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USGS2026

Scenarios to assess the future water availability in the Mississippi River Valley Alluvial Aquifer for the Cache River and Grand Prairie Regions of Arkansas

The U.S. Geological Survey, as part of the Arkansas Groundwater Initiative, developed forecast scenarios using previously calibrated MODFLOW 6 groundwater models that focused on the Cache and Grand Prairie Critical Groundwater Areas to assess the impact of future climate and water management strategies on the Mississippi River Valley alluvial aquifer. A Soil Water Balance model was used to forecast recharge and irrigation water use. The forecast scenario period was from January 1, 2019, through December 31, 2055, with monthly stress periods. Twenty scenarios were simulated and included seven alternate climate forecasts, five 13 general groundwater pumping reduction scenarios (round 1), and groundwater pumping reduction scenarios by crop type and for the Bayou Meto Water Management Project and Grand Prairie Area Demonstration Project (round 2). Declines in saturated thickness within the Cache Critical Groundwater Area were larger for 18 of the 20 scenarios as compared to outside of the Critical Groundwater Area. The largest average increase in saturated thickness inside the Critical Groundwater Area was 6.4 m which occurred for the round 1, 50 percent reduction scenario. Automatic reductions in groundwater pumping by MODFLOW 6 in the Cache simulation ranged from 0.02 to 13.1 percent of total groundwater pumping. For the Grand Prairie model domain, the average change in saturated thickness of the Mississippi River Valley alluvial aquifer inside the Critical Groundwater Area for the forecast period ranged between -6.6 to 1.7 m. The average saturated thickness of the Mississippi River Valley alluvial aquifer inside the Grand Prairie Critical Groundwater Area declined for 16 of the 20 scenarios. The average reduction in requested groundwater pumping for all scenarios inside the Grand Prairie Critical Groundwater Area was 25.1 percent, and the largest reduction was 46.5 percent.

ESS Open Archive↗
USGS2024

California State Waters Map Series—Benthic habitat characterization in the region offshore Humboldt Bay, California

Coastal and Marine Ecological Classification Standard (CMECS) geoform, substrate, and biotic component geographic information system (GIS) products were developed for the California State Waters of northern California in the region offshore of Humboldt Bay. The study was motivated by interest in development of offshore wind-energy capacity and infrastructure in Federal waters offshore. This project, carried out by the U.S. Geological Survey (USGS), resulted in four data releases for individual map blocks that are part of the “California State Waters Map Series”: (1) Offshore of Arcata, (2) Offshore of Eureka, (3) Offshore of the Eel River, and (4) Offshore of Cape Mendocino. The study area consists of 436 square kilometers of multibeam echo sounder (MBES) data acquired by Fugro Pelagos, Inc., in 2007. Towed camera-sled video was acquired in 2009 and 2010 to supervise the classification of the MBES data into habitats, and single channel sparker data were collected to calculate sediment thickness above the transgressive unconformity. Using video observations of habitat as ground truth, derivatives of the MBES data were classified into 3 seafloor character types (hard-rugose, hard-flat, and soft-flat), 26 induration-slope-depth groups, and 15 geoforms. The study area substrate is predominantly soft-flat sediment (mud and fine sand) covering 73.6 percent of the area. Hard-flat substrate areas, predominantly coarse sediment in scour depressions, cover 5.4 percent of the study area. The hard-rugose substrate areas are primarily outcrops of layered sedimentary bedrock and constitute 20.9 percent of the study area. Fifteen geoforms were identified in the analysis. The predominant geoforms mirror the seafloor character results, shelf geoforms, rock outcrop geoforms, and scour depression geoforms. Rock and scour areas are restricted to the southern portion of the study area off Cape Mendocino where uplift has exposed bedrock. On the flat shelf area post-transgressive sediment varies in thickness from 1.7 meters (m) nearshore to 28.1 m offshore.

California↗
USGS2026

Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python

Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.

Wisconsin↗
USGS2024

Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2019–2021

The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Water availability is an important issue in the Black Mesa area because of the arid climate, past industrial water use, and continued water requirements for municipal use by a growing population. Precipitation in the area typically ranges from less than 6 to more than 16 inches per year, depending on location. The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents the results of data collected as part of the monitoring program in the Black Mesa area from calendar years 2020–2021 and, additionally, uses streamflow statistics from November and December 2019. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry. In calendar year 2020, total groundwater withdrawals were estimated to be 2,680 acre-feet (acre-ft), and, in 2021, total withdrawals were estimated to be 2,570 acre-ft. Total withdrawals during 2021 were about 65 percent less than total withdrawals in 2005 because the Peabody Western Coal Company discontinued its use of water to transport coal in a coal slurry pipeline after 2005 and ceased mining operations in 2019. Owing to Navajo Nation and Hopi Reservation access restrictions during the Coronavirus pandemic, water levels were not collected from municipal wells in 2020 or 2021. Water levels measured in 2021 from wells completed in the unconfined areas of the N aquifer within the Black Mesa area showed a decline in 7 of 13 wells when compared with water levels from the prestress period (prior to 1965). The changes in water levels across all 13 wells ranged from +8.4 feet (ft) to −42.4 ft, and the median change was −0.4 ft. Water levels also showed decline in 11 of 12 wells measured in the confined area of the aquifer when compared to the prestress period. The median change for the confined area of the aquifer was −25.9 ft, with changes across all 12 wells ranging from +17.3 ft to −133.7 ft. Spring flow was measured at four springs between 2020 and 2021. Flow fluctuated during the period of record for Burro Spring and Pasture Canyon Spring, but a decreasing trend was statistically significant (p<0.05) at Moenkopi School Spring and Unnamed Spring near Dennehotso, Arizona. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s, and discharge at Pasture Canyon Spring has fluctuated for the period of record. Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976–2021), Dinnebito Wash near Sand Springs 09401110 (1993–2020), Polacca Wash near Second Mesa 09400568 (1994–2020), and Pasture Canyon Springs 09401265 (2004–2021). Median winter flows (November through February) of each winter were used as an estimate of the amount of groundwater discharge at the above-named sites. For the period of record, the median winter flows have generally remained constant at Polacca Wash and Pasture Canyon Springs, whereas a decreasing trend was observed at Moenkopi Wash and Dinnebito Wash. In 2020 and 2021, water samples were collected from a total of four springs in the Black Mesa area and analyzed for selected chemical constituents. Results from the four springs were compared with previous analyses from the same springs. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 30 years of record at that site. Concentrations of dissolved solids and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. However, concentrations of chloride from Pasture Canyon Spring show a diminishing trend. Concentrations of dissolved solids, chloride, and sulfate at Unnamed Spring near Dennehotso have varied for the period of record, but there is no statistical trend in the data. Concentrations of dissolved solids at Burro Spring have varied for the period of record, but there is no statistical trend in the data. However, concentrations of chloride and sulfate from Burro Spring show a trend towards lower concentrations.

Arizona↗
USGS2024

Environmental monitoring of groundwater, surface water, and soil at the Ammonium Perchlorate Rocket Motor Destruction Facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania, 2021

Letterkenny Army Depot in Chambersburg, Pennsylvania, built an Ammonium Perchlorate Rocket Motor Destruction (ARMD) Facility in 2016 to centralize rocket motor destruction and contain all waste during the destruction process. The U.S. Geological Survey has collected environmental samples from groundwater, surface water, and soils at ARMD since 2016. During 2021, samples were collected from four groundwater wells in September, one surface-water site in October, and five soil sites in November near the facility. Samples were analyzed for nutrients, trace metals, major ions, total volatile organic compounds, and perchlorate. Perchlorate was not detected in any 2021 samples. Groundwater results showed no constituents exceeded any U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL). Dissolved arsenic (As) was detected in one well above the reporting detection level (RDL) of 3 micrograms per liter (μg/L) at 5.4 μg/L but below its MCL of 10 μg/L. Dissolved iron (Fe) was the only inorganic constituent measured above an EPA secondary maximum contaminant level (SMCL). All groundwater samples collected in 2021 exceeded the Fe SMCL of 300 μg/L, with concentrations ranging from 390 μg/L to 3,500 μg/L. Surface-water data collected during 2021 showed no measured constituents in the surface-water sample that exceeded any EPA MCL or SMCL. Soil samples collected from 2016 through 2021 showed all concentrations of As exceeded the EPA soil screening levels of 3 milligrams per kilogram (mg/kg) but did not exceed the Pennsylvania medium-specific concentrations for As of 61 mg/kg. Arsenic concentrations in 2021 ranged from 9.1 mg/kg to 12.9 mg/kg. The 2021 results for the ARMD Facility indicate no increases in concentrations of reported compounds compared to data from 2016 to 2020. The contained burn treatment facility for demilitarization of rocket motors during 2021 appears to have operated without elevating concentrations of target compounds compared to previous years.

Pennsylvania↗
USGS2026

Vegetation cover and composition in environments surrounding uranium mines in the Grand Canyon ecosystem, Northern Arizona

Mining uranium from breccia-pipe deposits in the greater Grand Canyon region has occurred since the mid-1900s. However, possible ecosystem contamination with harmful levels of radionuclides may have occurred due to mining activities in the 21st century. In response, a 20-year Federal moratorium on new mining claims in the Grand Canyon watershed was initiated in 2012, to allow time to evaluate the potential effects of uranium exploration and mining on human health, wildlife, and water resources. This moratorium, nor the 2023 designation of the “Baaj Nwaavjo I’tah Kukveni–Ancestral Footprints of the Grand Canyon National Monument,” precludes operation or development of mining claims predating 2012. Vegetation is a core ecosystem component that may be affected by uranium mining (for instance, through uptake and storage of radionuclides from the air or soil) or may act as a vector of exposure to wildlife, livestock, and humans (for instance, via their consumption of contaminated plant tissues). To provide baseline information about the plant communities associated with uranium mines in the Grand Canyon region, the U.S. Geological Survey surveyed an approximately 200-meter-wide buffer surrounding four breccia-pipe deposits, each in a unique stage of mine development, and at one reference area (a livestock water tank) that underwent ground disturbance but contains no mineral deposits. We sectioned the buffer zones into 0.65–4.52 hectare plots, within which we (1) inventoried all plant species, (2) measured percent cover of plant species, plant functional groups, and ground surface types (dark cyanobacteria, lichen, moss, bedrock, rock, embedded litter, duff, plant bases, and bare soil) using line-point intercept, and (3) measured length and frequency of gaps between perennial plant canopies using canopy gap intercept. We found that plant composition at the mines and the reference area differed from one another but were all characteristic of expected regional vegetation patterns. We provide this data summary as potential baseline information for future research and management efforts.

Arizona↗
USGS2026

Bathymetric survey and storage capacity of Upper Lake Mary near Flagstaff, Arizona in 2024

The U.S. Geological Survey (USGS), in cooperation with the city of Flagstaff, collected bathymetric, light detection and ranging (lidar), and land-survey data of Upper Lake Mary in Arizona during the months of April and October 2024. The city of Flagstaff uses a combination of groundwater from well fields throughout the Flagstaff area and surface water, mainly from Upper Lake Mary, for its potable water supply. The purpose of the survey is to update previous surveys using new technology and compare the results to previous surveys to determine if there was a decrease in storage capacity that could affect the city’s water supply. The lakebed was mapped in April 2024 using a vessel equipped with a multibeam echosounder (MBES) and mobile lidar scanner with positioning captured using a real-time kinematic global navigation satellite system (RTK GNSS) base and receivers. In October 2024, areas of the reservoir that were too shallow for the boat and shoreline that were not captured by the vessel-based lidar were surveyed on foot using hand-held RTK GNSS receivers. At full pool (spillway elevation of 6,831.82 feet above NAVD 88 [2,082.34 meters (m)], Upper Lake Mary has a storage capacity of 16,449.80 acre-feet (20,290,611.73 cubic meters) and a surface area of 953.57 acres (3,860,926.075 square meters). The reservoir is 5.7 miles (9.7 kilometers) long and varies in width from 326 feet (99.36 m) near the central, narrow portion of the reservoir to 2,613 feet (796.44 m) in the upper portion. Comparisons between this survey and the previous two surveys from the 1950s and 2006 indicate no apparent decrease in reservoir area or storage capacity. Results of the 2024 survey indicate that Upper Lake Mary’s storage capacity increased by 0.9 percent from the 2006 survey and a 1.6 percent increase in surface area from the 2006 survey.

Arizona↗
USGS2026

End-user needs for remote sensing wetlands of the Prairie Pothole Region of North America

The Prairie Pothole Region (PPR) of North America comprises globally important grassland and wetland ecosystems critical for numerous populations of migratory birds. Due to the importance of this region for migratory birds, and particularly waterfowl, and the threats of habitat loss due to intensifying agriculture, there is a mature and diverse system of conservation organizations, agencies, and partnerships that spends hundreds of millions of dollars annually on habitat conservation to support migratory bird populations. Remote sensing can be a powerful tool for observing and evaluating global change at large scales as well as expanding inferences from field studies to the broader landscape with statistical models. However, development and utilization of these tools has lagged behind their demand for several reasons, including concerns over spatial and temporal resolution and accuracy of products; perception of a misalignment with decision-maker needs; technological barriers such as skill sets of conservation professionals, computing resources, data access, and usability. In this report, we summarize the needs of conservation professionals and scientists who use or want to use remote sensing data products to inform science about wetland change and conservation of wetlands in the PPR. We assembled this information through several methods leading up to, during, and following a January 2026 PPR Wetland Remote Sensing Workshop. The workshop included United States and Canadian scientists, conservation professionals, and policy experts. Our goal was to bring together end-users and remote sensing product developers jointly to explore reducing the lag between product development and utilization of products to inform science and conservation. Specifically, we aimed to identify gaps in wetland remote sensing that limit effective monitoring, management, and conservation in the PPR, and to develop a framework that outlines pathways to address these gaps by fostering collaboration, improving communication networks, encouraging discussion, and building on existing and ongoing efforts. This report summarizes our participants’ descriptions of end-user needs and the outcomes of the workshop.

Prairie Pothole region↗
USGS2025

A method to obtain remotely sensed grain size distributions from nonplanar granular deposits

Constraining the grain size distribution of granular deposits with complex surfaces is difficult with existing approaches. Field and laboratory techniques are time consuming and limited by the maximum grain size that laboratories can accommodate. In this study, we present a new method to identify the coarse fraction of the grain size distribution at a debris-flow fan deposit surveyed with terrestrial laser scanning (TLS) in Glenwood Canyon, Colorado, USA. This method is a novel grain segmentation algorithm developed for application to point cloud data of deposits with complex surfaces and angular grains ranging in size from centimeters to a meter. This approach combines an existing random forest machine learning method with a novel iterative clustering algorithm. We compared the grain size distribution from our algorithm with a Wolman pebble count conducted in the field, and found a root mean squared error of less than 2 cm from the 5th to 95th percentile of the grain size distribution of grains ranging from cobble to boulder sized (6.3–78 cm in our application). Finally, we compared our new algorithm with an existing open-source grain segregation algorithm, and our method outperformed the selected alternative when applied to the debris-flow deposit point cloud.

Colorado↗
USGS2025

ARCHI: A new R package for automated imputation of regionally correlated hydrologic records

Missing data in hydrological records can limit resource assessment, process understanding, and predictive modeling. Here, we present ARCHI (Automated Regional Correlation Analysis for Hydrologic Record Imputation), a new, open-source software package in R designed to aggregate, impute, cluster, and visualize regionally correlated hydrologic records. ARCHI imputes missing data in “target” records by linear regression using more complete “reference” records as predictors. Automated imputation is implemented using a novel, iterative algorithm that allows each site to be considered a target or reference for regression, growing the pool of complete references with each imputed record until viable gap-filling ceases. Users can limit artifacts from spurious correlations by specifying model-acceptance criteria and applying geospatial, correlation, and group-based filters to control reference selection. ARCHI provides additional functions for visualizing results, clustering records with similar correlation structures, evaluating holdout data, and interactive parameterization with an accessible and intuitive graphical user interface (GUI). This methods brief provides an overview of the ARCHI package, modeling guidelines, and benchmarking on two regional groundwater-level datasets from the Central Valley, CA and Long Island, NY. We evaluate ARCHI alongside widely used multivariate imputation software to highlight and contextualize its computational efficiency, imputation accuracy, and model transparency when applied to large, groundwater-level datasets.

California, New York↗
USGS2025

The effects of line simplification on planform geometry

Data on maps should retain accuracy regardless of scale. Yet, as cartographic lines are generalized, there can be impacts on properties such as topology, density, and planform geometry. Here, we investigate the use of the Scale Specific Sinuosity (S3) metric (Stanislawski et al., 2023) to evaluate the effects of line simplification on planform geometry, which is the bends of streams in map view. We employ an open-source Python S3 workflow to characterize the geometry of five diverse stream channels in the United States. The original data are extracted from the U.S. Geological Survey National Hydrography Dataset 1:24,000-scale vector data (U.S. Geological Survey, 2000) (Table 1), and the simplification is done using the Visvalingam and Whyatt method (2017) with a simplification tolerance of 0.5, 1.0, 1.5, and 2.0 km. The S3 analysis is calculated at each level of simplification and S3 derivatives are generated. Derivatives include measures of sinuosity, fractal dimension, and the dominant bend wavelength. The findings show that the change in planform geometry is scale-dependent, though simplification will have little effect on straighter lines. The change becomes more apparent in complex lines as the degree of simplification aligns with the scale of the dominant bend geometries. These logical conclusions are evidence that the S3 is a useful metric for automated characterization of bend geometry regardless of line complexity.

Conference Paper↗
USGS2025

Collaborative drought science planning in the Colorado River Basin

The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2025

Geologic map of the Greater Antilles and Virgin Islands

Introduction The geologic map of the Greater Antilles and Virgin Islands is a compilation of information from the literature, integrated to provide a seamless geologic map of the region. This map was prepared to serve as a base map for a mineral resource assessment of the region. Several small-scale regional geologic maps of the region have been prepared in the past. This report supersedes an earlier version of the geologic map of the Greater Antilles and the Virgin Islands that was released as U.S. Geological Survey (USGS) Open-File Report 2019–1036. For this report, the regional geologic overview shown on sheet 1 covers Cuba; the island of Hispaniola, which includes Haiti and Dominican Republic; Jamaica; the Cayman Islands; Puerto Rico; and the U.S. and British Virgin Islands. Sheet 2 shows the geology of Cuba and Cayman Islands, sheet 3 the geology of Jamaica, sheet 4 the geology of Hispaniola, and sheet 5 the geology of Puerto Rico and Virgin Islands. Accompanying the maps are three tables: table 1 lists the map units (in alphabetical order by map-unit label), their ages, and the countries or territories in which they can be found. These are listed in alphabetical order for ease in locating unit names from the symbols on the maps. Table 2 is a list of sources for the geologic map compilation of Puerto Rico. Table 3 shows formations in the Devil’s Race Course Group of Jamaica.

Greater Antilles, Virgin Islands↗
USGS2025

Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data

The fringing coral reef off Olowalu, Maui, Hawaii, has been identified as a local conservation priority site. In 2007, the National Oceanic and Atmospheric Administration (NOAA) produced a benthic habitat map of the Hawaiian Islands that was used as a foundation for this study. To support place-based management of the reef in the future, the U.S. Geological Survey (USGS) mapped the geologic zone, major and dominant geomorphological structure, biological cover type, and percent of biological cover for 11 square kilometers (km 2 ) of Olowalu Reef at a minimum mapping unit (MMU) of 100 square meters (m 2 ) to create a benthic habitat map. Heads-up digitization was employed on 0.50-meter (m) natural color satellite orthoimagery with ancillary 1-m acoustic backscatter imagery from single-scan sonar (sound navigation and ranging). A 1-m, 4-m, and 8-m digital bathymetric model (DBM) was interpolated from bathymetric lidar (light detection and ranging), and various geomorphometric layers derived from the DBMs were used for habitat interpretation. Still-frame imagery of the seafloor extracted from vessel-towed underwater video transects on Olowalu Reef served as ground validation points ( n =870) during active mapping and accuracy assessment points ( n =216) for thematic accuracy assessment. Thematic accuracy was cross-validated by the Hawai‘i Department of Land and Natural Resources Division of Aquatic Resources. Final thematic accuracy was 88.8 percent for major structure, 85.6 percent for dominant structure, 86.0 percent for major biological cover, and 78.6 percent for type and percent of major biological cover. Reef and hardbottom constituted 52 percent of the total mapped habitat, comprising mostly aggregate reef (31 percent) and pavement (11 percent), with large swaths of spur-and-groove (9 percent). Of this hardbottom, 17 percent was covered with moderate (10 to <50 percent) coral and 27 percent with high coral cover (50 to <90 percent). High (50 to <90 percent) macroalgae cover dominated the continuous sand sheets in offshore bank/shelf zones. The map created in this study supplements the NOAA 2007 map and expands on the observations made by USGS sampling of the reef. The NOAA 2007 map and our map differed in total areal extent by a negligible 6 m 2 and were in general thematic agreement. Our map is intended to serve as a baseline for public access, general research, local-level management, and reef change for future studies.

Hawaii↗
USGS2026

Preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont

Introduction The bedrock geology of the 7.5-minute Port Henry quadrangle consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of an anorthosite-mangerite-charnockite-granite (AMCG) suite, now exposed mostly as orthogneiss, at approximately 1.18–1.15 Ga (giga-annum). In the Port Henry quadrangle, the AMCG metaigneous rocks (Yhg, Ygb, Yanw) intruded older, mostly metasedimentary rocks of the Grenville Complex during the middle to late Shawinigan orogeny (~1,160–1,150 Ma [mega-annum]). All rocks were subsequently metamorphosed to upper amphibolite to granulite facies conditions during the 1,080–1,050 Ma Ottawan orogeny. New mapping reveals four periods of deformation: (1) D1 produced rarely preserved isoclinal folds in the paragneiss and marble and predates AMCG magmatism. (2) Subsequent D2 deformation produced the dominant gneissic fabric preserved in the rock, recumbent folding, and deformed all the Proterozoic units in the map area. Syn- to late-D2 felsic magmatism resulted in the regionally extensive Lyon Mountain Granite Gneiss, which hosts numerous magnetite ore bodies. (3) Mylonitic extensional shear zones and core complex formation marked the beginning of D3 deformation. Protracted D3 deformation resulted in F3 upright folding, dome and basin formation, pegmatite intrusion, reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron-ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. (4) D4 created northeast- and northwest-trending local high-grade ductile shear zones and boudinage, northwest-trending regional kilometer (km)-wide ductile shear zones, and crosscutting granitic pegmatite dikes. The development of the late-stage regional shear zones (D4) was likely due to the continuation of extensional doming and uplift from upper amphibolite facies conditions at the end of the Ottawan orogeny. The majority of iron-ore deposits in the Port Henry and adjacent Witherbee quadrangles are in the hanging wall of these extensional shear zones. In the Port Henry quadrangle, the km-wide Cheney Mountain shear zone is the result of D4 deformation. Kilometer-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. The Paleozoic rocks are part of the Early Cambrian to Late Ordovician carbonate bank on the ancient margin of Laurentia. The approximately 1-km-thick Cambrian to Ordovician stratigraphy records a transition from synrift clastics to passive-margin peritidal carbonate buildups to gradually deeper-water subtidal- to shelf-carbonates during foreland basin development associated with the Taconic orogeny. The Paleozoic rocks are weakly folded and block faulted. Large areas of the Champlain Valley are covered by undifferentiated glacial deposits, some of which contain mapped landslides. The map also shows waste rock piles and tailings from historical mining operations. This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondacks, provide a context for historical iron mines in the eastern Adirondacks, and update the stratigraphy of the Champlain Valley in New York and Vermont. This Open-File Report includes a bedrock geologic map; a description of map units; a correlation of map units; and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information.

New York, Vermont↗
USGS2024

Seismic velocity changes from repetitive seismicity at Mauna Loa prior to and during its 2022 eruption

Mauna Loa’s short-lived eruption from late November to early December 2022 marked the culmination of nearly a decade of elevated seismic activity and geodetic inflation. The volcano has been monitored by a network of permanent, short period and broadband seismometers. I used the continuous waveform data from that network starting in 2012 to generate a catalog of seismicity that enhances the US Geological Survey Hawaiian Volcano Observatory’s public seismic catalog with four times the number of earthquakes, which were then grouped by waveform similarity. Analysis of subtle delays in the timing of arrivals of scattered waves between pairs of earthquakes in this catalog yields a history of small changes in the shallow seismic velocity structure of the volcano. Seismic velocities have been shown at other volcanoes to change during unrest and eruption. My results show a decrease in seismic velocity centered on the summit beginning in September 2022, corresponding to the onset of a vigorous precursory swarm of seismic activity and shallow inflation. During the eruption itself, I observe large changes due likely to dike opening along the northeast rift zone and deflation of the summit reservoir. However, seismic velocity changes associated with non-volcanic sources such as ground shaking from large earthquakes and meteorological influences at seasonal and diurnal time scales are also observed, and these dominate the velocity changes prior to the eruption. Proper accounting of these effects will be a requirement for use in real-time monitoring, and this work serves as a starting point in that endeavor for Mauna Loa.

Hawaii↗
USGS2026

Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?

This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; and (3) a modified composite band-ratio method for Sentinel-2 (SatBathy) with an initial simplified calibration, followed by a more rigorous linear regression against in situ bathymetry data. All methods were tested in three different areas with different geological and environmental conditions, Cabo Rojo, Puerto Rico; Key West, Florida; and Cocos Lagoon and Achang Flat Reef Preserve, Guam. It is demonstrated that all satellite derived bathymetry (SDB) methods have increased accuracy when the results are aligned with higher-accuracy ICESat-2 ATL24 track bathymetry data using the iterative closest point (ICP). SDB vertical accuracy depends more on location characteristics than the method or optical satellite instrument used. All error metrics considered (mean absolute error, median absolute deviation, and root mean square error) can be less than 5% of the maximum bathymetry depth penetration for at least one method, although not necessarily for the same method for all sites. The SDB error distribution tends to be bimodal irrespective of method, satellite instrument, alignment, site, or maximum bathymetry depth, leading to the potential ineffectiveness of traditional error metrics, such as the root mean square error. However, our analysis demonstrates that performing detrending where possible can achieve an error distribution as close to normality as possible for which error metrics are more diagnostic.

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USGS2025

Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy

The Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked by section 7002 (“Mineral Security”) of title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Congress) with reviewing and revising the methodology used to evaluate mineral commodity supply risk and the U.S. List of Critical Minerals (LCM) no less than every 3 years. Following two previous LCM assessments, this analysis represents the latest technical input for evaluating each mineral commodity’s supply risk and determining their recommended status on the LCM. We evaluated mineral commodity supply risk using two criteria: (1) an economic effects assessment that quantified the potential effects of various trade disruption scenarios on the U.S. economy, and (2) an examination of whether the mineral commodity’s U.S. supply chain relied on a sole domestic producer that represented a single point of failure. For the first criterion, postdisruption equilibrium quantities and prices for each mineral commodity were calculated based on their price elasticities of supply and demand and the availability of excess production capacity for each yearlong foreign trade disruption scenario. Subsequently, a nonlinear optimization routine was used with detailed economic input-output tables to estimate the potential economic effects on the U.S. economy of over 1,200 scenarios for 84 mineral commodities. After accounting for the probability of each scenario’s occurrence, the overall results are presented in terms of changes in U.S. gross domestic product (GDP) by individual industry and the economy overall. The results, which ranged from a net decrease in U.S. GDP of nearly $4.5 billion to a net increase of $33 million, largely reflect U.S. import dependency and world production concentration. Using the Jenks natural breaks optimization method, a statistical classification technique, we categorized the mineral commodities into several classes based on this overall risk quantification. Mineral commodities with annualized probability-weighted net decreases in U.S. GDP greater than $2 million were recommended for inclusion on the LCM. If a mineral commodity did not meet the threshold for inclusion on the LCM under the first criterion, its domestic supply chain was examined under the second criterion, which recommended a mineral commodity for inclusion on the LCM if there was only a single domestic producer. Ultimately, the two criteria resulted in the recommendation of the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the LCM. By using an economic effects assessment, the results of this analysis provide a prioritization that can also be compared directly against other risk analyses and the cost of various risk mitigation strategies.

Open-File Report↗