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Extending the Boore and Abrahamson (2023) modified square-root-impedance method for the development of site amplifications consistent with the full-resonance approach to a range of VS30 values

The square-root-impedance (SRI) method is commonly used to approximate the seismic site amplifications computed using the full-resonance (FR) method for gradient shear-wave velocity ( V S ) profiles that are smoothly varying with depth. The SRI site amplifications have been observed to systematically underpredict the FR site amplifications by a ratio of FR/SRI amplifications around 1.05 to 1.3 across a wide frequency range (Boore, 2013). Recently, Boore and Abrahamson (2023; hereafter, BA23) related this difference in the SRI and FR methods to differences in the exponent η of the ratio of seismic impedances between the two methods. They proposed the implementation of a modified frequency-dependent η in the SRI method to improve its match to the FR site amplifications. This modified η was derived using only five V S profiles. We investigate the performance of the BA23 η for a wide range of realistic gradient V S profiles with V S30 ranging from 180 to 1500 m/s. These gradient V S profiles are constructed using two power-law functions of depth and are constrained by the assigned VS30 value, the depth and velocity of the half-space, and depths to shear-wave velocity horizons of 1.0 and 2.5 km/s ( Z 1.0 and Z 2.5 ) based on western United States sites. Despite observing a V S30 dependence of η, we find that the BA23 η generally works reasonably well for the range of V S profiles analyzed. Using the VS30 -dependent η derived in this study results in improvements in matching the FR site amplification compared to using the BA23 η. These improvements are more pronounced for the soft-site conditions and become modest to negligible for the stiff site conditions

Bulletin of the Seismological Society of America

Perspectives on transportable array Alaska background noise levels

Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.

Book chapter

Comparing subduction ground-motion models to observations for Cascadia

We evaluate Cascadia subduction ground-motion models (GMMs), considered for the 2023 US National Seismic Hazard Model (NSHM) update, by comparing observations to model predictions. The observations comprise regional recordings from intraslab earthquakes, including contributions from 2021 and 2022 events in southern Cascadia and global records from interface earthquakes. Since the 2018 NSHM update, new GMMs for Cascadia have been published by the Next Generation Attenuation (NGA)-Subduction Project that require independent evaluation. In the regional intraslab comparisons, we highlight a characteristic frequency dependence for Cascadia data, with short periods having lower ground motions and longer periods being comparable to other subduction zones. We evaluate differences in northern and southern Cascadia and find that the NGA-Subduction GMMs developed using southern Cascadia data perform better in this region than the model that did not consider these data. We compare ground-motion variability in Cascadia with the NGA-Subduction model predictions and find differences at short periods ( T = 0.1 s) due to the use of global versus regional data in the development of these models. Moreover, the within-event component of aleatory variability from the GMMs overpredicts the standard deviation of Cascadia recordings at very short periods ( T < 0.05 s). Using global interface earthquakes as a proxy to evaluate the Cascadia GMMs, we find long-period overprediction from a simulation-based GMM and some of the empirical GMMs. When comparing recent observations, we find a similar misfit to GMMs and the 2010 and 2022 Ferndale earthquakes. Finally, we observe different basin amplification factors arising in different subsets of the data, which indicate that differences in basin factors between empirical GMMs could arise from the data selection choices by the developers. As part of evaluating the regional basin terms, we apply basin amplification factors from the magnitude 9 Cascadia earthquake simulations to the empirical GMMs for interface earthquakes. The comparisons presented in this study indicate that the NGA-Subduction GMMs for Cascadia perform well relative to observations and older subduction GMMs.

British Columbia, California, Oregon, Washington

Nitrogen deposition weakens soil carbon control of nitrogen dynamics across the contiguous United States

Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified ( ƒ nitrified ), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta-glucosidase (BG) and N -acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒ nitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒ nitrified . The ƒ nitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒ nitrified , including for high soil C sites predicted to have low ƒ nitrified , which decreased the role of soil C as a predictor of ƒ nitrified . Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID-19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒ nitrified . Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.

contiguous United States

The Saudi Geological Survey-U.S. Geological Survey northern Harrat Rahat project—Styles, rates, causes, and hazards of volcanism near Al Madīnah al Munawwarah, 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. This initial chapter introduces the project and briefly summarizes results in plain language for readers who have more general backgrounds.

Al Madīnah al Munawwarah

Volcanic gas monitoring

Introduction As magma rises through the crust, decreasing pressure conditions allow volatiles to exsolve from the magma. These volatiles then migrate upward through the crust, where they can be stored at shallower levels or escape to the atmosphere. Rising magma also heats rock masses beneath volcanic centers, causing water in shallow aquifers and hydrothermal systems to boil and release additional gases and steam (see chapter F , this volume; Ingebritsen and Hurwitz, 2024). The chemistry and quantity of gases that reach the surface during periods of quiescence or volcanic unrest can reveal that gas-rich magma is ascending, crystallizing, or alternatively stalling, with important implications for volcanic hazard (for example, Sutton and others, 1992; Aiuppa and others, 2007, 2021; Werner and others, 2009, 2011, 2012; Moretti and others, 2013; de Moor and others, 2016; Lewicki and others, 2019; Edmonds and others, 2022; Kern and others, 2022; Kunrat and others, 2022). Most volcanoes in Alaska and the western United States are characterized by weak degassing, with one or more low-temperature fumaroles (typically near the local boiling temperature of water) and connect to a deeper and sometimes extensive hydrothermal system (for example, McGee and others, 2001; Symonds and others, 2003a, b). Hydrothermal systems will affect the chemistry of rising gases exsolved from deeper magma (Symonds and others, 2001), including sulfur dioxide (SO 2 ), hydrogen chloride (HCl), and water vapor (for example, Doukas and Gerlach, 1995; Gerlach and others, 1998, 2008; Symonds and others, 2001; Werner and others, 2013). As an example, depending on factors such as temperature, pressure, and oxidation state, rising SO 2 will react with groundwater to form hydrogen sulfide (H 2 S) gas, dissolved sulfate (SO 4 2− ), or elemental sulfur (Christenson, 2000; Symonds and others, 2001; Werner and others, 2008). The reaction and dissolution of SO 2 into shallow groundwater is commonly referred to as scrubbing, and can reduce the likelihood that ascending, degassing magma can be detected. Carbon dioxide, however, in addition to exsolving from magma early in the ascent process, is not easily removed by hydrothermal fluids (Lowenstern, 2001). As scrubbing and other processes take place, the SO 2 /H 2 S, CO 2 /SO 2 , and CO 2 /H 2 S ratios may change. High rates of SO 2 emission indicate that magma has moved to relatively shallow levels in the volcano and that the system has heated up enough to establish dry pathways from depth to the surface. Monitoring multiple gas species and the total output of those species is thereby useful for volcano monitoring during both periods of quiescence, to establish background degassing conditions, and during unrest, when gas geochemistry and emission rates can provide information on changing conditions, such as magma ascent. To provide context for multidisciplinary volcano forecasts, we focus on the following two key required capabilities: (1) characterizing baseline geochemistry and gas discharge from volcanoes and volcanic regions and (2) monitoring changes in gas geochemistry and discharge to inform forecasts of volcanic eruptions and their effects. Sufficient baseline data must be collected to identify and interpret anomalous degassing associated with volcanic unrest (for example, Sorey and others, 1998; Rouwet and others, 2014). Differences in volcano type, baseline degassing rates, local hydrology, and geography (for example, high versus low latitude) will result in a different baseline for each volcano. Volcanoes of any threat level that exhibit one or more degassing phenomena would ideally be monitored by techniques needed to establish baseline degassing data, with the sampling frequency of baseline data dictated by the threat level (table E1). Additional monitoring techniques become necessary during periods of unrest. In general, three of the most important techniques for gas monitoring are (1) direct sampling of fumarole, spring, and soil gases for laboratory geochemical measurements, (2) measurements of the chemical composition of the volcanic plume and emission rates of major gas species (for example, H 2 O, CO 2 , SO 2 , and H 2 S) by satellite, airborne, or ground-based techniques, and (3) measurements of diffuse emissions of CO 2 and other gases through soils. Various methods and instruments may be useful both for baseline studies and during unrest.

Scientific Investigations Report

Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows

In 2020, a wildfire burned across Glenwood Canyon in Colorado, USA. A history of postfire debris flows in the region and a hazard assessment for the burn area indicated that potentially life-threatening debris flows could be triggered by rainfall within months of a wildfire. As a result, four government agencies evaluated strategies to help mitigate hazards, including the loss of human life, that may be associated with debris-flow events. After the fire, 26 large debris flows occurred in the summer of 2021 and three sediment-laden flows occurred in the summer of 2023, but there were no major injuries or fatalities reported. We found that integrating hazard assessment/ forecasting, monitoring, and adaptation scenarios was a successful strategy for reducing postfire debris-flow risks to human life (including injuries and fatalities). Weather forecasts and estimates of debris-flow triggering rainfall thresholds, likelihood, and volume were used to anticipate the timing, location, and magnitude of debris-flow events. Rainfall monitoring and detailed recordkeeping of storms that triggered debris flows were used to validate and update debris-flow warning thresholds that varied with time following the wildfire. Although the governmental agencies working in this burn area had distinct and differing agency mandates, they were able to integrate information to reduce the risk of debris-flow events to human life.

Colorado

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

High-precision earthquake catalog for Minto Flats fault zone, central Alaska, reveals complex and conjugate faulting

The Minto Flats fault zone (MFFZ) in central Alaska is a left‐lateral strike‐slip fault system situated between the continental‐scale right‐lateral Denali and Kaltag‐Tintina faults. The MFFZ has the potential to generate magnitude 7 earthquakes, and it hosted a magnitude 6 earthquake in 1995. It has also produced exotic events, such as very‐low‐frequency earthquakes and nucleation signals. We use network‐matched filtering and relative earthquake relocation techniques to derive a detailed catalog of earthquake locations for the MFFZ. The catalog spans from August 2014 to December 2019, a time period including 13 temporary seismic stations in the region. Our results provide the most complete catalog for the MFFZ and include deeper events, clusters of shallow seismicity, and a complex and segmented fault structure not observed in the original regional catalog. We document right‐lateral strike‐slip faulting, conjugate to the main northeast‐striking left‐lateral faults of the MFFZ. Below Nenana basin, the relocated seismicity reveals northwest‐dipping left‐lateral faults, supporting the inference that deep crustal active faulting is associated with recent basin deformation.

Alaska

Reference 1D seismic velocity models for volcano monitoring and imaging: Methods, models, and applications

Seismic velocity models of the crust are an integral part of earthquake monitoring systems at volcanoes. 1D models that vary only in depth are typically used for real‐time hypocenter determination and serve as critical reference models for detailed 3D imaging studies and geomechanical modeling. Such models are usually computed using seismic tomographic methods that rely on P ‐ and S ‐wave arrival‐time picks from numerous earthquakes recorded at receivers around the volcano. Traditional linearized tomographic methods that jointly invert for source locations, velocity structure, and station corrections depend critically on having reasonable starting values for the unknown parameters, are susceptible to local misfit minima and divergence, and often do not provide adequate uncertainty information. These issues are often exacerbated by sparse seismic networks, inadequate distributions of seismicity, and/or poor data quality common at volcanoes. In contrast, modern probabilistic global search methods avoid these issues only at the cost of increased computation time. In this article, we review both approaches and present example applications and comparisons at several volcanoes in the United States, including Mount Hood (Oregon), Mount St. Helens (Washington), the Island of Hawai’i, and Mount Cleveland (Alaska). We provide guidance on the proper usage of these methods as relevant to challenges specific to volcano monitoring and imaging. Finally, we survey‐published 1D P ‐wave velocity models from around the world and use them to derive a generic stratovolcano velocity model, which serves as a useful reference model for comparison and when local velocity information is sparse.

Seismological Research Letters

Divisions of geologic time—Major chronostratigraphic and geochronologic units

Effective communication in the geosciences requires consistent uses of stratigraphic nomenclature, especially divisions of geologic time. A geologic time scale is composed of standard stratigraphic divisions based on rock sequences and is calibrated in years. Over the years, the development of new dating methods and the refinement of previous methods have stimulated revisions to geologic time scales. Advances in stratigraphy and geochronology require that any time scale be periodically updated. Therefore, Divisions of Geologic Time, which shows the major chronostratigraphic (position) and geochronologic (time) units, is intended to be a dynamic resource that will be modified to include accepted changes of unit names and boundary age estimates. This fact sheet is a modification of USGS Fact Sheet 2007-3015 by the U.S. Geological Survey Geologic Names Committee.

Fact Sheet

AAPG Energy and Minerals Division Tight Oil and Gas Committee Activities and Commodity Report for 2021-2022: Tuscaloosa Marine Shale, Gulf Coast basin, Louisiana and Mississippi

The Upper Cretaceous Tuscaloosa marine shale (TMS) potential production area encompasses 20.4 million acres across central Louisiana (LA), southern Mississippi (MS), southwestern Alabama (AL), and a small southwestern section of the Florida panhandle (Hackley et al., 2018). It remains a minor and largely undeveloped unconventional shale oil play with production from the TMS confined along the east-west LA-MS State boundary (Fig. 1). The mean undiscovered, technically recoverable resources in the TMS are estimated at 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas (Hackley et al., 2018). Geochemical analyses of source rock solvent extracts and oil samples indicate that, in the play area, the TMS is the primary source of shale oil produced from the TMS as well as of accumulated oils in the underlying conventional reservoirs of the lower Tuscaloosa (Hackley et al., 2020). The API gravity of TMS oils ranges from approximately 34 to 46 degrees (Hackley et al., 2020; Croke et al., 2020).

AAPG Wiki

Bascom Laser Diffraction Sedimentology Laboratory, Reston, Virginia

Introduction At the Bascom Laser Diffraction Sedimentology Laboratory, which is located in the Florence Bascom Geoscience Center at U.S. Geological Survey (USGS) headquarters in Reston, Virginia, scientists use physical sedimentology and particle characterization techniques to conduct detailed sediment characterization. Scientists address research problems in collaboration with other USGS science centers, State geological surveys, commercial industry, universities, and other partners. Laboratory capabilities include laser diffractometry for quantitative particle-size analysis, portable x-ray fluorescence (XRF) analysis for determining elemental abundances in rock or sediment samples, petrographic analysis of geologic media, and mechanical sieve analysis. These methods are used to analyze soil and sediment core material from terrestrial, marine, and lacustrine environments, surface sediments from coastal regions, and calcareous materials. Work done by the laboratory supports geologic mapping, resource assessments, land change studies, and geohazard analyses.

Fact Sheet

Analysis of aquifer framework and properties, Alvahs Lane well field, Cutchogue, New York

The U.S. Geological Survey, in cooperation with the Suffolk County Water Authority, evaluated the aquifer transmissivity and storage properties at the Alvahs Lane well field north of the village of Cutchogue, New York. This analysis of aquifer properties provides the Suffolk County Water Authority with hydrogeologic information needed to develop water supplies to meet the increasing water demands of the residents of Suffolk County, New York. An aquifer test was conducted at the Alvahs Lane well field from October 18 through October 21, 2022, when a production well was pumped at 550 gallons per minute for about 24 hours, and groundwater-level drawdown and recovery were measured in two monitoring wells. The three wells are screened in a glaciofluvial aquifer under unconfined (water table) conditions. Drawdown and recovery data were analyzed with an analytical solution for partial penetration and delayed yield in an unconfined aquifer to provide estimates of the glaciofluvial aquifer properties. Inclusion of lateral aquifer boundaries was not necessary for the analysis to result in satisfactory matches with the observed water-level responses. Aquifer transmissivity was estimated at 32,000 feet squared per day. Assuming a saturated aquifer thickness of 120 feet, this result is equivalent to a horizontal hydraulic conductivity value of 270 feet per day. Specific yield was estimated at 0.15 (dimensionless). The estimated properties are consistent with those of a highly transmissive unconfined aquifer.

New York

Airborne geophysical analysis to decipher salinization for coastal Louisiana

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

Louisiana

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California

Light absorbing particles deposited to snow cover across the Upper Colorado River Basin, Colorado Rocky Mountains, 2013-16: Interannual variations from multiple natural and anthropogenic sources

Atmospheric particulate matter (PM) as light-absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013–2016) from the mountainous Upper Colorado River basin by comparing among laboratory-measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35–2.50 μm, varied by a factor of 1.9 (range, 0.2300–0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6–22.5 wt. %) including inferred black carbon, natural organic matter, and carbon-based synthetic, black road-tire-wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11–0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source-area contributions implying strong interannual changes in regional source behavior, dust-storm frequency, and (or) transport tracks. Observations of dust-storm activity in the western U.S. and particle-size averages for all samples (median, 25 μm) indicated that regional dust from deserts dominated mineral-dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

Colorado

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina