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Design and function of the Autonomous Benthic Imaging and Surveying System (ABISS) for remote sensing of lake and seabed environments

Lake and seabed environments are home to fisheries and other biota that are important to ecosystems and economies, yet these environments and the species that use them are difficult to accurately assess and monitor. Traditional benthic survey techniques, like bottom trawling used by the U.S. Geological Survey, are limited by substrate constraints, poor spatial resolution and precision, and operational depth limits, hindering accurate assessment of benthic species and habitats. In response to these limitations, the U.S. Geological Survey developed the Autonomous Benthic Imaging and Surveying System, a camera system integrated into underwater vehicles, to capture high-resolution images of the lakebed. The system uses color and stereo cameras to collect imagery, which can be analyzed using computational methods to detect organisms and (or) characterize habitat features, such as geologic substrate types. The system has been integrated into autonomous underwater vehicles and into an underwater housing used by self-contained underwater breathing apparatus (SCUBA) divers. Although the engineering of the system was motivated by the need for data collection in the Great Lakes, it has potential to collect high quality data in any aqueous setting with sufficient water clarity and safe operating conditions. The Autonomous Benthic Imaging and Surveying System can operate across diverse depths and light conditions to map and quantify ecological patterns that were difficult or impossible to assess using traditional methods. The Autonomous Benthic Imaging and Surveying System offers the potential for accurate and precise monitoring and assessment of native benthic biota, invasive species, and habitat, potentially providing natural resource managers with improved information to support decision making about benthic resource management.

Great Lakes

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions

Seamless Geologic Map Database for the Intermountain West, United States: A foundational dataset for mineral systems analysis

The Intermountain West has a complex geologic history, resulting in the formation of a diverse array of mineral deposits. Effective mineral exploration requires understanding the spatial and temporal relationships among geologic processes and events, a key focus of the mineral systems approach to exploration. This paper presents the Intermountain West Seamless Geologic Map Database, a unified dataset designed to support mineral exploration. Integrating geologic provinces, structural settings, and hydrothermal alteration, the database leverages the Seamless Integrated Geologic Mapping (SIGMa) extension to the USGS Geologic Map Schema (GeMS) to standardize geologic data from varied sources. SIGMa's hierarchical stratigraphic organization and feature-level metadata enhance data interoperability and reusability, enabling seamless query, analysis, and visualization of lithology, structural features, mineral deposits, geochronology, hydrothermal alteration. volcanic activity, and By providing a regionally consistent and dynamically evolving geologic map, this database provides a foundational framework for mineral exploration and geologic research. It also allows for an efficient workflow that expedites the publication of integrated geologic map databases.

Conference Paper

Recent applications of the USGS National Crustal Model for Seismic Hazard Studies

The U.S. Geological Survey is developing the National Crustal Model (NCM) for seismic hazard studies to facilitate modeling site, path, and source components of seismic hazard across the conterminous United States. The NCM is composed of a 1km grid of geophysical profiles, extending from the Earth’s surface into the upper mantle. It is constructed from a threedimensional (3D) geologic framework and geophysical rules that use (1) a petrologic and mineral physics database; (2) a 3D temperature model; and (3) a calibrated rock type- and age-dependent porosity model. Parameters needed to estimate site response for existing ground motion models (GMMs), including the time-averaged velocity in the upper 30 meters (VS30), the depths to 1.0 and 2.5 km/s shear-wave velocity (Z1.0 and Z2.5), and sediment thickness, can be computed from the NCM. As GMMs continue to improve in the future, other metrics could also be extracted or derived from the NCM, such as fundamental period, site attenuation (ko), a fully frequency-dependent site response function, or 3D geophysical volumes for wavefield simulations. Application of the NCM may also benefit other aspects of seismic hazard analysis, including better accounting for path-dependent attenuation and geometric spreading, more accurate estimation of earthquake source properties such as hypocentral location and stress drop, and calculation of crustal strength profiles that inform estimates of the base of seismicity.

conterminous United States

2024 Surprise Inlet landslides: Insights from a prototype landslide‐triggered tsunami monitoring system in Prince William Sound, Alaska

Alaska's coastal communities face growing landslide hazards owing to glacier retreat and extreme weather intensified by the warming climate, yet hazard monitoring remains challenging. As part of ongoing experimental monitoring in Prince William Sound, we detected three large landslides (0.5–2.3 M m 3 ) at Surprise Inlet on 20 September 2024, within the span of an hour. These events were identified in near real-time through seismic data and later confirmed using satellite imagery, tidal records, and infrasound. The landslides generated a modest tsunami, and a 4 cm wave was recorded by a tide gauge 18 km away, marking the first recorded landslide to reach water since monitoring began in this region in 2021. Here, we examine the detection and interpretation of these landslides using multiple data sources and modeling. We demonstrate the effectiveness of this regional seismic monitoring system and show how complementary instrumentation, where available, can enhance detection capabilities.

Alaska

Streams, springs, and volcanic lakes for volcano monitoring

Introduction Volcanic unrest can trigger appreciable change to surface waters such as streams, springs, and volcanic lakes. Magma degassing produces gases and soluble salts that are absorbed into groundwater that feeds streams and lakes. As magma ascends, the amount of heat and degassing will increase, and so will any related geochemical and thermal signal. Subsurface magma movement can cause pressurization that alters hydrostatic head and may induce groundwater discharge. Fluid-pressure changes have been linked to distal volcano-tectonic earthquakes (White and McCausland, 2016; Coulon and others, 2017) and phreatic eruptions (for example, Yamaoka and others, 2016). Clearly, changes in groundwater and surface waters are both indicators of unrest and clues to how and where magma is rising toward the surface. Where possible, it is prudent to incorporate real-time hydrologic data into multiparameter monitoring of restless volcanoes. Hydrologic dynamics can also be tracked by changes in groundwater levels that are commonly measured in shallow boreholes (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. ">chapter K , this volume, on boreholes; Hurwitz and Lowenstern, 2024). Although inferred to be common, relatively few volcano-hydrology anomalies are well documented, and many are essentially anecdotal (Newhall and others, 2001), reflecting the fact that high-resolution time series remain rare. Extreme examples include the 2008 eruption of Nevado del Huila, Colombia, where relatively minor phreatomagmatic eruptions were accompanied by expulsion of as much as 300 million cubic meters of groundwater from fissures high on the volcano (Worni and others, 2011), generating large lahars. Substantial decreases in flow rate from springs about 8 kilometers from the summit of Mayon Volcano, Philippines, have been noted before most eruptions in the 20th century (Newhall and others, 2001). Stream monitoring at Redoubt Volcano in 2009 allowed Werner and others (2012) to recognize that groundwater was unable to absorb (or scrub) the high flux of volcanic gas and that a high CO 2 /SO 2 precursor signal had been evident for 5 months prior to the eruption. A key to better interpreting hydrologic anomalies—or even identifying them—is therefore obtaining adequate baseline data. Most hydrologic monitoring at U.S. volcanoes has been accomplished by intermittent sampling surveys with annual or less frequent sampling (for example, https://hotspringchem.wr.usgs.gov/index.php ). More frequent sampling, however, generally is needed to establish reliable baselines. A recent hydrologic and hydrothermal monitoring experiment at 25 sites and 10 of the 12 level 4 (very high threat) volcanoes in the U.S. portion of the Cascade Range demonstrated that there is sufficient temporal variability in hydrothermal fluxes, even during quiescent periods, that one-time measurements will commonly have limited interpretive value (Crankshaw and others, 2018). Thus, surveys are best augmented with data from streamgages (for example, Evans and others, 2004; Bergfeld and others, 2008). Streamflow (water discharge) data allow measured temperature and specific conductance to be converted to heat and solute mass fluxes, which could be insightful parameters for detecting anomalous activity (McCleskey and others, 2012). At the Yellowstone Caldera, long-term monitoring of river solutes has allowed calculation of the chloride flux, a proxy for heat discharge (Hurwitz and others, 2007; McCleskey and others, 2016) from the subsurface magma. This is readily accomplished because data from streamgages are continuously recorded and archived by the U.S. Geological Survey (USGS) National Water Information System (NWIS) (USGS, 2024). Similar studies on stratovolcanoes or shield volcanoes would be scientifically useful, and yet are logistically challenging, requiring streamgages on numerous radial drainages complemented by either frequent manual sampling or numerous deployments of equipment to measure water temperature and specific conductance as a proxy for water chemistry. Another challenge is that some volcanic areas, especially shield volcanoes, are characterized by near-surface porous rocks and soils, such that surface streams are rare and replaced by distant, dilute large-volume springs with only a trace of any original volcanically sourced water (Manga, 2001; Hurwitz and others, 2021). Volcanic lakes are worthy of special attention for monitoring efforts, as their temperature and composition can provide evidence of increased flux of volatile-rich fluids from below. Quantifying changes in volatile and heat release from magma can be simpler in lakes than for volcanoes with radial drainages and no major lakes. Moreover, volcanic lakes pose a range of hazards themselves, including phreatomagmatic eruptions, debris flows, flank collapse, tsunamis, and toxic gas release (Mastin and Witter, 2000; Delmelle and others, 2015; Manville, 2015; Rouwet and others, 2015)—hazards that have historically been responsible for substantial loss of life at many volcanoes worldwide (Manville, 2015). Catastrophic CO 2 release at Lake Nyos, Cameroon, in 1986 suffocated about 1,750 people and about 3,500 livestock and was probably triggered by a large landslide into the gas-saturated lake (Kling and others, 1987; Evans and others, 1993). Gas-charged springs in Soda Bay within Clear Lake (California) have caused almost a dozen deaths to bathers in the past hundred years (ABC News, 2000). A 2005 example of lake overturn and abundant gas release was documented at Mount Chiginagak in Alaska (Schaefer and others, 2008) but did not result in any human casualties. Although thermally stratified lakes, which promote trapping of exsolved magmatic gas, tend to develop in tropical regions, the phenomenon can also arise where salinity creates meromixis (a condition in which a lake does not mix completely), as occurs in Mono Lake, California (Jellison and Melack, 1993; Jellison and others, 1998). If magma erupts or flows into a lake, the interaction between hot magma and cold water can be explosive (Mastin and others, 2004; Zimanowski and others, 2015) and substantially expand the area affected by the eruption. Another hazard is the breaching of crater rims by landslides triggered by volcanic and (or) seismic activity. Under some circumstances, substantial volumes of water can be displaced, leading to large floods and lahars. Late Holocene lake flooding from Aniakchak Crater in the Alaska Peninsula (Waythomas, 2022) and from Paulina Lake in Newberry Crater, Oregon (Chitwood and Jensen, 2000), caused by the failure of outlet sills, testify to the substantial hazards at lake-filled calderas. Several volcanic systems in the United States host lakes known to receive heat and gas from underlying magma. These lakes vary widely in area, depth, and chemical composition. Lakes are present at level 4 volcanoes, including Crater Lake and Newberry Volcano in Oregon; Yellowstone Caldera in Wyoming; Long Valley Caldera, Clear Lake volcanic field, Medicine Lake, and Salton Buttes in California; and Aniakchak Crater, Mount Katmai, Fisher Caldera, Mount Okmok, and Kaguyak Crater, among others, in Alaska. A water lake was present in Halemaʻumaʻu, the crater of Kīlauea, Hawai‘i (fig. F1), from October 2019 to December 2020. Level 3 volcanoes with lakes include Mono Lake volcanic field (Calif.), Mount Bachelor (Ore.), Ukinrek Maars and Mount Chiginagak (Alaska), and Soda Lake (Nevada). In addition, there are lakes at many levels 1 and 2 volcanoes. In the United States, there are no strongly acidic lakes that receive abundant input of magmatic gas, such as those found at Mount Ruapehu (New Zealand), Ijen and Kelud (Indonesia), and Poás (Costa Rica). Nevertheless, many contain fluids that provide clues to magmatic processes below. Since publication of a previous report on recommended instrumentation for volcano monitoring (Moran and others, 2008), continuous hydrologic monitoring has become increasingly feasible. However, changes in water pressure, temperature, and chemistry remain, in general, poorly studied phenomena at volcanoes (Sparks, 2003; National Academies of Sciences, Engineering, and Medicine, 2017). Recent efforts by the USGS have included the temporary study of Cascade Range volcanoes, which included frequent (15 minute to hourly) temporal sampling of temperature, depth, and conductivity (Crankshaw and others, 2018; Ingebritsen and Evans, 2019). At Yellowstone Caldera, many streamgages have now added thermistors and specific conductance sensors, allowing estimation of time-dependent chloride flux as a proxy for variations in subsurface heat flux (McCleskey and others, 2012, 2016). Efforts to better understand lakes have also accelerated, with bathymetric mapping and sampling carried out at several locations in the United States. Especially thorough work was done at Yellowstone Lake thanks to the Hydrothermal Dynamics of Yellowstone Lake (HD-YLAKE, https://hdylake.org ) project, funded primarily by the National Science Foundation. In addition to geophysical surveys and recovery of cores and other samples, HD-YLAKE investigations included remotely operated vehicle (ROV) investigations of hydrothermal vents on the lake floor (fig. F2). Data collected by the ROV provided a better understanding of the thermal and chemical influx from lake-bottom hydrothermal systems (Sohn and others, 2017). In this chapter, we focus on detecting changes in the chemistry, temperature, discharge, or water levels of streams, springs, and lakes that can be caused by seismicity, volumetric strains, or increases in gas flux associated with ascending magma. There is unavoidable overlap with other chapters of this report. Samples of water and gas can also be obtained in boreholes ( of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. ">chapter K , this volume; Hurwitz and Lowenstern, 2024), both shallow and deep. Gas monitoring ( of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–E, 11 p., https://doi.org/10.3133/sir20245062e.">chapter E , this volume; Lewicki and others, 2024) relies in part on samples from springs and wells, particularly where measurable gas plumes are absent. Water acts as a trigger and lubricant for landslides and sediment-rich floods, and so hydrology has obvious relevance for lahar monitoring, as discussed in of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–H, 6 p., https://doi.org/10.3133/sir20245062h. ">chapter H (this volume; Thelen and others, 2024). Shared situational awareness among scientists engaged in geophysical, gas, and hydrologic monitoring will improve overall understanding of the volcanic hazard.

Scientific Investigations Report

The potential impact of three-dimensional distributed slip models derived from real-time GNSS data on the performance of the ShakeAlert earthquake early warning system for slab interface earthquakes

The ShakeAlert® earthquake early warning (EEW) system is designed to warn users of imminent strong ground motion with sufficient time to take protective actions. ShakeAlert currently uses three algorithms to characterize the earthquake source. One estimates the location and magnitude using the first few seconds of the P wave and, while fast, tends to underestimate magnitude for M w 7.0+ earthquakes. A second estimates the location, orientation, length, and corresponding magnitude of a line source using observed peak ground acceleration and contributes primarily to M w 5.5+ earthquakes. The third infers earthquake magnitude from peak ground displacement measured using Global Navigation Satellite System (GNSS) data and offers nonsaturating magnitudes for M w 7.0+ earthquakes. Other EEW algorithms exist that infer temporally evolving spatially variable slip on a 3D fault surface from real‐time GNSS data, information that might enable more accurate and timely alerts in the event of large‐magnitude subduction interface earthquakes. Here, we evaluate the potential contribution of one such algorithm, BEFORES ( Minson et al. , 2014 ), to improve ShakeAlert performance through a simulated real‐time implementation of Bayesian evidence‐based fault orientation and real‐time earthquake slip (BEFORES) and other ShakeAlert algorithms using data for eight M w 7.6+ earthquakes. The test results demonstrate that BEFORES can produce well‐constrained and accurate magnitude estimates as soon as or sooner than other EEW algorithms, in turn enabling it to increase the amount of warning time users receive in many cases. However, with a modified Mercalli intensity (MMI) threshold of 3.5, which is commonly used for issuing alerts, BEFORES would tend to alert large geographic regions that did not feel strong shaking (MMI 6+). This effect can be mitigated using a higher alert threshold of MMI 4.5 without negative impact on the amount of warning time obtainable with BEFORES.

Bulletin of the Seismological Society of America

A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications

The U.S. Geological Survey collects remote sensing data to support national scientific assessments of natural resources, hazards, and landscape change. Spectrometers and spectroradiometers are essential for gathering point-based spectral measurements used in applications such as uncrewed aerial systems (UAS) multispectral image calibration, validation, and analysis. Evaluating how different instruments perform in laboratory and field environments helps determine whether they provide consistent, interoperable measurements. Such verification can expand access to spectral ground data during UAS operations by allowing scientists to use alternative instruments when budgets, logistics, or field conditions limit options. We propose and test a methodological framework for evaluating spectrometers for measurement consistency during UAS multispectral vegetation mapping applications. There are three central evaluation components to the framework: laboratory, field, and relative to UAS multispectral imagery. By evaluating the instruments in both relatively controlled and uncontrolled environments, we thoroughly examine measurement consistency and when/why measurements may differ. We opportunistically selected two instruments for a case study in a coastal marsh setting: a compact laboratory spectrometer we modified for field use and a field-ready spectroradiometer. The instruments produced consistent measurements in both environments. We found differences between the field spectra and UAS spectra that likely reflect the perspectives of ground vs. aerial data and indicate that further radiometric calibration may be needed.

Massachusetts

Assessment of the interconnection between Tampa Bay and the Floridan aquifer system: Historical groundwater data compilation and analysis, 1976–2022

The U.S. Geological Survey used existing data collected after the last major navigational channel modification in the mid-1980s to investigate groundwater levels and chloride concentrations in wells in the Floridan aquifer system and other aquifers beneath and near Tampa Bay. Tampa Bay is located on the west-central coast of Florida and provides access for commercial shipping. In 2021, the U.S. Army Corps of Engineers began to investigate alternatives to improve the efficiency of the deep-draft navigation channels within Tampa Bay, reduce costs, improve safety, and analyze the implications of modifying navigational channels. The Floridan aquifer system underlies Tampa Bay and is the primary source of public water supply in the region. Modifications to the channels have the potential to expose the Floridan aquifer system to the saltwater in Tampa Bay, with the potential to increase salinity in wells in the region. Other factors affecting the groundwater levels and the location of the freshwater/saltwater interface were also examined, including changes in sea level, groundwater extraction, and variations in climate. Groundwater levels and well-construction reports were used to identify whether different aquifer units are well-connected. Twelve wells had available data before and after the last major channel modifications, which took place in the 1980s, with six datasets of chloride concentration available in areas along the northern and eastern coastline of Tampa Bay, which is nearest to historical dredging activities. Of these six, Kendall’s τ and p -values indicated increasing trends in chloride concentration for three datasets (TR 11-2, TR 10-2, 51), no trend in chloride concentration for two datasets (TR 9-3, 50), and a decreasing trend in chloride concentration for one dataset (TR 9-1). The upward trends in chloride concentration observed for TR 10-2 and 51 are likely the result of changes in local groundwater withdrawals. Well TR 11-2 had a gradual increasing trend in chloride concentration, fresh groundwater throughout the period of record, and a 3- to 4-foot increase in hydraulic head during the period of record, possibly caused by the construction and control of the Tampa Bypass Canal, resulting in changes to the regional potentiometric surface.

Florida

Chloride concentrations in groundwater from the western part of the Southern Hills regional aquifer system, Louisiana, 2021–22

Groundwater is heavily used for public supply and industrial uses in the Baton Rouge, Louisiana, area. Lowered water levels resulting from groundwater withdrawals have induced the movement of saltwater towards wells in East Baton Rouge and West Baton Rouge Parishes. Saltwater intrusion has the potential to affect water supply infrastructure, reduce water availability for some uses, and increase treatment costs. To document current conditions, samples were collected from 161 wells screened in 10 aquifers of the Southern Hills regional aquifer system during November 2021 through February 2022. The results were compared with historical data to identify where chloride concentrations are increasing, which could indicate that saltwater intrusion is occurring. Saltwater intrusion, to varying degrees and areal extents, was observed in most of the 10 aquifers. The limited availability of monitoring wells near or within some of the known saltwater plume areas restricts tracking of the movement or delineation of the plumes’ current extents.

Louisiana

Exploration for blind geothermal systems in the eastern Great Basin of Utah: An update on the “Lund North” INGENIOUS detailed study site

Existing geothermal production in Utah is commonly collocated with surficial expressions of geothermal heat including active hot springs and hot spring deposits. However, geothermal potential across the Great Basin region is thought to be much higher for hidden or blind geothermal systems. Accordingly, exploration techniques that can locate geothermal resources that lack surface thermal features could support future development of these systems. The goal of the INGENIOUS project is to reduce exploration risk and discover new, economically viable hidden geothermal systems in the Great Basin region. This paper summarizes the efforts and preliminary results of blind geothermal resource prospecting in Utah as part of the larger INGENIOUS project. The Lund North site in the Basin and Range province of southwest Utah was designated as the fourth detailed study site for the project. The site was initially identified from the preliminary Play Fairway Analysis (PFA) geothermal favorability map, which is based on various data elements, and the identification of favorable structural settings across Utah. This site contains existing legacy data including a thermal gradient borehole with a heat-flow value exceeding 220 mW/m 2 . New data collected at this site include terrestrial gravity, magnetotellurics, transient electromagnetics, fluid geochemistry, geologic mapping, UAV-based lidar, paleomagnetism, aeromagnetic surveys, and a shallow temperature survey. Preliminary data and model interpretations corroborate the presence of a large, east-dipping, northeast-southwest-trending normal fault on the edge of a typical Basin and Range graben. Quaternary fault mapping refined by high-resolution lidar surveys suggests a complex step over fault geometry. Utilizing multi-disciplinary datasets for further site assessment at Lund North will facilitate the development of a local-scale PFA and geothermal conceptual model. This new data will be used to site successive thermal gradient drilling to verify heat flow with temperatures at depth at the Lund North site and further investigate the existence of a local geothermal system.

Utah

Conventional hydrothermal power-producing systems of the Great Basin, USA

As part of the update to the electric-grade conventional hydrothermal assessment of the Great Basin, USA, Monte Carlo analyses of identified resources within explored regions will be performed to make estimates of discovered resources and associated uncertainty. Analyses use conditional statistics where estimates are conditioned upon a hydrothermal favorability map, allowing for the likelihood that more resources exist in regions of higher hydrothermal favorability. For these analyses, a dataset of identified hydrothermal systems is compiled, and the new compilation is described herein. Recognizing that a single hydrothermal system may be developed with multiple power plants, and that the hydrothermal upflow zone may be several kilometers across with many measurements characterizing a single hydrothermal system, a procedure was developed and employed to create clusters of points (power plants, measurements, etc.) that are associated with a single system, and a new central point was defined as the best estimator of the center of the hydrothermal system. Hydrothermal systems were uniquely identified by grouping electric-grade hydrothermal measurements and operating power plants within a distance of 10 km. Groups that are >10 km apart are assumed to be different electric-grade hydrothermal systems. While 10 km was used as the threshold, most systems were significantly further apart, and most points within groups were typically within 5 km of each other. A well measurement was considered an electric-grade measurement of a hydrothermal system if it had two properties: a measured temperature of >85 °C and evidence of hydrothermal convection. Other points that were added to the dataset are locations of operating powerplants or locations that have been classified as an electric-grade hydrothermal resource by either the U.S Geological Survey (USGS) or the Great Basin Center for Geothermal Energy. After all points are assigned to systems, new points were computed with the goal of identifying the center of the throat of the hydrothermal upflow zone. If operating powerplants exist for a system, then the arithmetic average of all power plant locations is used. Otherwise, if USGS made an estimate, that location is used. In the absence of both powerplants or USGS estimates, the arithmetic average of all electric-grade measurement locations is used. An example is shown of how these newly compiled locations might be ranked for uncertainty analyses, where higher confidence is assumed if measured temperature is higher and there are many supporting measurements indicating an electric-grade resource. In summary, 28 systems have operating power plants, an additional 78 systems are known identified electric-grade hydrothermal resources, and 99 new systems were identified as probable electric-grade systems with varying levels of confidence. These 205 locations are shown as a function of a recent hydrothermal favorability map, conceptually illustrating the conditional statistics that can be used to make estimates of the undiscovered resources of the Great Basin. An accompanying data release provides summaries of developed capacity by system and USGS estimates of likely total capacity and associated uncertainty.

Arizona, California, Idaho, Nevada, Oregon, Utah

Geophysical modeling of a possible blind geothermal system near Battle Mountain, NV

The northeastern portion of the Reese River basin in north-central Nevada is the focus of detailed geophysical and geological studies as part of the INGENIOUS project, which aims to identify new, commercially viable hidden geothermal systems in the Great Basin region of the western U.S. This location, herein referred to as Argenta Rise, occupies a broad (~15km wide) left-step between major range-front fault systems along the northwestern edge of the Shoshone Range and Argenta Rim, with numerous ENE-striking intra-basin faults presumably accommodating sinistral-normal oblique slip across the step-over. Four discrete regions have been identified within the study area that have favorable structural settings for hosting a blind hydrothermal system. However, with no definitive or extensive surface manifestations of an active hydrothermal system (e.g., geysers, steam vents, sinter, etc.), detailed geophysical studies are necessary to resolve subsurface geology and structure, and identify zones of enhanced structural complexity that may promote hydrothermal fluid flow. Hence, we collected high-resolution gravity, MT, and rock property data (density, magnetic susceptibility), and analyzed the recently acquired GeoDAWN aeromagnetic data to characterize potential geothermal resources in this region. Using the new geophysical datasets, we jointly modeled gravity and magnetic data along a series of intersecting 2D profiles that integrated information from recent, local-scale fault mapping. Rock property measurements performed on outcrops and hand samples throughout the study area constrained the models. The MT data were used to construct a 3D resistivity model that highlights the location of inferred alteration and fluids in the subsurface. Combined MT and potential field results reveal which structures may be most important for controlling hydrothermal fluid migration, as well as which geologic units may host hydrothermal fluids. Our gravity derived depth to basement surface coincides well with the base of shallow conductive anomalies, suggesting hydrothermal fluids may be confined to basin fill sediments and volcanics. This work supports our development of 3D geophysical and geologic models that are focused along the western flank of the northern Shoshone Range and aids the process of selecting sites for temperature gradient drilling.

Nevada

Water quality of the Boca Raton canal system and effects of the Hillsboro Canal inflow, southeastern Florida, 1990-91

The City of Boca Raton in southeastern Palm Beach County, Florida, is an urban residential area that has sustained a constant population growth with subsequent increase in water use. The Boca Raton network of canals is controlled to provide for drainage of excess water, to maintain proper coastal ground-water levels to prevent saltwater intrusion, and to recharge the surficial aquifer system from which the city withdraws potable water. Most of the water supplied to the Boca Raton canal system and the surficial aquifer system, other than rainfall and runoff, is pumped from the Hillsboro Canal. The Biscayne aquifer, principal hydrogeologic unit of the surficial aquifer system, is highly permeable and there is a close relation between water levels in the canals and the aquifer. The amount of water supplied by seepage from the conservation areas is unknown. Because the Hillsboro Canal flows from Lake Okeechobee and Water Conservation Areas 1 and 2, which are places of more highly mineralized ground water and surface water, the canal is a possible source of contamination. Water samples were collected at 10 canal sites during wet and dry seasons and analyzed for major inorganic ions and related characteristics, nutrients, and trace elements. All concentrations were generally within or less than the drinking-water standards established by the Florida Department of Environmental Protection. The high concentrations of sodium and chloride that were detected in samples from the Boca Raton canal system are probably from the more mineralized water of the Hillsboro Canal. Other water-quality data, gathered from various sources from 1982 through 1991, did not indicate any significant changes nor trends. The data include pesticide and metal analyses of water samples and bottom sediments collected at four canal sites in the Boca Raton study area by the U.S. Geological Survey during 1982-84. The effects of the Hillsboro Canal on the water quality of the Boca Raton canal system are indicated by increased concentrations of sodium, chloride, dissolved solids, and total organic carbon. Concentrations of the constituents in the canal water generally decrease with distance from the Hillsboro Canal pumping station and are the result of dilution by receiving canal waters.

Florida

Geochemical, mineralogical, and isotopic evidence for multi-stage genesis of the Hicks Dome REE + Y-HFSE-fluorite deposit, Illinois, USA

Hicks Dome hosts breccias enriched in rare earth elements (REE), Y, Th, F, Ba, Ti, Nb, and Be, alongside spatially associated lamprophyre dikes (ca. 271 Ma). Hicks Dome is located within the Illinois–Kentucky Fluorspar District, which hosts fluorite, Pb–Zn, and barite resources. This study investigates the genetic relationships between Hicks Dome mineralization in breccias, alkaline magmatism, and Illinois–Kentucky Fluorspar District mineralization. Lamprophyre dikes are light REE–enriched with chondrite-normalized abundances decreasing from La to Lu. The Host Breccia exhibits middle and heavy REE–enriched patterns that mirror those of the principal REE–Th host minerals, including fluorapatite, xenotime, and thorite. Textural evidence suggests recrystallization of phosphates, sulfates, and Ti–Nb oxides in the Host Breccia. U–Pb geochronology constrains multiple mineralizing events, with ages of 277 ± 18 Ma from low-Th apatite interpreted as main-stage mineralization, and 121.6 ± 9.7 Ma from high-Th apatite indicating later overprinting. O–H–C stable isotope data provide evidence for multiple stages of fluid-rock interaction and fluid mixing: (1) early magmatic fluids dissolved limestone country rock, (2) mixing between magmatic fluids and basinal brines led to main-stage mineralization in the Host Breccia, and (3) late-stage mineralization occurred following mixing of meteoric water and basinal brine. These results indicate that heavy REEs, high field strength elements, and fluorine precipitated proximal to its alkaline magmatic source because of fluid–rock interactions and fluid mixing. Subsequent fluid mixing drove late-stage recrystallization and additional fluorite formation, a process that may be similar to mineralization in the Illinois-Kentucky Fluorspar District.

Illinois

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

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water

Status and performance of the ShakeAlert® earthquake early warning system: 2019-2023

The U.S. Geological Survey (USGS)‐operated ShakeAlert® system is the United States West Coast earthquake early warning system ( Given et al. , 2018 ). In this study we detail ShakeAlert’s performance during some of the largest events seen by the system thus far. Statewide public alerting using ShakeAlert messages was authorized in California in October 2019. Over the next few years, public alerts were expanded into Oregon and then into Washington ( U.S. Geological Survey, 2024 ). ShakeAlert source results are routinely compared to the USGS Comprehensive Catalog (ComCat; Guy et al. , 2015 ; U.S. Geological Survey, Earthquake Hazards Program, 2017 ), which contains the earthquake location and magnitude determined using complete waveform data. M 4.5 and larger is the threshold used for public alerting and was deliberately set below the level where damage is likely to compensate for cases where the system underestimates the magnitude. Between 17 October 2019 and 1 September 2023, the ShakeAlert system created 95 events with maximum magnitude estimates of M ≥4.5, the public alerting threshold. 94 of the 95 events were due to real earthquakes. Seven were categorized “false” per ShakeAlert’s internal definition that there was no matching catalog event within 100 km and 30 s of origin time; however, all but one of these were real earthquakes that were poorly located, primarily because they were at the edges of the seismic network. Three detected events were labeled “missed” because they were very poorly located (>100 km location error). In addition, the system did not produce solutions for four ComCat events M ≥4.5 ( U.S. Geological Survey, Earthquake Hazards Program, 2017 ), which were all at the edge of the alerting and network boundaries. The ShakeAlert system has accurately detected the majority of earthquakes that have occurred within the operational region since completing the public rollout, and alerts from the system have been delivered to millions of cell phone users throughout the West Coast.

California, Oregon, Washington