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939 records · Page 32Linked to original sources
USGS2025

Preliminary depth to basement modeling at Salton Sea, California

The San Andreas Fault – Imperial Fault (SAF-IF) transtensional step-over zone along the southern margin of the Salton Sea hosts substantial geothermal production and lithium brine resources. Recent volcanism at the Salton Buttes and active seismicity along the SAFIF fault system highlight active tectonic and magmatic processes that pose natural hazards and may impact energy and mineral production. Characterizing the subsurface architecture and extent of concealed alteration associated with this tectono-magmatic system enhances understanding of these active processes, associated hazards, and resources. We have compiled a gravity database, consisting of new and re-processed existing data, from which we have constructed a new isostatic residual gravity anomaly map of the Salton trough. We have used this new gravity dataset together with a compilation of publicly available borehole data to develop new depth to basement inversion models for the region. These depth to basement models help to constrain basin geometries, inform alteration mapping, and reveal variations in basement rocks. Due to the concealed nature of the complex tectonic framework at the Salton trough, it is necessary to utilize geophysical methods for subsurface characterization. These new depth to basement models are a first step toward constructing 2D and 3D geophysical and geologic models of the Imperial Valley and Salton Sea geothermal area. This analysis complements other geophysical initiatives, including magnetotelluric (MT) modeling (Tokmakoff et al., 2024), magnetic mapping (Glen and Earney, 2023, 2024) and potential field modeling, and seismic studies focused on hazard and resource investigations in the Imperial Valley.

California↗
USGS2025

Gravity and magnetic surveys of the Skaergaard intrusion, East Greenland

Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland were carried out in July–August 1971 as part of a grant to the University of Oregon Center for Volcanology to refine the models of crystallization and differentiation of the intrusion, specifically to test whether the intrusion is underlain by dense rocks of a reservoir 20 kilometers (km) thick (referred to as a “hidden zone”). The Skaergaard intrusion is a source of platinum group elements that are critical mineral resources for many technologies, and because no new data have been collected these legacy datasets remain a valuable asset. The total-intensity aeromagnetic survey was flown in early July 1971 with a proton precession magnetometer at a constant barometric altitude of 1.5 km (5,000 feet) with a nominal line spacing of 1 km. Two gravimeters were used to acquire 168 stations of which 86 were at known altitudes (mainly sea level) and 82 had altitudes measured by altimetry in late July–August 1971. Finally, a north-south ground vertical-intensity magnetic traverse was completed across the intrusion together with collection of oriented hand specimens. The hand specimens were measured for remnant magnetization and density, along with density measurements of more specimens collected by expedition geologists for other purposes. The intrusion is composed of layered gabbro with extensive crystal fractionation that is dense and strongly reversely polarized. After terrain correction and standard Bouguer gravity reduction, the gravity anomaly dataset was corrected for all rock above sea level using the density measurements of the various zones of the intrusion and the topographic and geologic maps (variable density Bouguer gravity reduction). A large regional gradient in the gravity anomaly data was removed using orthogonal polynomial fitting to the gridded data. The zonal volumes of rock below sea level were calculated from the dipping polygonal layer gravity model of the intrusion below sea level and combined with elliptic cross–section cylinders for the various zones above sea level to approximate the original zonal volumes of the intrusion. The residual gravity anomaly of 18–20 milligals (mGal) was only about half of the expected anomaly if a large hidden zone proposed from petrologic considerations were present, and both two-dimensional and three-dimensional models imply that the exposed series of intrusion zones explain the gravity anomaly by their down-dip extension below sea level together with a small hidden-zone volume. A three-dimensional model of the exposed rocks and their down-dip extension below sea level also can account for the aeromagnetic anomaly with little or no requirement for hidden-zone rock. The middle and upper zone units of the intrusion contain the most magnetite and account for most of the aeromagnetic anomaly.

Skaergaard intrusion↗
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↗
USGS2024

U.S.-Mexico Borderland & vegetation community map

People on both sides of the United States-Mexico border need a high-resolution, binational vegetation community map that spans the entire United States-Mexico borderlands. Traditionally, mapping efforts in this region were impeded by complex logistics related to the international border, differing national needs and plans, and resource allocations and priorities. To address this need, scientists from the U.S. Geological Survey (USGS) Southwest Biological Science Center partnered with the Sonoran Joint Venture, the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program, data engineers from the Department of Biosystems Engineering at the University of Arizona, and collaborators from the Wildlands Network, the Borderlands Program to produce the first prototype land cover map within the overlapping Mojave Desert, Sonoran Desert, and the North American Bird Conservation Initiative’s Bird Conservation Region 33 (BCR33) using Landsat satellite data . BCR33 is an area of high biodiversity, providing habitat for bird species of concern and other wildlife. The land cover map supports FWS recovery plan efforts related to conservation planning activities for many species, including Yellow-billed Cuckoo ( Coccyzus americanus ), Cactus Ferruginous Pygmy-Owl ( Glaucidium brasilianum cactorum ), Southwestern Willow Flycatcher ( Empidonax traillii extimus ), Yuma Ridgway’s Rail ( Rallus obsoletus yumanensis ), Bendire’s thrasher ( Toxostoma bendirei ), LeConte’s thrasher ( Toxostoma lecontei ), Masked Bobwhite ( Colinus virginianus ridgwayi ), jaguar ( Panthera onca ), and endangered plants such as Bartram’s stonecrop ( Graptopetalum bartramii ) and the Pima pineapple cactus ( Coryphantha robustispina ssp. robustispina ). In 2024, a Phase-II map for the full BCR33 region was completed, increasing the understanding of the binational nature of natural communities. The published map and associated paper can be found here .

Borderland↗
USGS2026

Where will the cat cross the road? Comparing camera and GPS-based models for identifying wildlife corridors

Designing effective wildlife corridors is a critical conservation challenge in fragmented landscapes. GPS-based step selection functions strongly predict dispersal corridors and connectivity, but GPS collaring can be expensive and invasive. Camera-based occupancy models are widely used for connectivity analyses but may involve trade-offs in data resolution. Despite widespread use of both approaches, few studies have directly compared them using concurrent datasets. We developed a stacked single-species, single-season occupancy model and a Circuitscape connectivity surface for mountain lions (Puma concolor) on Washington’s Olympic Peninsula, USA, and compared them with a connectivity surface from an existing integrated step selection function. Both models predicted mountain lion GPS locations well, with binned Spearman rank correlations of 1 for Circuitscape and 0.96 for the step selection function, though step selection better identified habitat use by dispersers. Connectivity predictions were moderately correlated across the landscape ( r = 0.26), but agreement was strongest in human-dominated areas most critical for corridor planning. We conclude that GPS-based approaches are advantageous when data collection is feasible and the focus is on dispersal or fine-scale movement. However, camera-based approaches may be preferable for multi-species monitoring, large spatial and temporal scales, noninvasive sampling, when resources are limited, or when fine-scale or dispersal-specific inference is not required.

Washington↗
USGS1998

Satellite imagery of the north-central Gulf of Mexico, June 1993-May 1997

This CD contains imagery collected by the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar-orbiting weather satellites. The AVHRR provides almost daily coverage of a site at a resolution of approximately 1 km. The data types included are sea surface temperature (SST), water reflectance (REF), and a false-color infrared overview (FCI).

Alabama, Florida, Louisiana, Mississippi↗
USGS1999

Reconfigured-Channel Monitoring and Assessment Program

A U.S. Geological Survey program to monitor and assess channel reconfiguration activity is described. A data base available on the world wide web will enable land-management agencies and other interested parties to evaluate the long-term success of various channel reconfiguration projects. A demonstration project on the Lake Fork of the Gunnison River, Colorado, illustrates the program objectives and approach.

Colorado↗
USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗
USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗
USGS2025

Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)

Residual oil zones (ROZs) can offer significant oil resources via enhanced oil recovery (EOR) as well as subsurface carbon dioxide (CO 2 ) retention during injection. If injected CO 2 is anthropogenic, the ROZs can offer a substantial geologic storage potential. The ROZs below the oil/water contact (OWC) of main pay zones (MPZ) in conventional reservoirs or brownfields, are more commonly developed for CO 2 injection and oil production and reported in the literature. However, CO 2 -EOR in greenfield ROZs, reservoirs without a MPZ present, have rarely been developed for CO 2 -EOR operation. The Tall Cotton Field of West Texas, Permian Basin, which started production in 2015 (Phase 1) and expanded in 2017 (Phase 2) from the San Andres Limestone, is one of the first examples of greenfield ROZs developed for EOR by injecting CO 2 . This paper analyses EOR and CO 2 retention performance of Tall Cotton Field using allocated injection and production data from inverted 5-spot well patterns of Phase-1 and -2 developments. Production and injection data allocated to each of the 28 identified patterns (nine 20-acre patterns for Phase-1, three 20-acre and sixteen 10-acre patterns for Phase-2) were analyzed for historical and forecasted oil recovery using ratio-trend decline analysis, and for CO 2 retention performance of the patterns. The allocated data were further used to calculate injected reservoir pore volume and void replacement ratios (VRR) for the analysis period. Quantitative results indicated that oil recovery factors of the 5-spot patterns varied between 4–10 %, and 5–30 % between the end of injection and the forecast periods, respectively. Storage of CO 2 , on the other hand, increased to a mean value of ∼7130 MMscf per pattern in Phase-1 and to a mean storage of 3700 MMscf per pattern in Phase-2 until the end of injection, followed by a decline after the end of injection and into the forecast period. Resulting CO 2 utilization factors ∼6–50 Mscf/bbl were estimated at the end of injection. Overall, presented results suggested that developing greenfield ROZs for CO 2 -EOR can be as promising as brownfield ROZs and mature MPZs for EOR and underground storage of injected CO 2 . For Tall Cotton Field, results suggest that Phase-2 patterns generally outperformed Phase-1 for oil recovery factors, while Phase-1 performed better in CO 2 retention performance metrics. This is the first study in the literature that reports a detailed CO 2 -EOR performance analysis of a greenfield ROZ in the Permian Basin, which can potentially allow for comparison with MPZs and brownfield ROZs.

Texas↗
USGS2026

Complex carbonate ore mineralogy in the Mountain Pass carbonatite rare earth element deposit, USA

Economic concentrations of rare earth element (REE) minerals are uncommon in the Earth’s crust, with most occurring in carbonatites. Unlike most igneous rocks composed of silicate minerals, carbonatites are dominated by carbonate minerals, some of which can incorporate significant light REEs (LREEs; La, Ce, Pr, Nd). Technological applications of REEs are numerous and they have been identified as some of the most critical mineral commodities to the global economy. The Mountain Pass carbonatite stock in the Mojave Desert of California is the most economically significant REE deposit in the USA and contains a few to tens of percent (by volume) of the carbonate REE ore mineral bastnäsite. Despite the economic significance of the Mountain Pass deposit, studies of its ore mineralogy are limited. Here we present new carbonate ore mineralogy data for a compositionally diverse suite of carbonatitic rocks from the Mountain Pass stock and related dikes. Whole-rock geochemical data are integrated with mineral-scale textural and chemical data obtained by scanning electron microscopy (SEM), electron probe microanalysis (EPMA), and microRaman spectroscopy. Our results document a complex spectrum of REE-bearing carbonate minerals and intermediate mixed-layer structures. Mineral species include bastnäsite [REE(CO 3 )F], hydroxylbastnäsite [REE(CO 3 )OH], parisite [Ca(REE) 2 (CO 3 ) 3 F 2 ], synchysite [Ca(REE)(CO 3 ) 2 F], röntgenite [Ca 2 (Ce,La) 3 (CO 3 ) 5 F 3 ], and sahamalite [(Mg,Fe 2+ )(REE) 2 (CO 3 ) 4 ]. Carbonate ore mineralogy is heterogeneous within and between samples, including at the intracrystal scale. Complexly zoned crystals exhibit as many as five to six different compositional domains and syntaxial intergrowths, commonly with the more Ca-rich varieties (parisite, synchysite) forming crystal rims that surround relict bastnäsite cores. We attribute the phenocryst variability to changes in the chemistry and temperature of primary carbonatite magmas and evolved/exsolved fluids. Cross-cutting vein textures of calcite, celestine and various REE carbonate minerals, interstitial bastnäsite crystallization, breccia blocks lined by fine-grained bastnäsite, and the presence of hydroxylbastnäsite and partially hydroxylated bastnäsite point to the role of secondary hydrothermal processes in REE mineralization. Fluorcarbonate mineral compositions demonstrate that La and Ce are more structurally abundant in bastnäsite, whereas the more Ca-rich species (parisite, synchysite) contain a greater proportion of REE heavier than Pr (Nd, Sm, Eu, Gd) and Y. Atomic ratios of Pr/(Nd + Pr) are likewise variable, with the highest average value for bastnäsite (0.25) compared to parisite (0.22) and sychysite (0.21). This finding has geometallurgical implications, given that current mining operations are focused on recovery of Nd and Pr for high field strength permanent magnets and the Nd/Pr ratios are a critical factor in ore processing and magnet manufacture.

California↗
USGS2026

The Great Lakes Geologic Mapping Coalition—Working collaboratively to understand the geology of the Great Lakes Region

Introduction The Great Lakes Geologic Mapping Coalition (GLGMC), commonly referred to as the “Coalition,” is a partnership between the U.S. Geological Survey (USGS), the U.S. States of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin and the Canadian province of Ontario. The member States receive funding for geologic mapping work from the USGS National Cooperative Geologic Mapping Program (NCGMP), whereas Ontario participates as a nonfunded partner. The mission of the GLGMC is to produce three-dimensional (3D) geologic maps that depict unconsolidated sediments and near-surface bedrock in the Great Lakes region of North America. Geologic maps are the basis of most earth science investigations and help support resource exploration (energy, minerals, groundwater), natural hazard mitigation, infrastructure development, and land-use planning, all of which can be used to advance economic development and strengthen national security in the Great Lakes region. During the last few million years, the Great Lakes region has experienced repeated glacial advances and retreats, leaving behind extensive sediments, abundant natural resources, and widespread effects on the underlying bedrock geology (Swezey and others, 2022). Linked by shared histories of past glaciations, industrial agriculture, and legacy automotive, coal, steel, and manufacturing industries, the GLGMC member States collaborate to improve the understanding of the 3D distribution of the sediments overlying the region’s bedrock (fig. 1). Developing a comprehensive subsurface 3D framework of this glaciated terrain can provide earth science data to policymakers at all levels. These insights facilitate informed decisions on the exploration, use, and protection of vital resources, such as critical minerals, industrial materials, and aquifers, thereby supporting economic prosperity and the well-being of the citizens of this region. Since its inception in 1998, the Coalition has completed more than 100 geologic mapping projects across the Great Lakes region. Each project aims to deliver geologic maps, 3D datasets, and other information that improves understanding of the geology of the Great Lakes region, with an emphasis on economic and water resources. Key deliverables include 3D geologic maps and models typically portraying sediment thickness, often derived from top-of-bedrock and borehole data. These products are developed through a combination of fieldwork, subsurface modeling, and the collection and analysis of rock and sediment cores. To support Coalition goals, member States collaborate with scientists working on related STATEMAP, EDMAP, and FEDMAP projects. Coalition scientists also engage with Tribal Nations in the Great Lakes region to ensure that Tribal interests pertaining to Coalition work are addressed. Through this collaboration, the Coalition unites the efforts of State, Federal, and Tribal Nation stakeholders to advance geologic data production and enhance understanding of the geologic resources of the Great Lakes region.

Illinois, Indiana, Michigan, Minnesota, New York, ↗
USGS2026

The geologic history of the Chehalis Forearc Basin, Washington State, USA

The Chehalis basin is located between the Cascade arc and the Coast Range in southwest Washington State. It consists of sedimentary and volcanic rocks deposited throughout the Cenozoic and is underlain by the Siletzia terrane, a thick, large igneous province accreted in the Eocene. Here, we constrain evolution of the Chehalis basin depocenter using isochore maps derived from isostatic gravity anomalies, borehole data, and stratigraphy for several time periods: the Eocene (47.6–36.8 Ma), the Oligocene (36.8–20 Ma), and the Neogene (20–0 Ma). Our results suggest that local subsidence is driven by deformation on faults that bound and intersect the basin. We see northward depocenter migration, interpreted as a shift in deformation from the northwest striking Cedar Creek fault to the west striking Doty fault. We interpret these data in terms of the long-term north-south shortening and clockwise rotation of the Cascadia forearc. During the Eocene, the Cedar Creek fault was preferentially aligned with north-south shortening, but became less active when clockwise rotation brought the Doty fault into east-west alignment with the stress field. Sediment accumulation rates decreased from 196 m/Myr in the Paleogene (∼40–20 Ma) to 27 m/Myr in the Neogene (∼20–0 Ma) as Miocene uplift of the Coast Range limited accommodation space and shifted the depositional environment from marine to fluvial. Our results are consistent with the geologic evolution of the Portland and Tualatin basins to the south and reveal a depositional and structural history uniquely shaped by clockwise rotation of the Cascadia forearc.

Washington↗
USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗
USGS2026

From collision to subduction: Thermal-kinematic inversions constrain plate boundary structure and dip-slip activity in southwestern New Zealand

Constraints on three-dimensional fault system geometry and kinematics are required to understand both long-term tectonics and contemporary seismic hazard. In many cases, these parameters must be inferred from a combination of different data or analyses. Here, we invert low-temperature thermochronological data to quantitatively parameterize both the crustal-scale geometry and late Cenozoic dip-slip activity of the plate boundary system in southwest New Zealand. We find that the modern transpressive plate boundary system has accommodated the bulk of Australian-Pacific Plate convergence since establishment in the middle Miocene-early Pliocene. Shortening has occurred via (a) dextral-reverse slip on the moderate angle, listric central Alpine Fault décollement, and (b) reverse-slip on either the sharply curved, anti-listric northern Puysegur subduction interface or low-angle offshore thrust fault system that splays from the high-angle southern Alpine Fault at depth. We resolve late Cenozoic shortening rates on these structures that are indistinguishable, and interpret these to reflect the transfer of convergent deformation outboard of the predominantly strike-slip southern Alpine Fault. Our work helps elucidate the transition from strain localized oblique continental collision to strain partitioned subduction. We also provide an estimate of the across-strike width of the central-southern Alpine Fault section boundary at seismogenic depths. This is the first quantitative constraint on the geometry of a structural feature inferred to have arrested several major prehistoric earthquakes. This study furthers understanding of fault structure and dip-slip kinematics along the greatest sources of seismic hazard in and offshore of southwest New Zealand.

South Island↗
USGS2024

Surficial geology and Quaternary fault map of the Las Vegas Valley, Clark County, Nevada

The Surficial Geology and Quaternary Fault Map of the Las Vegas Valley, Clark County, Nevada is a 1:50,000-scale compilation of published 1:24,000-scale geologic maps integrated with new field and desktop mapping. This geologic map compilation and GIS database are part of a broader study on the Quaternary faults in the Las Vegas Valley, the results of which are summarized in this report. The map compilation utilized a variety of digital base maps to evaluate the characteristics of surficial deposits and Quaternary fault scarps including lidar data in undeveloped parts of the valley and orthorectified historical aerial photos in the urbanized center of the valley. The map distinguishes twenty surficial map units including alluvial-fan and ephemeral-wash deposits, groundwater discharge deposits of the Las Vegas Formation, and alluvium deposits of Las Vegas Wash. Quaternary faults include the Quaternary Las Vegas Valley fault system in the center of the valley and the Frenchman Mountain fault system along the eastern margin. All Quaternary fault traces in the valley were evaluated, and the previously published fault mapping was modified as needed. The new mapping and uniform correlation of surficial deposits displaced by Quaternary faults yields a consistent valley-wide characterization of the recency of fault activity. The map and GIS database include a Quaternary geochronology compilation of 119 previously published surficial deposit ages of various types, 35 new luminescence ages, and 3 new radiocarbon ages. The new age data further bracket the ages of the Las Vegas basin Quaternary stratigraphy and provide new constraints on the timing of Quaternary fault activity.

Nevada↗
USGS1995

The distribution of bromide in water in the Floridan aquifer system, Duval County, northeastern Florida

Although Duval County, Florida, has ample ground-water resources for public supply, the potential exists for a problem with excessive disinfectant by-products. These disinfectant by-products result from the treatment of raw water containing low concentrations of bromide and naturally occurring organic compounds. Because of this potential problem, the relation of bromide concentrations to aquifer tapped, well location and depth, and chemical characteristics of water in the Floridan aquifer system underlying Duval County were studied to determine if these relations could be applied to delineate water with low-bromide concentrations for future supplies. In 1992, water samples from 106 wells that tap the Floridan aquifer system were analyzed for bromide and major dissolved constituents. A comparison of bromide concentrations from the 1992 sampling with data from earlier studies (1979-80) indicates that higher bromide concentrations were detected during the earlier studies. The difference between the old and new data is probably because of a change in analytical methodology in the analysis of samples. Bromide concentrations exceeded the detection limit (0.10 milligrams per liter) in water from 28 of the 106 wells (26 percent) sampled in 1992. The maximum concentration was 0.56 milligrams per liter. There were no relations between bromide and major dissolved constituents, well depth, or aquifer tapped that would be useful for determining bromide concentrations. Areal patterns of bromide occurrence are not clearly defined, but areas with relatively high bromide concentrations tend to be located in a triangular area near the community of Sunbeam, Florida, and along the St. Johns River throughout Duval County.

Florida↗