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USGS2026

Estimating aftershock risk for entry into earthquake-damaged buildings

We present a simple method to estimate the risk of experiencing strong shaking from aftershocks during entry into earthquake-damaged buildings. We compute wait times until the probability of strong ground shaking from aftershocks reaches a predefined risk threshold; for example, a 0.4 percent probability of experiencing Modified Mercalli Intensity 7 or greater shaking during the planned building entry. We also develop a relation between aftershock probability and the probability of strong shaking, so that users can reference the U.S. Geological Survey aftershock forecast during an ongoing aftershock sequence to determine if the risk threshold has been met. We apply our method to active continental regions (for example, the Western United States), stable continental regions (for example, the Central and Eastern United States), and subduction zones (for example, Cascadia or Alaska).

Open-File Report↗
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↗
USGS2026

pySATSI: A Python package for computing focal mechanism stress inversions

We introduce pySATSI, a Python package for computing earthquake focal mechanism stress inversions. This algorithm can handle a wide variety of types of stress inversion problems with a single script and can duplicate many capabilities of preceding methodologies. We also add new capabilities that include spatiotemporally variable inversion grids, damped stress estimates for clusters with few or no focal mechanisms, and variable fault‐plane ambiguities that the user can assign to individual events. In addition, we added the ability to use damped stress inversions with fault‐plane ambiguity probabilities that are weighted by fault instabilities. Our algorithm is computationally efficient with faster runtimes than previous algorithms, scales well for large datasets, and can be easily parallelized.

Seismological Research Letters↗
USGS2025

Earthquake recurrence estimates for northern Caribbean faults from combinatorial optimization

We use combinatorial optimization to find the optimal spatial distribution of random samples of earthquakes (≥6.5) that minimize the misfit in target slip rates for all faults in the northeast Caribbean, and we derive magnitude-frequency relationships with uncertainties for these faults. Slip rates for many faults are derived from GPS block models, not direct measurements, because of their underwater locations. Predicted recurrence rates for eastern Hispaniola and Puerto Rico Trench faults are 220-450 yr for M7 and 3-5 kyr for M8, with maximum feasible magnitude of M8.2. The most frequent earthquakes with magnitudes ≥7.0 are predicted on the large upper plate strike-slip faults, Enriquillo (EF) and Septentrional Fault, commensurate with the historical record. Calais et al. (2023) suggested that shortening in western Hispaniola is accommodated on the offshore Jérémie and onshore Malpasse faults north and south of EF, instead of on terrestrial faults in western Hispaniola and EF. Because of our system-modeling approach, such a configuration predicts less frequent earthquakes on EF and on western Hispaniola and Muertos convergent zones. Recurrence times of a few 100s yr for M6.7 earthquakes is predicted on the submerged faults in Mona Passage, and infrequent M>7 earthquakes are predicted on the Virgin Islands faults.

Lesser Antilles↗
USGS2000

Method for estimating water use and interbasin transfers of freshwater and wastewater in an urbanized basin

Techniques for management of drainage basins that use water budgets to balance available water resources with actual or anticipated water use require accurate and precise estimates of basin withdrawals, interbasin transfers of freshwater, unaccounted-for use, water use, consumptive use, inflow and infiltration, basin return flow, and interbasin transfers of wastewater. Frequently, interbasin transfers of freshwater and wastewater are not included in basin water budgets because they occur within public water-delivery and wastewater-collection systems. A new 10-step method was developed to improve estimates of inflow and infiltration and interbasin transfers using readily available statewide data. The accuracy and precision of water-use estimates determined by this method are improved through careful application of coefficients for small users and the use of metered values for large users. The method was developed and tested with data for the Ten Mile River Basin in southeastern Massachusetts. This report uses examples from the basin to illustrate each step of the method.

Massachusetts↗
USGS1997

Analysis of minimum 7-day discharges and estimation of minimum 7-day, 2-year discharges for streamflow-gaging stations in the Brazos River basin, Texas

The minimum 7-day, 2-year discharge (7Q2) was estimated for each of 97 streamflow-gaging stations in the Brazos River Basin, Texas, with at least 10 years of unregulated or 10 years of regulated discharge data using the Pearson Type III distribution fitted by L-moment statistics of the annual minimum 7-day discharges. Forty-six stations have at least 10 years of unregulated discharge data only, 26 stations have at least 10 years of regulated discharge data only, and 25 stations have at least 10 years of unregulated and 10 years of regulated discharge data. Statistical tests were applied to the annual minimum 7-day discharges to determine if the unregulated and regulated data have trends; and to determine if the data before regulation are significantly different from the data after regulation. Results of the Mann-Kendall test indicate a significant trend at the 95-percent confidence level for 8 of the 46 unregulated-only stations, for 6 of the 26 regulated-only stations, and for 5 stations before regulation and for 10 stations after regulation of the 25 stations with both unregulated and regulated data. Results of the Wilcoxon rank-sum test indicate a significant difference between the unregulated and regulated annual minimum 7-day discharges at the 95-percent confidence level for 16 of the 25 stations with both types of data. The 7Q2 is zero for 31 of the 46 unregulated-only stations and for 9 of the 26 regulated-only stations. The 7Q2 also is zero for 9 stations before regulation and for 3 stations after regulation of the 25 stations with both unregulated and regulated data. The 7Q2 ranges from 33 to 631 cubic feet per second for the eight regulated-only stations on the mainstem Brazos River. For the seven stations on the mainstem Brazos River with at least 10 years of unregulated and 10 years of regulated discharge data, the 7Q2 ranges from 0 to 568 cubic feet per second before regulation and from 0.30 to 670 cubic feet per second after regulation. The 7Q2 increased during regulation for 19 of the 25 stations with both unregulated and regulated data. The effect of regulation for most stations generally was an increase in the magnitude of the 7Q2.

Texas↗
USGS2023

WellSTIC: A cost-effective sensor for performing point dilution tests to measure groundwater velocity in shallow aquifers

Many individual measurement points are required to characterize groundwater velocity within an aquifer. Groundwater velocity is most commonly measured using a network of >5 cm diameter monitoring wells, which, if not already present at a site, are expensive and labor-intensive to install. Drive-point piezometers—simple, cost-effective wells that can be installed by hand—are a common tool for sampling groundwater in shallow, alluvial aquifers, but most groundwater velocity measurement techniques require equipment that is too large for these narrow (usually <2 cm inside diameter) piezometers. In this technical note, we introduce a low-cost sensor and well packer system (<$90 USD) for performing point dilution tests in narrow piezometers. Field data show that the magnitude of groundwater velocity measured with this technique agrees with velocities computed from natural gradient tracer tests. Additionally, with proper calibration, these sensors can be used to continuously monitor in-well specific conductance, either during inter-well tracer tests with saline tracers or for water quality monitoring. This system is a viable tool for rapid assessment of the magnitude of groundwater velocity in shallow aquifers.

Water Resources Research↗
USGS2026

Standardized method for logging drill core at the Idaho National Laboratory, Idaho

The U.S. Geological Survey’s (USGS) Lithologic Core Storage Library (CSL) at the Idaho National Laboratory stores more than 120,000 feet of drill core that is accessible to the public for research and sampling. To effectively convey the physical and descriptive properties of the drill core, USGS staff at the Idaho National Laboratory Project Office log the drill core and publish the lithologic logs as data releases. The logs provide essential data on the lithology, texture, mineralogy, alteration, and other physical properties of the core, which serve as valuable information for researchers to guide their research and sampling efforts. To ensure consistent, quality, and dependable lithologic logs, this document outlines the procedures and expectations for logging drill core at the CSL. This document describes the processes for storing, photographing, and logging core, and includes a variety of resources, reference materials, and appendixes designed to standardize and aid the logging process. Following the procedures outlined in this document will produce consistent, detailed logs that facilitate dependable observations and serve as an easy reference for researchers and other interested parties.

Idaho↗
USGS2000

Assessment of potential for natural attenuation of chlorinated ethenes and ethanes in ground water at a petrochemical reclamation site, Harris County, Texas

Redox conditions in the Numerous Sand Channels Zone beneath a petrochemical reclamation site in Harris County, Texas, range from sulfate reducing to methanogenic as indicated by the presence of methane in ground water and the range of molecular hydrogen concentrations. Assessment of the potential for reductive dechlorination using BIOCHLOR as a screening tool indicated conditions favoring anaerobic degradation of chlorinated organic compounds in the Numerous Sand Channels Zone. Evidence supporting reductive dechlorination includes apparently biogenic cis -1,2-dichloroethene; an increased ratio of 1,2-dichloroethane to 1,1,2-trichloroethane downgradient from the assumed contaminant source area; ethene and methane concentrations greater than background concentrations within the area of the contaminant plume; and a positive correlation of the ratio of ethene to vinyl chloride as a function of methane concentrations. The body of evidence presented in this report argues for hydrogenolysis of trichloroethene to cis -1,2-dichloroethene; of 1,1,2-trichloroethane to 1,2-dichloroethane; and of vinyl chloride to ethene within the Numerous Sand Channels Zone. Simulations using BIOCHLOR yielded apparent first-order decay constants for reductive dechlorination in the sequence tetrachloroethene trichloroethene cis -1,2-dichloroethene vinyl chloride ethene within the range of literature values reported for each compound and apparent first-order decay constants for reductive dechlorination in the sequence 1,1,2-trichloroethane 1,2-dichloroethane slightly greater than literature values reported for each compound along the upgradient segment of a simulated ground-water flowpath. Except for vinyl chloride, apparent rates of reductive dechlorination for all simulated species show a marked decrease along the downgradient segment of the simulated ground-water flowpath. Evidence for reductive dechlorination of chlorinated ethenes within the Numerous Sand Channels Zone indicates potential for natural attenuation of chlorinated ethenes. Reductive dechlorination of chlorinated ethanes apparently occurs to a lesser extent, indicating relatively less potential for natural attenuation of chlorinated ethanes. Additional data are needed on the concentrations and distribution of chlorinated ethenes and ethanes in individual fine sand intervals of the Numerous Sand Channels Zone. This information, combined with lower minimum reporting levels for future chloroethane analyses, might enable a more complete and quantitative assessment of the potential for natural attenuation at the site.

Texas↗
USGS2024

Getting to the surface of the problem: A dynamic rupture benchmark for shallowly dipping faults near Earth’s surface

The Statewide California Earthquake Center (SCEC) Dynamic Rupture Group workshop “Getting to the Surface of the Problem: A Dynamic Rupture Benchmark for Shallowly-Dipping Faults Near Earth’s Surface” was convened virtually, in an online meeting on November 4, 2024. 52 people participated, including two who sent pre-recorded lightning talks earlier, but were unable to join us that day due to the international time-zone difference. One-half of our participants were students or postdocs, and the group included scientists from 11 countries (USA, Canada, China, Czech Republic, France, Germany, Iceland, Japan, New Zealand, Saudi Arabia, Switzerland).

Final Report↗
USGS2024

Case definitions for wildlife diseases

Welcome to the first manual of “Case Definitions for Wildlife Diseases,” a “living” electronic publication. The plan is to add and update this manual’s case definitions periodically as warranted; thus, this manual will never be completed, and readers should download the latest versions of specific chapters (that is, definitions) when available. Constructive suggestions from readers are welcome and will help guide adjustments as this project progresses. The purpose of this manual is to provide case definitions for selected diseases of importance to wildlife in Canada and the United States. Case definitions provide standard sets of criteria for classifying the degree of certainty of a particular diagnosis and help improve surveillance data quality and comparability. Better data and standardization allow for improved data sharing, which increases geographic and species surveillance coverage and permits more robust analyses. The definitions included in this manual have been developed by veterinary pathologists, epidemiologists, and wildlife biologists primarily from the U.S. Geological Survey National Wildlife Health Center (NWHC) and Canadian Wildlife Health Cooperative (CWHC). Pathologists from each organization reviewed and finalized the definitions. Each case definition has been peer reviewed by two scientific experts before publication. This manual begins with the case definition template. This generic template includes four sections: “Individual, Place, and Time Criteria for Diagnosis and Testing,” “Field Criteria for Diagnosis,” “Laboratory Criteria for Diagnosis,” and “Epidemiological Linkage Criteria for Diagnosis” and can be used to guide development of new case definitions. Information in each section is then combined to provide an overall case classification. Disease diagnoses are classified as “Confirmed,” “Presumptive,” or “Suspected;” and evidence of a pathogen or toxin is classified as “Exposed” or “Present/Detected.” Each subsequent chapter is then a case definition for a specific disease of wildlife, and infectious and non-infectious diseases are included.

Techniques and Methods↗
USGS2025

A model uncertainty quantification protocol for evaluating the value of observation data

The history-matching approach to parameter estimation with models enables a powerful offshoot analysis of data worth—using the uncertainty of a model forecast as a metric for the worth of data. Adding observation data will either have no impact on forecast uncertainty or will reduce it. Removing existing data will either have no impact on forecast uncertainty or will increase it. The history-matching framework makes it possible to perform this quantitative analysis leveraging the connections among observations, model parameters, and model forecasts. We show this behavior on a specific groundwater flow model of the Mississippi Alluvial Plain and show where the analysis can be informative for considering the potential design of an observation network based on existing or potential observations.

Scientific Investigations Report↗
USGS2026

A process-based model for forecasting wave runup along the coast of Georgia

Wave runup is an important nearshore process that impacts total water level, sediment transport, and coastal design. Current methods for forecasting wave runup implement an empirical model that considers offshore wave height, wave period, and generalized beach slope. In this study, the authors generated wave runup forecasts from offshore wave conditions and a system of polynomial equations derived from numerical simulations at three different still water datums for each beach profile. They developed a process-based methodology that incorporated site-specific cross-shore topobathy into the phase-resolving numerical model. A comparison between the system of equations, deterministic hydrodynamic simulations, and observed high-water marks was made using Hurricanes Matthew (2016) and Irma (2017) for 12 cases, and it showed that the polynomials were capable of being consistent with the results from full simulation runs, while not requiring hours of runtime when a forecast was needed—the differences between the polynomial and the observed high water marks ranged from 3 to 32 cm for the Irma hindcast and 9–70 cm for Matthew. Then, using forcings from Hurricanes Ian and Nicole (2022), the model predicted the occurrence of dune collision, overwash, and inundation for the coast of Georgia and suggested that wave runup was impacted by the still water level and local topobathy.

Georgia↗
USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗
USGS2025

Enhanced geothermal systems electric-resource assessment for the Great Basin, southwestern United States

The U.S. Geological Survey recently (2025) completed a provisional assessment of the geothermal-electric resources associated with high-temperature, low-permeability rock formations of the Great Basin, Southwestern United States. If sufficient technological advances to commercialize enhanced geothermal systems occur, then a current best provisional estimate for electric-power generation capacity of 135 gigawatts electric are available from the upper 6 kilometers of the Earth’s crust. This estimate is a potential substantial increase of the installed geothermal electricity-generating capacity from <1 to 10 percent of current total U.S. power production capacity.

California, Idaho, Nevada, Oregon, Utah↗
USGS2025

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↗
USGS2025

The feasibility of using lidar-derived digital elevation models for gravity data reduction

Gravity data require submeter elevation accuracy for data processing, and differential global navigation satellite system (dGNSS) equipment is commonly used to acquire three-dimensional positional data to achieve such accuracy. However, lidar (light detection and ranging) data are commonly used to develop digital elevation models (DEMs) of Earth’s surface. Therefore, using elevations from lidar-derived DEMs for gravity-data acquisition and reduction may improve field efficiency and reduce cost. This study examines the feasibility of using DEMs for gravity-data reduction by comparing dGNSS elevation data from 435 gravity stations in Michigan, Wyoming, and Colorado with their respective DEM elevations. The results show that the average difference between DEM and dGNSS elevations is 13 centimeters (cm) and that 93 percent of those differences are less than 50 cm, even in areas with steep terrain. Because an elevation discrepancy of 50 cm corresponds to an error of roughly 0.1 milligals (mGal) in the simple Bouguer gravity anomaly, the results suggest that lidar-derived DEMs are a viable source for acquiring the elevation data needed to process gravity data, thus improving both the cost and efficiency of data collection for regional surveys where an accuracy of less than 1.0 mGal is desired.

Open-File Report↗
USGS2026

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters↗