO 2 injectivity. They also suggest that only injecting CO 2 into the storage unit with the greatest injectivity, enhancing that unit’s injectivity by extracting brine, and disposing of the produced brine in other suitable units could maximize total CO 2 injectivity in limited regions of the basin. At the majority of simulated injection sites, however, we found that injecting CO 2 into all of the accessible and suitable storage units was more likely to maximize the CO 2 storage resource.

Illinois, Kentucky, Indiana↗
USGS1997

Nutrients and pesticides in ground water of the Ozark Plateaus in Arkansas, Kansas, Missouri, and Oklahoma

A total of 229 ground-water samples were collected from 215 sites as part of the Ozark Plateaus study unit of the National Water-Quality Assessment Program. These samples were collected from 1993 through 1995 using a network of springs and wells with three scale-dependent components. The first component, the study-unit survey, consisted of 99 randomly selected springs and domestic wells in the Springfield Plateau and Ozark aquifers. The second component, two land-use studies, consisted of 42 springs and domestic wells in a poultry-dominated agricultural area and 40 springs and domestic wells in a cattle-dominated agricultural area overlying the Springfield Plateau aquifer. The third component, the small-watershed study, consisted of 4 springs, 18 domestic wells, and 11 monitoring wells in a small basin within the poultry land-use study area. Samples were analyzed for major ions, nutrients, dissolved organic carbon, methylene blue active substances, tritium, and 88 pesticides and metabolites.The water-quality data from these samples were analyzed with descriptive and statistical methods. Nitrite plus nitrate, which was detected more often and in greater concentrations than any of the other nutrients, ranged from less than 0.05 to 25 milligrams per liter as nitrogen. Nitrite plus nitrate concentrations positively correlated to percent agricultural land use around each site. Median nitrite plus nitrate concentrations generally were greater in samples from springs than in samples from wells. Concentrations of nitrite, ammonia, and ammonia plus organic nitrogen were also affected by land use and also by concentrations of dissolved oxygen in the ground water. Concentrations of phosphorus and orthophosphate probably were affected by land use and also by phosphorus solubility. Pesticides were detected in 80 of 229 samples from 73 of 215 sites. A total of 20 pesticides were detected with a maximum of 5 pesticides detected in any 1 sample. The most commonly detected pesticides were tebuthiuron, atrazine, prometon, desethylatrazine, and simazine. Maximum concentrations ranged from 0.003 to 1.0 microgram per liter. The occurrence and distribution of pesticides were related to land use. Percent agricultural land use was greater for samples with pesticides detected than for samples with no pesticides detected. Pesticides were detected more often in samples from springs than in samples from wells. The occurrence of pesticides also was related to seasonality and chemical characteristics, such as solubility and persistence, of the compounds.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2025

Spatio-temporal evolution of distributed volcanic fields, case studies—Sierra Chichinautzin and Michoacán-Guanajuato, México

An analysis of 1,375 volcanoes in the Michoacán-Guanajuato (1,148 volcanoes in a 26,200 square-kilometer area) and Sierra Chichinautzin (227 volcanoes in a 3,500 square-kilometer area) volcanic fields in central Mexico identified patterns in the spatial and temporal distribution of past eruptions. A cluster agglomerative hierarchical method and kernel analysis confirmed that the Michoacán-Guanajuato volcanic field comprises four volcanic fields (Valle de Santiago, Uruapan, Apatzingán, and Pátzcuaro volcanic fields) controlled by different fault systems, indicating that it is not a single volcanic field but rather a group of volcanic fields (a “superfield”), each of which has distinct characteristics. In the Sierra Chichinautzin volcanic field, well-constrained isotopic ages were used to build a model of how the spatial distribution of the eruptions has changed over time. Two new 40Ar/39Ar ages from a locally recognized volcanic feature near the town of El Cantil, herein called El Cantil volcano (1,537±17 kilo-annum [ka]) and the volcanic feature at Cerro el Elefante (herein called El Elefante dome) (1,485±92 ka) belong to the oldest volcanic group identified in the Sierra Chichinautzin volcanic field, confirming the timing of the beginning of monogenetic volcanism in the region. Based on the volcanic groups identified in the Sierra Chichinautzin volcanic field, the youngest volcanism (less than 35 ka) is found only in the central-western sector of the field. Principal component analysis determined the directional trends of feeder dikes only for vents <10 ka in the Sierra Chichinautzin volcanic field. Possible magma migration paths through the crust were identified using seismic data from both volcanic fields using an earthquake catalog from 1973 to 2023, which includes 9,016 earthquakes in the Michoacán-Guanajuato volcanic field and 841 in the Sierra Chichinautzin volcanic field. The spatial distribution of the hypocenters does not highlight any trend that could be associated with superficial movement of magma in the Sierra Chichinautzin volcanic field. In the Michoacán-Guanajuato volcanic field, however, eight seismic swarms since 1997 have been detected. These swarms are interpreted to result from ascending magma. Strengthening monitoring systems and reinforcing mitigation measures to address volcanic hazards and risk are important means of preparing for future eruptions in both regions. Analysis such as those herein provide insights as to where an eruption might occur and may help mitigate volcanic hazards.

Michoacán-Guanajuato, Sierra Chichinautzin↗
USGS2025

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

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

Arctic↗