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1,687 records · Page 70Linked to original sources
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↗
USGS2024

Testing megathrust rupture models using tsunami deposits

The 26 January 1700 CE Cascadia subduction zone earthquake ruptured much of the plate boundary and generated a tsunami that deposited sand in coastal marshes from northern California to Vancouver Island. Although the depositional record of tsunami inundation is extensive in some of these marshes, few sites have been investigated in enough detail to map the inland extent of sand deposition and depict variability in tsunami deposit thickness and grain size. We collected 129 cores in marshes of the Salmon River estuary in Oregon and reanalyzed 114 core logs from a 1987–88 study that mapped the inland extent of circa 1700 CE sandy tsunami deposits. The ca. 1700 CE tsunami deposit in the Salmon River estuary is easily recognized in cores ≤1 m deep in which a buried marsh peat is overlain by a well sorted sand bed with a sharp lower contact that thins and fines inland. We use tsunami deposit data and models of sandy tsunami sediment transport (using Delft3D-FLOW) to test 15 rupture models that could represent a ca. 1700 CE earthquake. At least 12–16 m of slip offshore of the Salmon River, which results in 0.8–1.0 m of coastal coseismic subsidence, is required to match the ca. 1700 CE sand deposit's inland extent, which is consistent with models of heterogeneous megathrust slip in ca. 1700 CE. Our methods of detailed tsunami deposit mapping, combined with sediment transport modeling, can be used to test models of megathrust ruptures and their tsunamis to potentially improve earthquake and tsunami hazard assessments.

JGR Earth Surface↗
USGS2012

Development of vegetation based soil quality indices for mineralized terrane in arid and semi-arid regions

Soil quality indices (SQIs) are often management driven and attempt to describe key relationships between above- and below-ground parameters. In terrestrial systems, indices that were initially developed and modified for agroecosystems have been applied to non-agricultural systems in increasing number. We develop an SQI in arid and semi-arid ecosystems of the Western US impacted by different types of geologic mineralization using the relationship between vegetation community parameters and soil abiotic and biotic properties. We analyze these relations in soils associated with three different mineralization types: podiform chromite, Cu/Mo porphyry, and acid-sulfate gold vein systems at four different sites in California and Nevada. Soil samples were collected from undisturbed soils in both mineralized and nearby unmineralized substrates as well as from waste rock and tailings. Aboveground net primary productivity (ANPP), canopy cover and shrub density were measured for the vegetative communities. Minimum data sets were developed based on correlations between the soil and vegetation parameters, refined using principal components analysis, scored using non-linear functions, and combined into an overall SQI. The indices are comprised of one or two microbial parameters and three to six abiotic parameters, the latter consisting of nutrients and metals. Given the preliminary development of this approach, the parameters and combinations to arrive at an SQI for a given site cannot at this time be correlated or compared with that of another site. This SQI approach provides a means of quantifying disturbed ecosystem recovery resulting from mining, and could be applied to other disturbances in a way that readily distills the information for potential use by land managers. However, severely disturbed areas with little to no aboveground biomass, such as unreclaimed tailings, have likely crossed an ecological threshold that precludes the use of this type of monitoring tool.

California↗
USGS2023

Hidden system identification: Basin modeling as a tool for examining sedimentary geothermal resource potential

Three-dimensional (3D) geologic and temperature models have been developed for the onshore U.S. Gulf Coast. The results from these models identify areas of moderate- to high-temperature (90°-150°C and >150°C; respectively) geothermal resources at depths <6 km. This modeling study addresses the fundamental challenge of predicting where opportune temperature and lithology coincide. Unlike traditional geothermal systems with surface expressions of hydrothermal circulation (e.g., hot springs, fumaroles, sinter), sedimentary geothermal systems (SGS) are generally hidden. Historically, simplified efforts to predict subsurface temperatures in sedimentary basins have focused on linear temperature extrapolation that does not consider the variable thermal properties of different lithologies or lithologic changes with depth (e.g., compaction, lithification). Therefore, the need to understand basin architecture and predict temperatures in 3D within SGS is paramount to identifying geothermal resources and determining economic feasibility. Basin modeling software has long been used to characterize the subsurface conditions of sedimentary basins, including temperature, in the pursuit of finding hydrocarbons. This tool can also be adapted to evaluate the potential of geothermal resources in a sedimentary basin by predicting the confluence of desirable temperatures and reservoir lithologies. In this work, PetroMod basin modeling software was used to create a regional geologic model of the onshore U.S. Gulf Coast, covering over 500,000 km 2 calibrated to temperature data from wells. Inputs include structural surfaces from commercial databases, lithology information derived from published literature, and corrected bottom-hole temperatures (BHT) from over 6,000 wells. The resulting 3D geologic model can be used to predict temperatures throughout the basin. Maps were exported showing the depth, depositional unit, and reservoir lithology at which temperatures of 90°C and 150°C were reached, revealing over 400,000 km 2 of moderate- to high-temperature resources at depths <6 km. These maps function as a first-order screening tool to identify areas where low-, moderate-, or high-grade resource potential may exist, based on temperature and if optimal reservoir lithologies or depositional units of interest are present. Depending on the success criteria of a project, the same maps can be exported for any isotherm or incorporate other 1407 Gardner and Birdwell subsurface properties. The methodology employed in this work can be applied in any sedimentary basin with available subsurface data. Further calibration incorporating other data, including pressure and porosity, can expand the utility of basin modeling for geothermal evaluations. Basin modeling is a powerful but underutilized tool for identifying prospective geothermal resources in sedimentary basins.

Conference Paper↗
USGS2025

Understanding market sensitivity: Estimation of supply and demand elasticities for non-fuel minerals

In today’s rapidly changing economic landscape, understanding market responsiveness to price changes and the factors influencing commodity prices has become increasingly relevant. Price elasticities serve as indicators of how variations in market conditions affect supply and demand, providing insights into the sensitivity of commodity markets to price fluctuations. This paper presents a comprehensive analysis of price elasticities of supply and demand for 74 non-fuel mineral commodities including precious metals, base metals, minor metals, and industrial minerals that are utilized across various industries. We employ various econometric techniques, including fixed effects models for panel data and two-stage dynamic ordinary least squares (2S-DOLS) alongside autoregressive distributed lag (ARDL) models for time series analysis, to derive robust estimates of price elasticities. Our findings reveal variability in elasticities among different commodities and indicate that all studied mineral commodities exhibit price inelastic supply and demand in the short run, which we define as one year for the purposes of our analysis, given that the data is all annual. This research provides original estimates of price responsiveness for a wide range of commodities that have not been previously addressed in the literature, thereby enhancing the understanding of market dynamics in the mineral sector. Given that price elasticities can be influenced by factors such as market structure, technological advancements, mining costs, and industry-specific demand drivers, we use variables that serve as proxies for these factors.

Mineral Economics↗
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↗
USGS2026

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

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

Puerto Rico, US Virgin Islands↗
USGS2025

Airborne geophysical analysis to decipher salinization for coastal Louisiana

Coastal Louisiana is known for saltwater intrusion that threatens wetlands, aquifers, and rivers. However, the extent of saltwater intrusion is not well understood. This study develops an innovative framework with airborne electromagnetic (AEM) data to map chloride concentration distributions for wetlands in the Mississippi River deltaic plain and Chenier plain as well as for the Mississippi River Valley alluvial aquifer (MRVA) and Chicot aquifer. Moreover, the framework maps chloride concentrations along the Mississippi River and Atchafalaya River. Key components in the framework include the establishment of resistivity-to-chloride concentration transformation, 3D resistivity architecture building through geostatistics, and the employment of a lithologic model. The transformation functions correlate AEM resistivity data with porewater salinity measurements and groundwater and river chloride samples. The results show that AEM data reliably infers soil water chloride concentrations and correlates well with the distribution of various marsh types. AEM data reveals extensive saltwater presence at depth and near the coast, originating from salt domes and the Gulf of Mexico, respectively. The saltwater upconing pattern in the Chicot aquifer is likely due to excessive groundwater withdrawals. The AEM data also confirms a distinct tongue of saltwater intruding into the Atchafalaya Basin from the Gulf. The AEM data helps to identify faults that are obscured or eroded at the surface, which appear as leaky barriers in the subsurface where dramatic changes in chloride concentration are apparent. Finally, this study uses the AEM data to infer the presence of an extensive seawater wedge in the Mississippi River and Atchafalaya River.

Louisiana↗
USGS2025

Prospectivity mapping for geologic hydrogen

Geologic, or naturally occurring, hydrogen has the potential to become a new, low-carbon, primary energy resource. Often referred to as “white” or “gold” hydrogen, this gas occurs naturally in the Earth’s subsurface, similar to petroleum resources. However, unlike petroleum, which releases carbon dioxide when burned, burning hydrogen only produces water as a byproduct. Exploration for geologic hydrogen remains in an early stage and discoveries of high concentrations of subsurface hydrogen are still relatively rare. To facilitate research and exploration for this potential resource, this report presents the first publicly available prospectivity map of geologic hydrogen accumulations in the conterminous United States. Prospective regions are those regions in which all major components necessary for a hydrogen accumulation likely are present—a source of sufficient hydrogen generation, porous reservoirs for storage, and seals to prevent leakage. The midcontinent region of the United States and the central California coast are revealed as having high prospectivity. This analysis also identifies previously unrecognized prospective regions that may be favorable due to long distance lateral migration of subsurface hydrogen, such as the offshore eastern seaboard of the United States, and can provide a linkage between surface observations of hydrogen degassing and far-field source regions. The methodology developed to create this map is expandable and flexible and may be adapted to incorporate new concepts in the hydrogen system and for application to other regions of the world.

conterminous United States↗
USGS2025

Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes

Groundwater flow paths and processes that govern metal mobility and transport are difficult to characterize in mountainous bedrock watersheds. Despite the difficulty in holistic characterization, conceptual understanding of subsurface hydrologic and geochemical processes is key to developing remediation plans for locations affected by acid mine drainage, such as the Upper Animas River watershed in southwestern Colorado, USA. Stable isotopes of water and rare earth elements were utilized to evaluate groundwater flow and metal sources within this complex catchment. Stable isotope samples collected from draining mine adits and springs display systematic spatial variation wherein sample sites at higher elevations have greater seasonal variability than sites at lower elevations. The Upper Cement Creek watershed, where multiple draining mines are present, displays the lowest seasonal variation in stable isotopic signatures, potentially indicating the presence of a large, well-mixed volume of groundwater storage or interbasin groundwater flow. Rare earth elements display statistically significant variation between different alteration styles in the catchment. Overprinting of regional propylitic alteration is evident based on enrichment of middle rare earth elements in acidic springs and mines that are not spatially associated with surficial exposures of acid generating alteration styles. Europium anomaly and middle rare earth enrichment signatures from two flooded mine tunnels on opposite sides of a watershed divide indicate connections to the same subsurface flooded mine workings.

Colorado↗
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↗
USGS2000

Quality assurance and analysis of water levels in wells on Pahute Mesa and vicinity, Nevada Test Site, Nye County, Nevada

Periodic and continual water-level data from 1963 to 1998 were compiled and quality assured for 65 observation wells on Pahute Mesa and vicinity, Nye County, Nevada. As part of the quality assurance of all water levels, ancillary data pertinent to computing hydraulic heads in wells were compiled and analyzed. Quality-assured water levels that were not necessarily in error but which did not represent static heads in the regional aquifer system, or required some other qualification, were flagged. Water levels flagged include those recovering from recent pumping or well construction, water levels affected by nuclear tests, and measurements affected by borehole deviations. A cursory examination of about 30 wells with available water-level and down-hole temperature data indicate that water levels in most wells on Pahute Mesa would not be significantly affected by temperature if corrected to 95 degrees Fahrenheit. Wells with large corrections (greater than 10 feet) are those with long water columns (greater than 1,500 feet of water above the assumed point of inflow) in combination with mean water-column temperatures exceeding 105 degrees Fahrenheit. Water-level fluctuations in wells on Pahute Mesa are caused by several factors including infiltration of precipitation, barometric pressure, Earth tides, ground-water pumpage, and seismic events caused by tectonic activity and underground nuclear testing. No observed water-level fluctuations were attributed to a naturally occurring earthquake. The magnitude and duration of changes in water levels caused by nuclear tests are affected by the test size and the distance from a well to the test. Identifying water levels that might be affected by past nuclear tests is difficult because pre-testing water-level data are sparse. Hydrologically significant trends were found in 13 of 25 wells with multiple years of water-level record. The largest change in water levels (1,029 feet in 25 years) occurred in well U-19v PS 1D as a result of the Almendro nuclear test. Likely explanations for trends in most of the wells are either changes in precipitation patterns that affect recharge rates to the ground-water system, pumping effects from water-supply well U-20 WW, or a combination of these two factors.

Nevada↗
USGS1976

Digital telemetry system network installation for the National Earthquake Information Service

A Digital Telemetry System Network, developed by the Albuquerque Seismological Laboratory, was installed for the USGS National Earthquake Information Service (NEIS) during January 1975. NEIS is located in Golden, Colorado. The initial Digital Telemetry System Network consists of four independent digital telemetry systems that provide wide area coverage over most of the United States. The four systems were installed between: Albuquerque, New Mexico to NEIS; St. Louis, Missouri to NEIS; Salt Lake City, Utah to NEIS; and Menlo Park, California to NEIS. Each digital telemetry system will transmit fourteen channels of high accuracy seismic data in a digital format over a standard C-1 grade telephone line. Digitized data words will have a resolution of eleven digital bits plus one sign bit. Each digital telemetry receiver, located at NEIS, will have the capacity to provide fourteen channels of seismic data in a digital format suitable for either on-line digital computer analysis or magnetic tape recording. In addition the data can be presented in an analog format suitable for recording on helicorders or develocorders. This network is the first large scale digital telemetry system used by the U.S. Geological Survey for the transmission of real time seismic data.

Open-File Report↗
USGS2025

Enhanced hydrologic monitoring and characterization of groundwater drainage features

Groundwater drains to the land surface, generating the baseflow of streams, lakes, and wetlands. The hydrologic resilience of baseflow during prolonged dry periods and after disturbance can be assessed with evolving remote sensing analysis paired with localized monitoring of groundwater drainage features and creative model calibration strategies.

Nature Water↗
USGS2026

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

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

BioScience↗
USGS2025

3D Converted wave reverse time migration imaging

We describe a newly developed method for recovering high-resolution images of seismic discontinuities, such as subducting slabs, in 3D. Our method makes use of converted S → P or P → S waves observed by dense arrays of seismometers to infer the locations and relative strengths of seismic discontinuities at depth in a target region. Observed direct and converted waves are backpropagated to their times of origin. The time-reversed wavefield is then separated into its constituent P and S components via the Helmholtz decomposition, and those separated wavefields are used to compute imaging functions that characterize the locations and relative strengths of seismic discontinuities. Imaging functions may be designed to use either S → P or P → S waves, so that users can target those arrivals expected to be most dominant in a given dataset. We have previously demonstrated the efficacy of our method in two dimensions, and we now present a 3D implementation of our technique which addresses the significant computational challenges posed by the size of volumetric wavefield data in three dimensions. Through a series of synthetic examples, we demonstrate that our method is capable of recovering the fine scale structure of a subducting slab given realistic station coverage and earthquake sources. We investigate optimal seismic station geometries for our technique and explore image interpretability in regions with poor data coverage. We find that linear station geometries yield more optimal, interpretable imaging functions than collections of small arrays can. We also show that our method can successfully recover bothS → P or P → S images when realistic shear earthquake sources are used, and we explore the additional computational challenges presented by the high frequency content of S waves. Our results demonstrate the potential for our technique to recover high-resolution information about subducting slabs in real-world regions, given that relatively sparse seismic arrays with only approximately 100 stations are capable of recovering interpretable imaging functions from just a few realistic earthquake sources for multiple discontinuities at significant depth in an area of approximately 400~sq~km.

Seismica↗
USGS2026

Multi-site evaluation of a postfire debris-flow runout forecast method

Postfire debris flows pose a hazard to human life, property, and infrastructure when they travel from steep source areas to urbanized alluvial fans or other developed areas. Existing methods for rapid (<1 week) postfire debris-flow hazard assessment document the increase in the likelihood and size of debris flows as the magnitude of high-intensity rain necessary to initiate debris flows increases but do not indicate the extent of downstream debris-flow runout. Although many models for the simulation of debris-flow motion are available, there is no established approach for using these models to delineate locations susceptible to postfire debris-flow runout that (a) is feasible to use at the spatial scale of an entire fire; (b) is appropriate for runout onto unconfined areas; (c) reproduces observed relations between runout and rainfall intensity; and (d) characterizes inherent uncertainty in runout, even without spatiotemporally variable rainfall. We propose and evaluate a method for generating postfire debris-flow runout hazard maps that has all the above qualities. Selection of case studies prioritized events triggered by a range of rainfall intensities, locations within and outside of southern California, and observed runout onto unconfined topography. Qualitative and quantitative assessment of performance for four events indicate that simulation results broadly match observations albeit with some discrepancies at a scale larger than structure or land parcel level (approximately 20-m by 20-m). The method may be used to identify potentially hazardous areas immediately following a fire and to provide approximate runout forecasts when a storm is imminent.

Arizona, California↗
USGS2025

Dating a medieval tsunami with uranium-series techniques on Caribbean corals

Uranium-series dates from coral boulders constrain the timing of a medieval tsunami from the Puerto Rico Trench. Previously reported evidence for this tsunami includes hundreds of coral boulders that came to rest hundreds of meters inland on Anegada, British Virgin Islands. New U-series dates on these coral boulders provide limiting dates for the tsunami. The narrowest limits were by dating interior bands of a coral that retains the hemispherical form of a living coral colony, and which include adjustments for the number of annual density band couplets between the dated samples and the boulder exteriors. By those limits, the tsunami dates between 1381 and 1391 CE, and likely occurred during summer or fall. The tsunami is important as the only reported sign that the eastern Puerto Rico Trench has produced a great earthquake. The dating may aid in defining the earthquake source and in communicating tsunami hazards.

British Virgin Islands, Puerto Rico↗