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Extracting data from maps: Lessons learned from the artificial intelligence for critical mineral assessment competition

The U.S. Geological Survey (USGS), Defense Advanced Projects Research Agency (DARPA), NASA Jet Propulsion Laboratory (JPL), and MITRE ran a 12-week machine learning competition aimed at accelerating development of AI tools for critical mineral assessments. The Artificial Intelligence for Critical Mineral Assessment Competition solicited innovative solutions for two challenges: 1) automated georeferencing of historical maps, and 2) automated feature extraction from historical maps. Competitors used a new dataset of historical map images to train, validate, and evaluate their models. Automated georeferencing pipelines attained a median root-mean square error of 1.1 km. Prompt-based extraction (i.e., with user input) of polygons, polylines, and points from geologic maps yielded median F1-scores of 0.77, 0.56, 0.35, respectively. Geologic maps pose numerous challenges for AI workflows because they vary significantly. However, despite its short duration, the competition yielded promising results that have since spurred further innovation in this area and led to the development of new AI tools to semi-automate key, time-consuming parts of the assessment workflow.

Applied Computing and Geosciences

Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia

Active volcanic systems pose serious hazards to people and property including inundation and incineration by lava, blanketing by tephra (volcanic ash), exposure to noxious volcanic gases, and damage from shallow earthquakes triggered by ascending molten material (magma). To improve understanding of volcanism and associated seismicity on the western Arabia Plate, the Saudi Geological Survey and the U.S. Geological Survey conducted a multi-year investigation of the northern Harrat Rahat volcanic field adjacent to the city of Al Madīnah al Munawwarah, Kingdom of Saudi Arabia. Project components included creation of a high-resolution digital topographic base; interpretation of eruptive history supported by detailed geologic mapping, paleomagnetism, and abundant high-precision geochronology of volcanic deposits; assessments of eruptive styles and volcanic hazards by physical volcanology; investigation of the origins of magmas in the mantle and of their differentiation in the crust revealed by chemical and isotopic petrology; gravity and magnetotelluric surveys to reveal crustal structures and to search for magma reservoirs; and regional and local seismic tomography and analyses of seismic hazards. Project results are presented in this Professional Paper as chapters written for technical scientific audiences.

Professional Paper

U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33

Executive Summary Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak to the need for nationwide interest and investment in earthquake hazard characterization and risk reduction. Authorized under the Earthquake Hazards Reduction Authorization Act, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) provides the scientific information, situational awareness, and knowledge necessary to reduce deaths, injuries, and economic losses from earthquakes and earthquake-induced tsunamis, landslides, and soil liquefaction. The EHP supports activities in three focused topical areas: (1) earthquake monitoring, (2) hazard assessment, and (3) applied research, using the results of each—and the coordination among them—to further support risk translation and communication in regions at risk nationwide. For earthquake monitoring, the Advanced National Seismic System (ANSS), a cooperative effort of USGS networks, university partner regional seismic networks, and real-time geodetic networks, collects and analyzes data on earthquakes; issues timely, reliable notifications of their occurrence and impacts; and provides data for earthquake research, hazard, and risk assessment as a foundation for building an earthquake-resilient Nation. The USGS-operated ShakeAlert Earthquake Early Warning system is a recent addition to EHP’s ANSS infrastructure. In the realm of earthquake hazard assessment, the EHP contributes to earthquake risk mitigation strategies by developing the National Seismic Hazard Model and maps, and other related products, that describe the likelihood and potential effects of earthquakes nationwide, especially in the urban areas of highest risk. The EHP also conducts research on the causes, characteristics, and effects of earthquakes and prioritizes work that directly increases the accuracy and precision of earthquake hazards assessments, earthquake forecasts, and earthquake monitoring and situational-awareness products and that supports the Nation’s earthquake mitigation practices. Bridging the EHP’s efforts across research, hazard assessments, and earthquake monitoring is a broad and comprehensive collection of earthquake information products, including the National Seismic Hazard Model, ShakeAlert, and other products describing impact, such as ShakeMap and PAGER (Prompt Assessment of Global Earthquakes for Response), which have been developed and integrated into EHP’s real-time monitoring systems. EHP funds external partners to carry out many important collaborative activities through an active external grants program—one of the largest in the USGS—and through cooperative agreements with other partners such as the university-operated regional seismic networks, funded as part of the ANSS. To continue its support of earthquake hazard characterization and risk reduction, the EHP aims to strengthen its foundational products and practices while positioning itself to respond to the evolving needs of the Nation and follow best practices of the scientific community. This document describes a strategy for the program to ensure it can meet these demands. The foundational priorities outlined in this strategy represent those activities that remain critical to the core functionality of the program and those that can be supported under current fiscal year 2024-level appropriations. Priorities described as aspirational are important for future growth, and to maintain the program’s position as a leading global resource in earthquake science, but would require increases in appropriated funding to be fully realized. Across the program’s portfolio of activities, several major themes have been identified as the most critical activities to advance EHP science over the coming decade. Together, these activities provide the framework necessary to integrate critical hazard characterization and risk reduction activities across the program. They provide the structure for research to advance the understanding of where, when, and why earthquakes occur and how we can use improved knowledge to drive short-term and actionable forecasts of seismic activity. They expand the usefulness of critical earthquake products and advance the sophistication of those products to keep pace with the rapidly evolving needs of an ever-expanding user base while maintaining the position of the USGS as a global leader in earthquake science. Focus on system-level science. Establish an automated earthquake-processing pipeline. Enhance the accuracy and reliability of the ShakeAlert Earthquake Early Warning system and plan for extension to other regions. Implement time-dependent earthquake forecasting. Develop physically realistic models. Expand computational capacity. This science strategy is organized into three primary sections. The first section provides an overview of the EHP and its budget, governance, and program council. Readers familiar with the program may wish to focus on the second section, which describes the core of the science strategy, including priorities across each of the EHP’s major program activities in monitoring, hazard assessment, and targeted research. The third section outlines science priorities that cut across program activities, including those involving collaborations external to the EHP.

American Samoa, Guam, Northern Marianas Islands, U

Synergy between geology and geophysics in graphite mineral resource assessment

Graphite is designated as a critical mineral by the U.S. Government due to its essential role in modern technology and its vulnerability to supply chain disruption. To evaluate domestic graphite resources, the U.S. Geological Survey (USGS) conducted two airborne electromagnetic (AEM) surveys as part of the Earth Mapping Resources Initiative (Earth MRI) over prospective areas in the southern Appalachians of Alabama and the Seward Peninsula of Alaska. These surveys aimed to refine areas of interest by revealing subsurface electrical resistivity patterns indicative of graphite-bearing rocks. The results of the AEM surveys were integrated with existing geological knowledge and supplemented by field observations to assess the likelihood of undiscovered resources in these regions. This multidisciplinary approach combined geophysical techniques with traditional geological methods, enhancing the understanding of graphite potential in areas that may have been previously overlooked. The findings from this initiative are expected to contribute significantly to the ongoing efforts to secure a reliable domestic supply of graphite, thereby reducing import reliance and supporting national interests in mineral resource management.

Conference Paper

Updating the crustal fault model for the 2023 National Seismic Hazard Model for Alaska

We present the crustal fault model for Alaska, based on geologic observations, as a primary input for the 2023 revision of the U.S. Geological Survey National Seismic Hazard Model. We update the 2013 Alaska Quaternary fault and fold database to produce a simplified model of 105 fault sections and four fault zone polygons with basic geologic parameters including slip sense and rate. Significant updates include the following: (1) a slip rate of ∼53 mm/year on the Queen Charlotte Fault indicating it accommodates all of the plate boundary motion; (2) quantified slip rates on megathrust splay faults in the southern Prince William Sound region and near Kodiak Island; (3) improved details of structures in the Chugach-St. Elias orogen; (4) revision of the Castle Mountain Fault from right-lateral slip to a predominantly reverse fault; (5) improved Interior Alaska tectonic models that clarify relationships between the Denali, Totschunda, and thrust faults on both sides of the Alaska Range; (6) identified large earthquake sources in the eastern Brooks Range; and (7) omission of the Chatham Strait section of the Denali Fault. The fault model underscores that the collision of the Yakutat microplate is the dominant driver of active crustal faulting in most of Alaska.

Alaska, Yukon

Three-dimensional hydrogeologic framework model of the Russian River watershed, California

The Russian River watershed is in northern Sonoma County and southern Mendocino County, California, in the northern part of the California Coast Ranges. The Russian River serves as a supply for agricultural irrigation and for municipal, domestic, and commercial uses. Through a cooperative agreement with the California State Water Resources Control Board and Sonoma County Water Agency, the U.S. Geological Survey has completed studies to better understand the hydrogeologic system and develop numerical hydrologic modeling tools to evaluate and aid in managing groundwater resources. This report focuses on the development of a digital three-dimensional hydrogeologic framework model of the Russian River watershed for use in groundwater resource assessment and numerical models. The digital three-dimensional hydrogeologic framework model of the Russian River watershed portrays the altitude, thickness, and extent of five hydrogeologic units. These five hydrogeologic units include (1) a basement unit, (2) the Sonoma Volcanics, (3) a consolidated sedimentary rock unit, (4) an unconsolidated sediment unit, and (5) channel alluvium. Model input data were compiled from published geologic maps, interpreted well data, and a model of the top of basement derived from gravity data. These data were used to construct surfaces that represent the upper and lower subsurface boundaries of each hydrogeologic unit. Top surfaces were created for the five hydrogeologic units and then stacked in three dimensions to create a solid-volume digital model. The digital three-dimensional hydrogeologic framework model described in this report and the corresponding data represent the generalized geometry of the subsurface geologic units; the model reproduces the input geologic data with reasonable accuracy and is consistent with previously published subsurface conceptualizations of the region. The model indicates the overall geometry of the basement within the watershed and the spatial extent, altitude, and thickness of the basin-filling units. The hydrogeologic framework model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.

California

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina

Separating signals in elevation data improves supervised machine learning predictions for hydrothermal favorability

A recent study identified topography (land surface elevation above sea level) as an important input dataset (feature) for predicting the location of hydrothermal systems in the Great Basin in Nevada. Yet, topography is generally a result of more than one geological process and may consequently contain multiple distinct signals. For example, the geologic evolution of the Great Basin has produced both crustal thickening (i.e., regional-scale trends in elevation) and thinning via Basin and Range extensional faulting (i.e., valley-scale topographic relief). We postulate that these geologic processes may affect the occurrence of hydrothermal systems differently. Therefore, we separate the regional trend from the valley-scale signal in the Great Basin, and then use them separately to evaluate the importance of each as predictors for hydrothermal favorability. Our prior work applying supervised machine learning (ML) using the data from the Nevada Machine Learning Project demonstrated that employing a training strategy that randomly selects negative training sites produces better performing models for predicting hydrothermal favorability than a training strategy that uses expert-selected negatives. The models created using both training strategies exhibited a west-east geographic trend in the predictions for the favorability of hydrothermal resources. These models generally predicted higher favorability in western Nevada and lower favorability in eastern Nevada. This west-east trend in predicted favorability correlates with elevation across the Great Basin, which trends higher from west to east. By separating the original elevation feature into distinct features for elevation trend (i.e., regional-scale topography) and detrended elevation (i.e., valley-scale or local relative topography), we find that models using the separated topographic signals consistently outperform competing models that use the original elevation feature. Although western Nevada still exhibits higher favorability than eastern Nevada, using separated signals for regional elevation and local structure reduces the west-east prediction trend in the region and emphasizes structures associated with hydrothermal upflow. This work emphasizes how carefully engineering features to represent geological conditions relevant to hydrothermal systems allows ML algorithms to detect important patterns for predicting hydrothermal resource favorability and leads to better model performance.

Conference Paper

Albuquerque Seismological Laboratory strategic vision

This circular presents a strategic outlook for the U.S. Geological Survey (USGS) Albuquerque Seismological Laboratory (ASL) for the next 10 years (2026–36). The ASL is a USGS field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. The strategic outlook is categorized into two types of tasks: “Foundational Tasks” and “Aspirational Tasks.” Foundational Tasks are those that maintain the laboratory’s basic operations and services, including regional and global seismic monitoring, improving data quality, and providing instrument testing and support. A suite of Aspirational Tasks is also articulated; these can be considered priority targets of ASL that could improve ASL’s seismic monitoring capabilities and mission. Such tasks include improvements to remote stations, testing capabilities of nonseismic geophysical instruments, detection threshold monitoring, rapid aftershock deployments, and expanding seismic monitoring networks. This report was written with input from the USGS Geological Hazards Science Center, the USGS Earthquake Hazards Program (EHP), and colleagues with an interest in the work done by the ASL. Although the details of these tasks may change, this document can provide guidance on the overarching tasks at the ASL from 2026 to 2036 and an overview of the various components of the ASL and how they fit into the EHP and the Global Seismographic Network Program.

Circular

Bathymetric and acoustic-backscatter mapping of Lake Sammamish, Washington, during USGS field activity 2021-656-FA

In 2021, scientists from the U.S. Geological Survey (USGS) acquired bathymetric and acoustic-backscatter data within Lake Sammamish, Washington. Mapping was completed to find evidence of past earthquakes such as underwater landslides and is part of a larger USGS project to understand the overall geologic hazards history of the Cascadia Margin region. The survey was conducted using the USGS research vessel Parke Snavely outfitted with an interferometric sidescan-sonar system for swath mapping. Three estimates of bathymetric uncertainty were calculated from the post-processed bathymetric data. This report provides a summary of the mapping mission.

Washington

Three-dimensional temperature maps of the Williston Basin, USA: Implications for deep hot sedimentary and enhanced geothermal resources

As part of U.S. Geological Survey's (USGS) efforts to identify and assess geothermal energy resources of the US, a three-dimensional (3D) geologic and thermal model has been constructed for the Williston Basin, USA. The geologic model consists of all sedimentary units above the Proterozoic and Archean crystalline rock (called basement herein), with a total sedimentary thickness of up to 5 km near the basin center. Twenty-nine geologic units were mapped from interpreted formation tops from 16,465 wells. A 3D temperature model was constructed to a depth of 7 km by constructing a 3D heat flow model for the sedimentary units, followed by estimating underlying temperature using a one-dimensional (1D) analytic solution for heat flow within the underlying crystalline basement. Using the sedimentary basin model, heat flow was simulated in 3D and was calibrated using three temperature datasets: 1) 24 high-confidence static temperature logs (equilibrium thermal profiles), 2) more than15,000 drill stem test (DST) measurements from >7,000 wells, and 3) more than 45,000 bottomhole temperature (BHT) measurements from >14,000 wells. The DST and BHT datasets provide broad spatial coverage, but are lower confidence, primarily because measurements were made prior to attaining thermal equilibrium. DST and BHT measurements were binned regionally to develop representative thermal profiles that generally agree with these lower quality data (hereafter called pseudowell temperature profiles). Layer properties (primarily thermal conductivity and compaction curves) were set to best estimate values, then the heat flow model was calibrated to fit pseudowell and static temperature logs primarily by adjusting basal heat flow to approximate the overall temperature profile. Minor adjustments to thermal conductivity allowed adjusting changes in slope at lithologic contacts. Resulting maps include 3D temperature and basal (bottom of sedimentary units) heat flow estimates, which are used as input for the temperature model of the basement. The crystalline basement temperature model uses an analytic 1D solution to the heat flow equation that requires estimates of heat flow and temperature at the upper boundary (i.e., the sediment/basement contact), radiogenic heat production within the crystalline basement, and reference thermal conductivity (i.e., uncorrected for temperature). Two regions of high heat flow are identified: 1) in western North Dakota along the North American Central Plains Conductivity Anomaly and 2) in eastern Montana near the Poplar dome. Within the sedimentary column in the center of the basin of the basin, an area of approximately 100,000 km2 is predicted to have moderate- to high-temperature geothermal resources (>90 °C) under the thickest sequences of sediments. Where thick insulation and high heat flow coincide, electric-grade resources can be less than 4 km deep. Assuming a maximum feasible drilling depth of 7 km, temperatures are predicted to be as high as 175 °C. The geologic model may be used to identify strata at sufficient temperatures that may have natural permeability or that may have conditions that favor development of enhanced/engineered geothermal systems resources.

Montana, North Dakota, South Dakota

A high-resolution 3-D P-wave velocity structure of the south-central Cascadia subduction zone from wide-angle shore-crossing seismic refraction data

This study addresses a significant gap in understanding the features of the south-central Cascadia subduction zone, a region characterized by complex geologic, tectonic, and seismic transitions both offshore and onshore. Unlike other segments along this margin, this area lacks a 3-D velocity model to delineate its structural and geological features on a fine scale. To address this void, we developed a high-resolution 3-D P-wave velocity model using active source seismic data from ship-borne seismic shots recorded on temporary and permanent onshore seismic stations and ocean-bottom seismometers. Our model shows velocity variations across the region with distinct velocity-depth profiles for the Siletz, Franciscan, and Klamath terranes in the overlying plate. We identified seaward dipping high-velocity static backstops associated with the Siletz and Klamath terranes, situated near the shoreline and further inland, respectively. Regions of reduced crustal velocity are associated with crustal faults. Moreover, there is significant along-strike depth variation in the subducting slab, which is about 4 km deeper near the thick, dense Siletz terrane and becomes shallower near the predominantly less-dense Franciscan terrane. This highlights a sudden tectonic and geologic transition at the southern boundary of the Siletz terrane. Our velocity model also indicates slightly increased hydration, though still minimal, in both the oceanic crust and the upper mantle of the subducting plate compared to other parts of the margin.

British Columbia, California, Oregon, Washington

Geochemical geodatabase of sedimentary strata (coal, coal-adjacent rocks, tuffaceous oil shale, phosphate-rich rocks) and produced water in the Uinta region, Utah and Colorado

The Geochemical Geodatabase of Sedimentary Strata (Coal, Coal-adjacent Rocks, Tuffaceous Oil Shale, Phosphate-rich Rocks) and Produced Water in the Uinta Region, Utah and Colorado, consists of compiled datasets acquired as part of the Carbon Ore, Rare Earth, and Critical Mineral (CORE-CM) Uinta Region assessment funded by the U.S. Department of Energy (DEFE0032046, 2021–2024; Birgenheier et al., 2024). The CORE-CM assessment focused on providing comprehensive geological and geochemical characterization of current and prospective sedimentary-hosted resources including coal, oil shale, phosphatic limestone, and produced water from oil and gas targets present in eastern Utah and northwestern Colorado (Figure 1). This Data Series includes a geodatabase that consists of analytical geochemical data collected September 2021 through December 2024 via portable X-ray fluorescence (pXRF), and laboratory measured analyses produced by inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectroscopy (ICP-OES). The coal-related geochemical data are derived primarily from the Cretaceous Blackhawk Formation and Ferron Sandstone of Utah, and the Mesaverde Group of Colorado. Additional non-coal resources assessed include oil shale-bearing strata of the Eocene upper Green River Formation (Utah and Colorado), phosphate-rich limestone of the Permian Park City Formation (Utah) and produced water from oil and gas-bearing strata of the Eocene Green River and Wasatch Formations (Uinta Basin) and the Pennsylvanian Paradox Formation (Paradox Basin) (Table 1). The CORE-CM assessment included a wide range of lithologies present in the coal, oil shale, and phosphate geologic resource systems whether or not the specific lithology has current economic value. Geochemical analyses of produced water from oil and gas wells focused on current and emerging hydrocarbon targets in the central Uinta Basin and northern Paradox Basin. A total of 13,092 geochemical analyses from these geologic systems is provided in the included geodatabase. A series of coal quality data (e.g., composition and maceral analyses) is also included in the database and was digitized from archived coal samples from the Utah Geological Survey (Appendix A).

Colorado, Utah

Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California

The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes substantially to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides substantial volumes of agricultural products not just for California but for the United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface-water and groundwater resources in the valley. This situation has resulted in water management challenges in the Salinas Valley that generally relate to the distribution of the water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. Historically, to deal with the distribution issue, water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface-water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface-water supplies are insufficient. The availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand for groundwater and surface-water resources throughout the Salinas Valley has resulted in undesirable effects from unsustainable water use, such as surface-water depletion, groundwater-level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface-water and groundwater resources. To meet water demands and reduce the undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and climate variability. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resources Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley hydrogeologic system called the Salinas Valley System Model. The geologic framework is known as the Salinas Valley Geologic Framework and was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The surface-water model is called the Salinas Valley Watershed Model and simulates the Salinas River watershed. Monthly surface-water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.

California

Creation of aerial camera system boresight installations in Bangor, Maine; Monroe, Louisiana; and Bassville Park, Florida

Aerial camera systems rely on boresights for defining internal and external metrics. The U.S. Fish and Wildlife Service’s Migratory Bird Surveys Branch required boresights to calibrate their camera systems for creating georeferenced imagery that can then be used in geographic information systems. The U.S. Geological Survey created high-accuracy boresight installations in Bangor, Maine, in July 2024; Monroe, Louisiana, in September 2024; and Bassville Park, Florida, in January 2025 to provide this metric-defining capacity to the U.S. Fish and Wildlife Service. This U.S. Geological Survey Data Report details the methods and results of the boresight installation process and provides camera operators with the data needed to use each of the installations.

Florida, Louisiana, Maine

Current status of the community sensor model standard for the generation of planetary digital terrain models

The creation of accurate elevation models (topography) from stereo images are critical for a large variety of geospatial activities, including the production of digital orthomosaics, change detection, landing site analysis, geologic mapping, rover traverse planning, and spectral analysis. The United Stated Geological Survey, Astrogeology Science Center, continues to transition the supported planetary sensor models to the Community Sensor Model (CSM) standard. This paper describes the current state of use for this photogrammetric standard, supported sensor model types, and qualitatively compares derived topography between SOCET SET and SOCET GXP ( ® BAE Systems) using HiRISE stereo images of Mars. Our transition to the CSM standard will ensure an uninterrupted capability to make these valuable products for Mars and many other extraterrestrial planets and moons.

Remote Sensing

New methodology for assessing underground natural gas storage resources – Example from Michigan Basin, United States

Energy consumption in the United States (U.S.) and across the world is shifting away from traditional fossil fuels like coal and oil, and towards natural gas and renewable sources, including hydrogen. Because gas demand is typically greatest during cold seasons and renewable sources sometimes produce variable supplies, it is important to store energy for use when demand exceeds supply. Whereas batteries and tanks typically store energy above ground, geologic (underground) storage may be able to retain much greater quantities of energy over much longer durations (e.g., Matos et al. 2019; Buursink et al. 2023). Consequently, the U.S. Geological Survey (USGS) is developing a methodology to locate new geologic energy storage sites with an initial focus on depleted hydrocarbon reservoirs followed by estimates of associated pore space or gas storage capacity. Depleted hydrocarbon fields in Michigan Basin in the U.S. already host large quantities of injected natural gas (about 681 billion cubic feet of seasonal gas capacity in 42 gas storage facilities; U.S. Energy Information Administration 2024). Therefore, we used this basin as an example to assess potential new storage resources alongside existing storage capacity and carbon dioxide sequestration resources (e.g., Katz and Coats 1968; Haagsma et al. 2020). In Michigan Basin gas storage is taking place in reservoirs within several key hydrocarbon producing formations with different lithologies, including the informal Stray sandstone of the Michigan Formation and the pinnacle reefs of the Niagara Group (Gautier et al. 1995; Swezey et al. 2015). The assessment methodology introduced here consists of two steps relying on both well information and reservoir data.

Michigan

Arsenic and isotope concentrations in the lower Platte River valley of eastern Nebraska, early 1970s to 2023

The City of Lincoln, Nebraska, has been monitoring concentrations of arsenic in their source water and evaluating their options for treatment and removal since at least 2002. In 2022, the City of Lincoln, Nebr., with funding assistance from the Nebraska Water Sustainability Fund, began cooperating with the U.S. Geological Survey to examine arsenic concentrations in surface water and groundwater in the lower Platte River valley and the area around City of Lincoln Water System (LWS) well field. Arsenic data collected from the Platte River since 1974 were examined using the “weighted regression on time, discharge, and season” model, which compared the streamflow (also referred to as “discharge”), time of year, and season to estimate concentrations of arsenic. Annual mean arsenic concentrations modeled for more than 49 years at the Platte River at Louisville, Nebr., U.S. Geological Survey streamgage (station 06805500), indicated a significant increasing trend. Arsenic concentrations in the Platte River were seasonal, with the highest concentrations being observed during mid- to late summer. When seasonal patterns and streamflow were combined with arsenic concentrations in the Platte River during low streamflow conditions, groundwater contributions, which can have higher arsenic concentrations, make up a larger portion of the streamflow. Arsenic samples were collected from upstream rivers in 2022 and 2023 and were paired to analyze the arsenic contributions at the U.S. Geological Survey streamgage on the Platte River near Ashland, Nebr. (station 06801000), near the City of Lincoln well field. The arsenic concentrations from the streamgage on the Platte River near Ashland, Nebr., location, were higher than the U.S. Geological Survey streamgage on the Elkhorn River at Waterloo, Nebr. (station 06800500), and significantly lower than at the U.S. Geological Survey streamgage on the Platte River near Leshara, Nebr.(station 06796500), indicating that the Platte River usually contributes a higher concentration of arsenic than does the Elkhorn River as they join near Ashland, Nebr. During 1991–2023, six groundwater monitoring wells were analyzed to identify trends in arsenic concentrations. Two of the six wells had a positive trend during the 33-year period. One monitoring well did not reveal a long-term trend during this period but showed a trend during 2019–23, correlating to a period when the island in the middle of the Platte River was connected to the east bank of the river when manganese reducing conditions were present and groundwater levels were declining in the well. Across all wells the oxidation and reduction (redox) condition during the time of sampling was assessed. Mixed anoxic and (or) oxic redox condition was the most common redox process and the highest sampled arsenic concentrations in monitoring wells were observed in anoxic conditions driven by manganese reduction. Groundwater arsenic concentrations had seasonal variation around the City of Lincoln well field, with higher arsenic concentrations tending to be further south in comparison to samples collected further north. Isotope samples were collected and analyzed in surface water and groundwater around the LWS well field. The samples indicate that the proportion of surface water present in the LWS production wells can be higher in the spring and lower in the summer. With higher arsenic concentrations observed in the stream water during the summer period, the LWS source water can be affected by these elevated arsenic concentrations even though the proportion of surface water is lower.

Nebraska