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1,660 records · Page 70Linked to original sources
USGS2026

Ground-motion characterization for the 2025 U.S. National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands

We develop the ground-motion characterization (GMC) for the 2025 U.S. National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands (NSHM-PRVI) for earthquakes in active crustal, subduction interface, and subduction intraslab regimes. Using ground-motion models (GMMs) from the Next-Generation Attenuation (NGA)-West2 and NGA-Subduction projects, the GMC is parameterized by scaled-backbone models for median ground motions and by independent logic trees of aleatory variability. We introduce several novel GMC features into the U.S. NSHM: (1) use of regional ground-motion data for modeling median ground motions; (2) development of scaled-backbone models for median ground motions; and (3) development of independent logic trees of aleatory variability from variance components of GMMs and computed from multiple ground-motion datasets, and incorporating regional ground-motion data effects on variability. We compute probabilistic seismic hazard curves and maps to evaluate the contributions from the GMC components and for comparison with the 2003 GMC. Contributions of the GMC to epistemic uncertainty in seismic hazard are evaluated through spatial variations in epistemic uncertainty in hazard maps, comparisons between mean hazard curves and fractiles, as well as investigations of the contributions of logic-tree branches to hazard maps and curves. Comparisons between seismic hazard from the 2025 and 2003 GMCs allow examination of the changes in hazard curves and mapped values with 2% and 10% probabilities of exceedance in 50 years. The 2025 GMC exhibits modest changes in median predictions, relative to the 2003 GMC; overall, values of aleatory variability are higher, except at long periods ( ), resulting in changes to probabilistic ground motions at low probabilities of exceedance (<10% probability of exceedance in 50 years). Changes in hazard at 2% and 10% probabilities of exceedance in 50 years are also relatively modest (within 20%) at most sites, with the impacts from the 2025 GMC exhibiting minor reductions and increases at 0.2 and 1.0 s periods, respectively, relative to the 2003 GMC.

Puerto Rico, U.S. Virgin Islands↗
USGS2026

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗
USGS2025

Water use across the conterminous United States, water years 2010–20

Withdrawals of water for human use are fundamental to the evaluation of the Nation’s water availability. This chapter provides an analysis of public supply, crop irrigation, and thermoelectric power water use for the conterminous United States (CONUS) during water years 2010–20. These three categories account for about 90 percent of water withdrawals in the Nation. The values presented here are based on modeling approaches that estimate water use at temporal (monthly) and spatial scales (12-digit hydrologic unit code—small watersheds sized 50–100 square kilometers) compatible for integration into a broader national assessment of water availability. Models also provide an understanding of factors that influence water use. An estimated 244,817 million gallons per day (Mgal/d; 28,677 million cubic meters per month [Mm 3 /mo]) were withdrawn on average within the CONUS during water years 2010–20 from fresh water and saline water for crop irrigation, public supply, and thermoelectric power, with shares of 43, 14.5, and 42.5 percent for each of these categories, respectively. In the same period, estimated withdrawals and consumptive use (1) for public supply were 35,400 and 4,219 Mgal/d (4,081 and 486 Mm 3 /mo), respectively; (2) for crop irrigation were 105,497 and 75,698 Mgal/d (12,147 and 8,716 Mm 3 /mo), respectively; and (3) for thermoelectric power from fresh water were 82,656 and 2,904 Mgal/d (9,952 and 345 Mm 3 /mo), respectively. Withdrawals for these categories of water use are highly spatially variable, with western States dominated by crop irrigation and eastern States dominated by thermoelectric-power water use. Public supply accounts for the largest percentage of water use in several heavily populated northeastern States. Reliance on groundwater compared to surface water depends on the availability of water sources and the type of water use. For public supply, withdrawals from groundwater are greater than withdrawals from surface water in the Western aggregated hydrologic regions, whereas the balance shifts to more surface water for the rest of the CONUS. In all aggregated hydrologic regions, the predominant source of water for crop irrigation is groundwater. Most thermoelectric power facilities in the eastern half of the CONUS use surface water from freshwater and saline sources; most thermoelectric power facilities in the western half of the CONUS use groundwater.

conterminous United States↗
USGS2026

Ungulate migrations of the Western United States, volume 6

This report, volume 6 in the “Ungulate Migrations of the Western United States” report series, showcases the migrations of 23 ungulate herds in the Western United States. The report series is produced by the Corridor Mapping Team (CMT). Led by the U.S. Geological Survey, the CMT is a collaboration among 11 State agencies, as well as regional and Federal partners, and an expanding number of Tribal wildlife agencies. The CMT was initiated in response to the U.S. Department of the Interior Secretarial Order 3362, which was signed in 2018 and provided Federal support to expand existing research efforts to study ungulate populations and conserve their migrations throughout the Western United States. Including this volume, the report series has detailed the migrations of 237 unique ungulate herds throughout the Western United States and continues to serve as a valuable resource to guide local and regional management, policy, and on-the-ground work necessary to maintain intact and functional ungulate migrations. This report highlights several guiding principles of the CMT that facilitate collaboration among the diverse set of partners and contribute to the program’s continued successes. Notably, raw global positioning system data are not shared among participating agencies and the U.S. Geological Survey, delineating migration corridors and seasonal ranges relies on empirical data, the CMT provides flexible approaches to participating State and Tribal partners, and regular CMT meetings create a framework for open communication among agency partners that supports transboundary mapping of migrations. The 237 ungulate migrations that have been included in the report series are an expanding inventory, which can help maintain ungulate migrations in perpetuity.

Arizona, California, Colorado, Idaho, Montana, Nev↗
USGS2025

Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070

In 2019, the U.S. Geological Survey and Wake County Environmental Services began a collaborative study to evaluate groundwater resources and long-term groundwater availability in the county’s fractured-rock groundwater system. Wake County, in central North Carolina, is experiencing rapid population growth, associated land development, and changing water use. Hydrogeologic data including groundwater levels, aquifer testing, borehole fracture flow measurements, water-quality samples, and groundwater age-dating tracers were collected, along with findings from previous investigations, to help inform a conceptual model of the flow system used to develop a modular three-dimensional finite-difference groundwater-flow model (MODFLOW) for simulating historical and future groundwater conditions from 2000 to 2070. Hydraulic conductivity and transmissivity ranges were estimated from 17 slug tests and 21 borehole-flow measurements. Groundwater-quality analytical results from 19 sampling sites indicate that oxidation-reduction (redox) conditions varied within the regolith and bedrock and that minimal evaporation occurred before recharge entered the groundwater system. Age dating revealed mixtures of older and younger water, ranging from the 1940s to the 1990s—indicating variable flow pathways of recharge within permeable bedrock fracture zones. To simplify the complex fractured-rock groundwater system, two layers representing the regolith and the fractured bedrock were used in the MODFLOW model. Model calibration included parameter estimation and provided a reasonable fit to observed groundwater levels and estimated stream base flows. The model forecast scenarios incorporated future climate-model data for two emissions scenarios with land cover change projections to simulate potential impacts to future groundwater levels, recharge, and base flows. Recharge and base flow projections were largely within historical ranges, with no apparent long-term trends, but did indicate a slight downward shift in median values—likely, in part, because of differences in spatial resolution of input climate datasets. Seasonal patterns were consistent with historical data, with projections of possible increases in future winter recharge. Model limitations are discussed, and additional monitoring and model refinement needs are highlighted to support decision making for local groundwater management.

North Carolina↗
USGS2025

Evidence for nonlocal sediment transport on hillslopes from fault scarp morphology

Hillslope sediment transport processes such as bioturbation, rainsplash, and granular mechanics occur across the entire planet. Yet, it remains uncertain how these small-scale processes act together to shape landscapes. Longstanding hillslope diffusion theory posits that hillslope processes are spatially limited, whereas new concepts of nonlocal sediment transport argue otherwise. However, each theory produces subtly different, but distinct, predictions for the evolution of fault scarps. We use the topographic change of fault scarps to demonstrate that hillslope processes produce nonlocal sediment transport. Analysis of a global compilation of 340 dated single-earthquake scarp profiles reveals a statistically significant ( p < 0.05 ) relationship between scarp age and scarp asymmetry, here defined as the ratio of imaginary to real components of the Fourier transform of absolute slope. Numerical simulations show that nonlocal models predict this relationship, whereas hillslope diffusion models do not. To further investigate this result, we examined the depositional geometry of a well-exposed colluvial wedge along the Wasatch fault in central Utah, United States. Our quantitative comparison between the exposure and numerical simulations reveals better agreement with the nonlocal model. Nonlocal sediment transport theory appears to best capture the physics of how hillslope processes shape fault scarps, yet hillslope diffusion provides a useful approximation in many cases. As the processes that act on fault scarps are nearly identical to those acting on hillslopes, our results provide evidence supporting nonlocality as a generalized model of hillslope sediment transport.

Utah↗
USGS2024

3-D geological modeling for numerical flow simulation studies of gas hydrate reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. This study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-step gridding were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a 3-D trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

Alaska↗
USGS2024

Examining 22 years of ambient seismic wavefield at Mount St. Helens

An increase in seismic activity precedes most volcanic eruptions. Whereas event-based forecasting approaches have been successful, some eruptions remain unanticipated, resulting in casualties and damage. Our study leverages the recent advancements in ambient field seismology. We explore features extracted from continuous ambient fields using traditional methods, for example, peak ground velocity, peak ground acceleration, root mean square, root median square, real-time seismic amplitude measurement, and novel methods (displacement seismic amplitude ratio and spectral width). In addition, we explore unsupervised learning of higher order wavelet features using scattering networks. We find that combining all the methods was necessary to disentangle the effects of seismic sources from structural changes at Mount St. Helens. Although the ambient wavefield-based approach does not yield additional or more significant precursory signals than event-based methods at Mount St. Helens, our study demonstrates that the ambient wavefield provides supplementary information, mainly about structural changes and complements traditional methods. The ambient seismic wavefield offers additional insights into long-lasting processes. We find enhanced wave attenuation correlating with geochemical measurements. We interpret this as ongoing structural changes, such as dome growth or the evolution of the volcanic conduit system. On annual and decadal timescales, we interpret seasonal seismic attenuation in the shallow subsurface as groundwater fluctuations, corroborated by observations at the nearby Spirit Lake level. This multimethod approach at Mount St. Helens sheds light on a volcanic system’s underlying dynamics and structure.

Washington↗
USGS2025

A spatial analysis of the groundwater emergence flood hazard in Long Island, New York and near coastal areas surrounding Long Island Sound in New York, Connecticut, and Rhode Island

Long Island, New York and near coastal areas surrounding Long Island Sound are densely populated and, like other coastal areas, are susceptible to flooding from several potential sources, including stormwater from precipitation events, tidal flooding and storm surge, and groundwater inundation or groundwater emergence flooding. The latter refers to the intersection of a rising water table with land surface or critical infrastructure. Many studies of flood drivers either neglect or only briefly discuss how shallow groundwater conditions may contribute to or exacerbate flood conditions. As part of a comprehensive study of compound flood hazards in the near coastal areas surrounding Long Island and Long Island Sound, a spatial analysis was completed, in cooperation with the Environmental Protection Agency’s Long Island Sound Study, using available regional datasets to characterize the potential hazard for groundwater emergence flooding. The approximately 3,100 square mile study area was subdivided into 11,407 900-meter by 900-meter (approximately 3,000-feet by 3,000-feet) grid cells, for the purposes of integrating the spatial datasets to calculate and map the groundwater emergence flood hazard. The depth to the water table, hydrologic soil groups, and National Land Cover Database were harmonized to the common grid. A groundwater emergence flood hazard rank was calculated for each grid cell for current average conditions following a set of rules accounting for the depth to the water table and the percent of area within each cell with slow infiltrating soils. A higher sea level position scenario was also calculated for the Long Island part of the study area. The calculated groundwater emergence flood hazard rank was reviewed in concert with the National Land Cover Data Base to identify developed areas and associated infrastructure that may be at risk to groundwater emergence flooding. Study results indicate that the groundwater emergence flood hazard is highest in coastal areas and near surface water where the water table is close to ground surface. Inland areas away from surface water bodies are not likely to be exposed to groundwater emergence flooding. For Long Island, under a scenario with higher sea level position, a greater groundwater emergence flood hazard is calculated in some locations closer to the coast and where land is submerged. Away from the coast and surface-water drainage, the groundwater emergence flood hazard is similar between the current average sea level condition and a higher sea level position scenario.

EarthArXiv↗
USGS2025

Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses

Seawater intrusion threatens groundwater resources in coastal regions, including southern Baldwin County, Alabama, where the freshwater-saltwater interface dynamics remain poorly understood. To address this gap, this study uses combined physics-based and machine-learning models to quantify seawater intrusion caused by natural (storm surges) and anthropogenic (human activities) perturbations. The long short-term memory network and wavelet analysis were used to assess vertical aquifer vulnerabilities, revealing that the shallow part of the Coastal lowlands aquifer system (CL1) in the southern Baldwin County region is more susceptible to sea level rise and groundwater extraction than deeper aquifers. Based on these findings, a cross-sectional numerical model (physics approach) for the CL1 aquifer was developed to evaluate tidal and storm surge effects, using Tropical Storm Claudette (June 2021) as a case study. Results showed that tidal fluctuations had a minimal impact on the saltwater-freshwater interface location, whereas storm surges caused substantial inland movement, with effects lasting for nine months. The steady-state version of the three-dimensional (3D) physical model predicted seawater intrusion across the entire area, and convolutional neural network-based modeling further validated the model results. The 3D physical model was also applied to a smaller area to assess human impact on the saltwater interface due to two groundwater pumping scenarios (± 50% of the baseline pumping rate). Results revealed that a 50% increase in groundwater withdrawals caused seawater to advance ~ 320 m inland, whereas a 50% reduction led to a ~ 270-meter retreat. This study highlights the vulnerability of Alabama’s shallow coastal aquifers to seawater intrusion due to storm surges and human activities, and demonstrates that combining physics-based models with machine learning approaches can improve groundwater predictions, though its accuracy depends on the availability of site-specific data.

Alabama↗
USGS2025

Speleothem evidence for Late Miocene extreme Arctic amplification – An analogue for near-future anthropogenic climate change?

The Miocene provides an excellent climatic analogue for near-future runaway anthropogenic warming, with atmospheric CO 2 concentrations and global average temperatures similar to those projected for the coming century under extreme-emissions scenarios. However, the magnitude of Miocene Arctic warming remains unclear due to the scarcity of reliable proxy data. Here we use stable oxygen isotope and trace element analyses, alongside clumped isotope and fluid inclusion palaeothermometry of speleothems to reconstruct palaeo-environmental conditions near the Siberian Arctic coast during the Tortonian (8.68 ± 0.09 Ma ). Stable oxygen isotope records suggest warmer-than-present temperatures. This is supported by temperature estimates based on clumped isotopes and fluid inclusions giving mean annual air temperatures between + 6.6 and + 11.1 °C , compared with − 12.3 °C today. Trace elements records reveal a highly seasonal hydrological environment. Our estimate of > 18 °C of Arctic warming supports the wider consensus of a warmer-than-present Miocene and provides a rare palaeo-analogue for future Arctic amplification under high-emissions scenarios. The reconstructed increase in mean surface temperature far exceeds temperatures projected in fully coupled global climate models, even under extreme-emissions scenarios. Given that climate models have consistently underestimated the extent of recent Arctic amplification, our proxy data suggest Arctic warming may exceed current projections.

Lena River delta↗
USGS2026

Suitability of ground-motion models for seismic hazard assessment in Puerto Rico and the U.S. Virgin Islands

We perform linear mixed-effects analyses with a ground-motion dataset to evaluate how well ground-motion models (GMMs) fit active crustal, subduction interface, and subduction intraslab earthquakes in Puerto Rico and the US Virgin Islands. Most of the GMMs reproduce the spatial variation in peak ground motions with earthquake magnitude and rupture distance but predict ground motions 0.3–1.0 natural log units (35%–270%) greater than observations. Two GMMs developed for Puerto Rico that are based on ground-motion records from mostly magnitude 4–5 earthquakes do not perform as well. We attribute the period-dependent overprediction in observed ground motions to differences between the observed site response and the linear site response in the GMMs. Consequently, we developed region-specific GMMs by adjusting the period-dependent linear site response coefficients and period-dependent constant coefficients to remove most of the bias between predicted ground motions and observations. For the analysis, we compile ground-motion records and process waveforms to build a dataset with 10,127 records at 72 stations from 849 magnitude 4.0–6.4 earthquakes between 1 January 2006 and 31 March 2024. The earthquakes include active crustal, subduction interface, and subduction intraslab events. We evaluate the GMMs using the time-averaged shear wave speed in the top 30 m ( ), which we compile from site surveys and proxy values computed from horizontal to vertical spectral ratios. Site terms exhibit strong consistency across GMMs and crustal and subduction earthquakes, indicating that the linear mixed-effects analysis successfully isolates the effects of local site response. The event terms show little spatial correlation and more substantial variability than in other regions, which we attribute to uncertainties in the earthquake magnitudes. This analysis guides the selection of the GMMs for the 2025 update of the National Seismic Hazard Model for Puerto Rico and the US Virgin Islands.

Puerto Rico, U.S. Virgin Islands↗
USGS2026

Cultural benefits knowledge and social learning in Elwha River dam removal and ecosystem decision-making

In a retrospective case study of the seminal Elwha River dam removal in Washington State, USA, we explore pathways through which ecosystem services (ES) knowledge can inform environmental decision-making. We specifically investigate how knowledge of cultural benefits linked to the Elwha River ecosystem was made available. Through interviews and historical document review we identify diverse forms of cultural benefits knowledge (i.e., how individuals or groups know the contributions of an ecosystem to their identities, experiences, and capabilities), including both knowledge in the form of practices – embodied or enacted forms of knowledge, and knowledge in the form of products – quantitative or written documentation. Recognizing and learning from the diverse forms in which benefits knowledges are conveyed can support more accurate and equitable consideration of the diverse values, well-beings, and human-nature relationships linked to ecosystems. With this case study, we illuminate pathways for meaningful consideration of multiple knowledge forms, and the plural ecosystem values they convey, with relevance for environmental decision processes in the Puget Sound and beyond.

Washington↗
USGS2026

GST-1: A high-resolution global sediment thickness model

Global Sediment Thickness 1 (GST-1) is a high-resolution sedimentary thickness model calculated on a 0.125° x 0.125° grid. It modifies the sediment thickness of the 1° x 1° Earth Crustal Model 1 (ECM1) by means of 3D inversions of free air gravity anomalies. GST-1 is calculated by performing structural inversions on high-density contrasts across two crustal boundaries: the sediment – basement interface and the crystalline crust – upper mantle interface. The inversions are calculated in each of ten overlapping 3D models that span the globe. These ten models are merged to obtain the GST-1 global model, providing an eight-fold increase in lateral spatial resolution in comparison with ECM1 and CRUST 1.0. Our sediment thickness model exploits the nearly continuous sampling of gravity data when compared to the irregular, sparse sampling of seismic refraction data. Sediment thickness values in GST-1 are in excellent agreement with independently derived cross sections from well-studied sedimentary basins, and within expected resolution limits of seismic refraction data. GST-1 offers a robust, high resolution global model of sedimentary thickness to support studies of sedimentary basins.

Tectonophysics↗
USGS2025

Haunted Summerville: Ghostly lights or earthquake lights?

Among the colorful local lore in the Charleston, South Carolina, area, are a number of ghost stories, shared not only over campfires but also in published books. Among the most well-known of the stories is the tale of the Summerville Light. Local lore holds that a strange light sometimes seen in a remote area is a lantern carried by the ghost of a local woman who once waited hours for her husband, who turned out to have been decapitated earlier that day in a train accident (DePoppe, 2023). Extant sources suggest the ghost stories began to circulate in the 1950s to 1960s. So pervasive was the lore that (Old) Sheep Island Road became known among local residents as Light Road, with a local stretch of road known today as Old Light Road. Reviewing the location where the lights appear as well as the nature of accounts, I suggest that many if not all of the anecdotal observations can be most readily attributed to natural phenomena, including earthquake lights from earthquakes that were too small to be felt. Accounts of lights near Summerville cluster in proximity to the generally accepted epicenter of the 1886 Charleston, South Carolina, earthquake, where foreshocks to the 1886 mainshock were apparently concentrated, and within a few kilometers of three M3.5 – 4.4 earthquakes in 1959 and 1960.

South Carolina↗
USGS2026

Hydrological control on soil redox condition and carbon loss of coastal wetland under sea-kevel rise

Coastal wetlands are critical carbon sinks with their biogeochemical and ecological functioning shaped by dynamic hydrological conditions that are increasingly influenced by climate change. A key unresolved question is how hydrologic flow, vegetation response, and rising sea levels interact to regulate soil redox condition and carbon loss in coastal wetlands. Using a field-tested hydrological–biogeochemical–ecological modeling framework, we reveal how the interplay between terrestrial groundwater discharge and tidal fluctuations generates complex groundwater flow patterns at the terrestrial–aquatic interface, and how these patterns modulate soil redox conditions, in turn influencing soil organic matter decomposition and carbon loss. Notably, rising sea levels suppress soil CO 2 emissions while reducing lateral dissolved carbon losses, thereby enhancing litter carbon sequestration under anoxic conditions. As vegetation responds to sea-level rise and carbon inputs diminish, litter carbon subsequently declines. These findings underscore a critical hydrological control on carbon cycling, advancing our understanding of coastal ecosystem resilience in a warming world.

Louisiana↗
USGS2026

Open-source gravity reduction workflows for geothermal resource assessment

Potential-field geophysical data such as gravity can enhance understanding of geothermal resources at all stages of the resource life cycle, including assessment, exploration, development, and monitoring, and at multiple scales, from the reservoir scale to regional scale. However, to make gravity data useful for geothermal resource characterization, several processing steps are required to isolate the effects of density variations in the Earth’s crust to enable the identification of structural features associated with geothermal resources. Although this process is well-established, standard computational implementations for processing gravity data that are FAIR (Findable, Accessible, Interoperable, and Reproduceable) are still lacking. This paper details ongoing efforts at the U.S. Geological Survey (USGS) to develop a standard set of open-source Python tools for gravity data reduction that align with the FAIR principles. This workflow makes use of existing open-source tools for geophysical data processing with the goal of maximizing opportunities for rapid improvements, interoperability, and adaptability to other types of geophysical data.

Conference Paper↗