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USGS2024

The 2023 U.S. 50-state National Seismic Hazard Model: Changes in 2023 compared to 2018 ground motions

We present the 2023 U.S. National Seismic Hazard Model (NSHM) for all 50 states that applies new smoothed seismicity, fault rupture, and ground motion models. New data and methods are introduced in the 2023 earthquake rupture forecast that include: new earthquake catalogs - excluding induced earthquakes, alternative declustering methods, spatially smoothed seismicity distributions, full-catalog scaled rates to account for aftershocks, updated CEUS-WUS attenuation boundary, new magnitude-scaling equations, new geodetic and geologic deformation models, and alternative fault system solutions accounting for a more complete representation of epistemic uncertainty potential for earthquake generation in Alaska, Hawaii, and the conterminous U.S. Improved ground motion models consider new Next Generation Attenuation NGASubduction, modified NGA-East, and adjustments to account for regional biases in ground shaking observations. Semi-empirical and 3D simulations of ground motion are applied to account for shaking at 21 oscillator periods, 2 peak motions, and 8 site conditions. Site effects models are constructed for western U.S. basins (Seattle, Portland/Tualatin, San Francisco, Central Valley of California, Los Angeles, and Salt Lake City) and for sites with deep sedimentary wedges found across the central and eastern U.S. Gulf Coast and Atlantic coastal plain regions. These models result in substantial changes compared to the older NSHMs and are differentiated for the earthquake rupture forecast and ground motion model changes to display sensitivities and impacts.

Conference Paper↗
USGS2025

Generalized Bancroft algorithm for locating earthquakes with P- and S-wave arrival times

Because of similarities between locating an earthquake with seismic stations and locating a Global Positioning System (GPS) receiver from satellites, the Bancroft algorithm developed for GPS processing can be used to locate earthquakes. Such an approach to earthquake location differs from the conventional method of choosing an initial or trial solution and then iteratively improving the solution until convergence. The Bancroft algorithm has the advantage of being a direct, noniterative solution but with the disadvantage of only being able to accommodate a homogeneous velocity model. An additional limitation of the standard Bancroft algorithm is that it considers arrival times in a medium with a single propagation velocity. This poses no problem for GPS processing because electromagnetic waves travel at the speed of light; however, for seismic waves it means the algorithm can be applied to collections of either P ‐ or S ‐wave arrival times. Here, I show how the Bancroft algorithm can be generalized to handle both P ‐ and S ‐wave arrival‐time measurements simultaneously. I also show how to accommodate depth‐varying P ‐ and S ‐wave velocity models. I apply the generalized Bancroft algorithm to microearthquakes beneath Tanaga Volcano in Alaska and compare standard locations from the widely used HYPOINVERSE location code to Bancroft locations and to the output of HYPOINVERSE when setting the trial location to the Bancroft location. I find the Bancroft locations outperform the results from the other methods for shallow earthquakes near sea level, where a quantity known as the geometric dilution of precision is large and linearized approaches such as HYPOINVERSE are expected to struggle.

Alaska↗
USGS1998

Continuous hydrologic simulation of runoff for the Middle Fork and South Fork of the Beargrass Creek basin in Jefferson County, Kentucky

The Hydrological Simulation Pro-gram-FORTRAN (HSPF) was applied to an urban drainage basin in Jefferson County, Ky to integrate the large amounts of information being collected on water quantity and quality into an analytical framework that could be used as a management and planning tool. Hydrologic response units were developed using geographic data and a K-means analysis to characterize important hydrologic and physical factors in the basin. The Hydrological Simulation Program FORTRAN Expert System (HSPEXP) was used to calibrate the model parameters for the Middle Fork Beargrass Creek Basin for 3 years (June 1, 1991, to May 31, 1994) of 5-minute streamflow and precipitation time series, and 3 years of hourly pan-evaporation time series. The calibrated model parameters were applied to the South Fork Beargrass Creek Basin for confirmation. The model confirmation results indicated that the model simulated the system within acceptable tolerances. The coefficient of determination and coefficient of model-fit efficiency between simulated and observed daily flows were 0.91 and 0.82, respectively, for model calibration and 0.88 and 0.77, respectively, for model confirmation. The model is most sensitive to estimates of the area of effective impervious land in the basin; the spatial distribution of rain-fall; and the lower-zone evapotranspiration, lower-zone nominal storage, and infiltration-capacity parameters during recession and low-flow periods. The error contribution from these sources varies with season and antecedent conditions.

Kentucky↗
USGS2025

Characterizing sedimentary organic carbon in a hydrothermal spreading center, the Escanaba Trough

Sediments in critical marine mineral environments are of wide importance due to their preservation of both marine minerals and organic carbon (OC) stocks. However, OC storage and cycling is often overlooked in mineral system studies. This work characterizes sedimentary OC within the Escanaba Trough, a hydrothermal sulfide system off the coast of northern California. By utilizing ROV-based push coring, we collected sediments near and far from high temperature, low temperature, and inactive vents. We applied a multipronged organic geochemical approach, measuring bulk sediment, OC fractions of varying labilities, and biomarkers to tease apart the storage, source, and cycling of OC within this complex system. In contrast to past work indicating a primarily terrestrial source to deeper, Pleistocene sediments, our results suggest a primarily marine source in surface sediments at least 50 m away from active venting. Near active venting, we see evidence of locally produced chemosynthetic OC in addition to the background marine source. This chemosynthetic OC appears to be rapidly remineralized and supports more complex deep-sea food webs compared to hemipelagic sites. Still, the greatest contribution of labile OC was observed at inactive vent sites, which we suggest is due to hydrothermal fluid alteration of more labile OC at actively venting sites. Depending on fluid temperature, hydrothermally altered OC is either preserved in the sediments as petroleum or migrated with fluid flow. Considering inactive sites are those most likely to be targeted by potential mining, we suggest additional studies could verify if these results apply at other sedimented seafloor massive sulfide systems.

California↗
USGS2026

Groundwater budget for the Mountain Home area, southern Idaho, 2022–23

The U.S. Geological Survey, with funding from the Idaho Department of Water Resources, developed a groundwater budget for the Mountain Home area in southern Idaho for irrigation year 2023 (November 1, 2022–October 31, 2023). This study focused on the water balance across the Cinder Cone Butte Critical Groundwater Area (CGWA), Mountain Home Groundwater Management Area (GWMA), and the rest of the study area (RoSA), compiling data from various sources, including precipitation records, groundwater level measurements, metered groundwater pumpage data, surface water diversions and evapotranspiration (ET) estimates derived from remote sensing satellite imagery, and ground-based reference data. Key inflow components included recharge from applied surface water irrigation (which incorporates incidental recharge from irrigation practices and conveyance losses), estimated tributary streamflow, and estimated mountain block recharge. The key outflow components were groundwater pumpage for irrigation, municipal, industrial, and domestic uses, and ET. Recharge from applied irrigation and mountain block recharge were the largest inflows, and groundwater pumpage for irrigation was the largest outflow. The CGWA had a positive groundwater budget residual of 2,170 acre-feet (acre-ft), which contrasts with observed long-term groundwater level declines and historical trends of storage depletion. This positive residual is likely associated with unquantified outflows, including lateral groundwater flow out of the subregion, or other complexities, such as overestimated tributary contributions relative to the actual recharge for the 2023 water budget. The GWMA exhibited a positive residual of 56,563 acre-ft, primarily owing to recharge from applied surface water irrigation and areal recharge during a wetter-than-average year, which allowed irrigation entities to deliver more water from in-basin and out-of-basin reservoirs. The RoSA showed a large positive residual of 124,933 acre-ft. The interpretation of these positive residuals must account for significant uncertainties, including estimations of areal recharge, tributary streamflow (particularly losses and diversions), ET, the volume of surface water loss to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and the unquantified groundwater discharge to the Snake River. These uncertainties, in combination with the complex hydrogeologic controls on water movement and limitations of remotely sensed data, directly affect the accuracy of water availability assessments. Future data collection efforts would help reduce these uncertainties and support water resource management decisions in the Mountain Home area. Key efforts could include installing additional streamflow gaging stations (particularly to quantify tributary losses and gains and surface water losses to the Snake River), improving groundwater pumpage metering, and validating remotely sensed ET data with ground-based measurements. Furthermore, to better quantify unrepresented or highly uncertain fluxes, focused investigations on groundwater discharge to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and a more robust determination of the actual influence and volume of mountain block recharge would help refine future water availability assessments for the Mountain Home area.

Idaho↗
USGS2025

A generalized deep learning model to detect and classify volcano seismicity

Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] ( 10.1029/2024JB029194 ) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network ( VOISS-Net ) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.

Volcanica↗
USGS2012

Development of vegetation based soil quality indices for mineralized terrane in arid and semi-arid regions

Soil quality indices (SQIs) are often management driven and attempt to describe key relationships between above- and below-ground parameters. In terrestrial systems, indices that were initially developed and modified for agroecosystems have been applied to non-agricultural systems in increasing number. We develop an SQI in arid and semi-arid ecosystems of the Western US impacted by different types of geologic mineralization using the relationship between vegetation community parameters and soil abiotic and biotic properties. We analyze these relations in soils associated with three different mineralization types: podiform chromite, Cu/Mo porphyry, and acid-sulfate gold vein systems at four different sites in California and Nevada. Soil samples were collected from undisturbed soils in both mineralized and nearby unmineralized substrates as well as from waste rock and tailings. Aboveground net primary productivity (ANPP), canopy cover and shrub density were measured for the vegetative communities. Minimum data sets were developed based on correlations between the soil and vegetation parameters, refined using principal components analysis, scored using non-linear functions, and combined into an overall SQI. The indices are comprised of one or two microbial parameters and three to six abiotic parameters, the latter consisting of nutrients and metals. Given the preliminary development of this approach, the parameters and combinations to arrive at an SQI for a given site cannot at this time be correlated or compared with that of another site. This SQI approach provides a means of quantifying disturbed ecosystem recovery resulting from mining, and could be applied to other disturbances in a way that readily distills the information for potential use by land managers. However, severely disturbed areas with little to no aboveground biomass, such as unreclaimed tailings, have likely crossed an ecological threshold that precludes the use of this type of monitoring tool.

California↗
USGS1998

Technique for simulating peak-flow hydrographs in Maryland

The efficient design and management of many bridges, culverts, embankments, and flood-protection structures may require the estimation of time-of-inundation and (or) storage of floodwater relating to such structures. These estimates can be made on the basis of information derived from the peak-flow hydrograph. Average peak-flow hydrographs corresponding to a peak discharge of specific recurrence interval can be simulated for drainage basins having drainage areas less than 500 square miles in Maryland, using a direct technique of known accuracy. The technique uses dimensionless hydrographs in conjunction with estimates of basin lagtime and instantaneous peak flow. Ordinary least-squares regression analysis was used to develop an equation for estimating basin lagtime in Maryland. Drainage area, main channel slope, forest cover, and impervious area were determined to be the significant explanatory variables necessary to estimate average basin lagtime at the 95-percent confidence interval. Qualitative variables included in the equation adequately correct for geographic bias across the State. The average standard error of prediction associated with the equation is approximated as plus or minus (+/-) 37.6 percent. Volume correction factors may be applied to the basin lagtime on the basis of a comparison between actual and estimated hydrograph volumes prior to hydrograph simulation. Three dimensionless hydrographs were developed and tested using data collected during 278 significant rainfall-runoff events at 81 stream-gaging stations distributed throughout Maryland and Delaware. The data represent a range of drainage area sizes and basin conditions. The technique was verified by applying it to the simulation of 20 peak-flow events and comparing actual and simulated hydrograph widths at 50 and 75 percent of the observed peak-flow levels. The events chosen are considered extreme in that the average recurrence interval of the selected peak flows is 130 years. The average standard errors of prediction were +/- 61 and +/- 56 percent at the 50 and 75 percent of peak-flow hydrograph widths, respectively.

Maryland↗
USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the southern Appalachian orogen

The first quantitative mineral resource assessment for undiscovered lithium pegmatite deposits in the southern Appalachian region of the United States was conducted. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical and mineral occurrence data. Lithium pegmatite prospectivity of the tracts was ranked with simplified mappable criteria, including proximity to Paleozoic felsic intrusions and major lithotectonic structures, stream sediment geochemical anomalies, and pegmatite occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. These estimates were integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was applied to convert the probabilistic estimates of contained lithium into recoverable material. The identified lithium pegmatite resources for the Carolina Lithium and Kings Mountain deposits, North Carolina, contain 1589 thousand tons (kt) of Li 2 O. The median contained undiscovered resource for the southern Appalachian orogen was estimated to be 2240 kt Li 2 O. At 90% confidence, the region contains at least 130 kt Li 2 O, and 10,700 kt at 10% confidence. After applying economic filters, the median recoverable contained resource was 1430 kt Li 2 O, corresponding to approximately 201 years of current lithium imports for consumption in the United States. North and South Carolina are likely to contain most of these resources. Coarse data resolution and intra-state variations in the geological data contribute to uncertainty of undiscovered lithium pegmatite resources. Continued efforts to harmonize disparate geospatial datasets with updated or new information can improve the accuracy and precision of estimated undiscovered lithium pegmatite resources in the study area and at broader scales.

Alabama, Georgia, Maryland, North Carolina, South ↗
USGS2024

Seismic techniques and suggested instrumentation to monitor volcanoes

Introduction Changes in the pressure or location of magma can stress or break surrounding rocks and trigger flow of nearby waters and gases, causing seismic signals, such as discrete earthquakes and tremor. These phenomena are types of seismic unrest that commonly precede eruption and can be used to forecast volcanic activity. Mass movements at the surface, including avalanches, debris flows, and lahars, may also generate seismic signals that are specifically addressed in chapter H , this volume (Thelen and others, 2024). Our focus in this chapter is to determine the levels of instrumentation recommended to produce high-quality, well-constrained seismic observations important for early warning of impending eruptions, detecting changes in ongoing eruptions, and characterizing other hazardous volcanic events. There are emerging techniques and new types of instrumentation, such as distributed acoustic sensing or rotational seismometers, that we do not consider here. These types of instrumentation show promise for monitoring but still require maturation before being considered more generally in volcano monitoring. Most of the capabilities mentioned below are universal for all types of volcanic systems, although some are best applied to stratovolcanoes with an apical single vent. In some settings, such as calderas or shield volcanoes, we must broaden coverage to include multiple possible storage regions or vent locations. As an example, Thelen (2014) discretized the long rift zones of shield volcanoes in Hawaiʻi as a set of evenly spaced “vents.” In this construct, each vent comes with recommendations, and several thousand network configurations were simulated to assess the effect on network quality levels and to determine the most efficient network design. The same process could be applied in a caldera setting or a volcanic field, where an evenly spaced grid of potential vents is considered. Localized recommendations for each unique system are beyond the scope of this report and left up to local experts to assess based on the conditions, restrictions, and requirements of each volcano.

Scientific Investigations Report↗
USGS2025

An evaluation of the effects of different deicing salt application rates on three watersheds in Essex County, New York

The U.S. Geological Survey, in cooperation with the New York State Department of Transportation, evaluated the effects of different deicing salt application rates on surface water, groundwater, and highway runoff quality near State highways in northern New York. Three reaches of State highways were tested with different deicing treatments between October 2019 and November 2022: a salt-sand mixture (Treatment A), a salt mixture applied at a lower rate (Treatment B), and a control mixture consistent with typical deicing salt amounts and application rates. Data on pavement conditions and the quality of surface water, highway runoff, and groundwater were collected. Surface electromagnetic data were also collected. Surface-water and groundwater quality downgradient from the State highways were compared with water quality at upgradient locations. The percentage of snow or ice coverage was used to evaluate the effectiveness of the salt applications. This report provides an overview of the transport of deicing salt. The Treatment B watershed had deicing mixture applied more frequently than other highway reaches, which caused it to have the highest annual total chloride application. Despite differences in chloride application, flow-weighted mean chloride concentrations in highway runoff were comparable across treatments. Chloride concentrations were elevated in surface water and groundwater downgradient from highways relative to chloride concentrations upgradient from highways. A chloride mass balance, calculated for one treatment watershed, indicated that groundwater affected by legacy deicing practices may be contributing additional chloride to surface water. Spatial patterns from electromagnetic surveys show a shallow saline plume alongside the highway in that area. Differences in winter severity and pavement-surface conditions drove deicing salt applications in the treatment areas. This study found that several factors affect chloride loads in the watersheds, including variable winter conditions, adaptive snow and ice management, legacy management practices, and area-specific aquifer and groundwater conditions.

New York↗
USGS2024

Insights on gas hydrate formation and growth within an interbedded sand reservoir from well logging at the Qiongdongnan Basin, South China Sea

Although variable well log resolution and its control on saturation estimation has been studied, it has not been directly applied to a specific location to explore the nature of gas hydrate within a sand reservoir. We applied in-situ measurements of resistivities, neutron porosity, and gamma ray at two sites in the Qiongdongnan Basin, South China Sea (QDN-W05–2021 and QDN-W08–2021) to investigate the reservoir parameters of a hydrate-bearing sand reservoir. Our results show that gas hydrate is distributed in 5 zones with a total thickness of 10.7 m and an average saturation of 69% at the QDN-W05–2021 site, while they are distributed in 2 zones with a total thickness of 4.3 m and an average saturation of 49% at the QDN-W08–2021 site. We found that variances in saturations estimated from lateral-extra deep button (RX), phase shift (P40H-P40L), and attenuation (A40H-A40L) resistivities within the laterally mapped continuous sand body were affected by the nature of gas hydrate occurrences. Results indicate gas hydrate forms and accumulates at the center of the sand layer and tends to be less or not present toward the top and base. Integrated with seismic data, the in-situ measurements provide insights in the evolution of a mushroom-shaped, hydrate-gas reservoir system. In the system, free gas is likely horizontally transported from the top-center of the gas chimney to the surrounding areas in the early stage dominated by a warm-gas environment, whereas hydrate forms in the opposite pathway starting from the surrounding areas in the following stage with temperature reducing. Our study suggests that high-resolution in-situ measurements not only are a tool to identify the physical properties, but also can be used to help explain the physical process of hydrate growth and accumulation.

Marine Geology↗
USGS2025

An empirical Green’s function approach for isolating directivity effects in earthquake ground-motion amplitudes

In this study, we apply an empirical Green’s function (eGf) method within a ground‐motion modeling framework to mitigate trade‐offs between source, path, and site effects. Many physical processes contribute to spatial variations in observed ground motions, including earthquake radiation pattern, directivity, variable path attenuation, and site effects. Current nonergodic ground‐motion models use spatially varying coefficients for path and site effects, but they do not address trade‐offs with complex earthquake source effects. To quantify the influence of directivity on ground‐motion amplitudes, we use records from multiple smaller earthquakes with epicenters near that of a larger event. We use these small magnitude events as eGfs and estimate repeatable path and site effects at individual stations, assuming that the average adjustments are not controlled by directivity. We adjust residuals from the larger earthquake using the eGf terms, isolating effects related to the rupture. This method clearly enhances the observed broadband directivity observed in the 2022 M 5.1 and 2007 M 5.4 Alum Rock earthquake ground motions, reinforcing the conclusion that their ruptures were unilateral. For the 2004 M 6.0 Parkfield earthquake, we find a bilateral rupture model better fits the data because variations in rupture velocity, slip rate, and slip distribution seem to have a stronger effect on the ground motions than rupture direction alone. Applying eGf adjustments reduces the standard deviation of the rupture models over the three earthquakes by 32% on average and by up to 57% for the 2022 Alum Rock earthquake, confirming we have effectively removed repeatable effects related to the wave propagation path and site response. We propose a novel measure of the frequency‐dependent directivity amplification strength as the reduction in ground‐motion residual variability gained by fitting a directivity model; for the three earthquakes considered, this parameter varies between 25% and 75%, indicating that directivity can strongly influence ground motions and should be considered in ground‐motion modeling.

California↗
USGS2024

SCEC/USGS Community Stress Drop Validation Study: How spectral fitting approaches influence measured source parameters

Spectral source parameters used to estimate an earthquake’s stress drop (Δσ) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress-Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low-frequency displacement (Ω0) and corner frequency ( f c ) by fitting a smooth function to benchmark displacement spectra. Participants used linear- or log-sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate Ω0, f c , and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in Ω0 and f c can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade-off between Ω0 and f c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω0 and somewhat higher f c compared to those assuming a Brune model, although resulting Δσ estimates are similar. When compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ.

California↗
USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗
USGS2026

Aspergillosis (Avian) case definition for wildlife

Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents. The intent of a case definition is to provide scientifically based criteria for determining: (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition is specific to aspergillosis and applies to all avian species.

Techniques and Methods↗
USGS2024

A comparative analysis of OpenET for evaluating evapotranspiration in California almond orchards

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in soils, age, and variety. It also compares OpenET ensemble evapotranspiration (ET) data with applied irrigation and precipitation records over an additional 148 almond orchards located in the Central Valley of California. Results show OpenET models, including the ensemble ET value, produced reasonable and actionable ET values, with overall coefficient of determination (R 2 ) and mean absolute error values of 0.73- and 0.95-mm d −1 at the daily time step, respectively. However, given the temporal sampling of Landsat (8-day revisit) and the interpolation methods used, the assessed ET models had difficulty in capturing short-term variability in almond ET; for example, the rapid decline in measured ET observed as a response to lack of irrigation preceding and during almond harvest. The study also drew attention to the spatial complexity in scenarios where irrigated orchards are surrounded by hot/dry areas, causing discrepancies between measured and modeled ET values. In comparison with irrigation records, OpenET ensemble ET was capable of quantifying water input (applied irrigation + precipitation) in almond orchards to within 13 % when evaluating monthly data. Initial results presented here reinforce the idea that RSET models, such as in OpenET, are powerful tools, yet their application requires nuanced understanding and careful consideration of local conditions.

California↗
USGS2025

Grammar to graph—An approach for semantic transformation of annotations to triples

Data annotation is the process of labeling data to show the outcome that a related data model should predict. In this study, annotation data were transformed into semantic graph triples, mainly for use with the Resource Description Framework (RDF), a type of entity-relationship-attribute data model for graph databases. The transformation of annotation data to semantic graph triples provides complex linguistic meaning with data handling advantages such as reduced data storage needs, improved logical specification of relations between objects, and reusable classes and properties that support logic and inference. A grammar-based framework in graph form supports user questions and queries. The words defining approximately 334 topographic feature types compiled by the U.S. Geological Survey were tokenized as units of analysis and grouped by part of speech. Their dependency relations were identified for this study using natural language processing libraries. Dependency concepts are used as structured semantic relations among part-of-speech classes. Tokens, units equivalent to words, form instances of classes and were quantified within a tabular output format using PostgreSQL data storage software. Table data were logically aligned as triples following a mapping file and stored with an ontology file using Ontop virtual triplestore software. A grammar ontology schema for the data was synchronized to match queries whose results validated the graph’s structure. The text analysis produced 8 part-of-speech classes of content words for object representations and 4 classes of function words for operational applications. Dependency relations formed 27 ontology properties for topographic subgraph structures. Token occurrences shaped overall ontology salience and formed a lexicon of syntactic terms for subgraph objects and properties. The schema ontology of class and property population shapes formed the lexicon of English terms. SPARQL Protocol and RDF Query Language (SPARQL) was used with the lexicon to conform data to RDF guidelines. This study confirms the hypothesis that although linguistic logic varies from description logic, its approximation applies to ontology design. Property and query use case patterns extracted from the analysis support queries concerning complex topographic relations and patterns normally embedded within text definitions. The method used in this study could be applied to text forms in other domains, such as survey notes.

Scientific Investigations Report↗