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1,606 records · Page 86Linked to original sources
USGS2025

Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration

Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.

Water Resources Research↗
USGS2026

Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?

This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; and (3) a modified composite band-ratio method for Sentinel-2 (SatBathy) with an initial simplified calibration, followed by a more rigorous linear regression against in situ bathymetry data. All methods were tested in three different areas with different geological and environmental conditions, Cabo Rojo, Puerto Rico; Key West, Florida; and Cocos Lagoon and Achang Flat Reef Preserve, Guam. It is demonstrated that all satellite derived bathymetry (SDB) methods have increased accuracy when the results are aligned with higher-accuracy ICESat-2 ATL24 track bathymetry data using the iterative closest point (ICP). SDB vertical accuracy depends more on location characteristics than the method or optical satellite instrument used. All error metrics considered (mean absolute error, median absolute deviation, and root mean square error) can be less than 5% of the maximum bathymetry depth penetration for at least one method, although not necessarily for the same method for all sites. The SDB error distribution tends to be bimodal irrespective of method, satellite instrument, alignment, site, or maximum bathymetry depth, leading to the potential ineffectiveness of traditional error metrics, such as the root mean square error. However, our analysis demonstrates that performing detrending where possible can achieve an error distribution as close to normality as possible for which error metrics are more diagnostic.

Florida↗
USGS2025

Submarine avalanche deposits hold clues to past earthquakes

Earthquakes and other natural events sometimes shake the seafloor near coastlines severely enough to cause underwater avalanches that rush down steep slopes, scouring the seabed and carrying sediment to greater depths. These fast-moving sediment-laden flows, called turbidity currents , have at times damaged underwater infrastructure like pipelines and communications cables, as they did, for example, in snapping transatlantic cables off the coast of Newfoundland after the 1929 Grand Banks earthquake.

EOS Transactions↗
USGS2025

Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia

Seven potential sources of water, consisting of free-flowing discharge from abandoned coal mines at six locations and one abandoned flooded underground coal mine air shaft, were sampled for chemical analysis to assess the quality of the groundwater emanating from the seven mine sources. The six free-flowing mine discharge sources were also assessed for discharge by current-meter measurements on two separate occasions. The U.S. Geological Survey assessed these seven sources to provide information to the City of Gary, West Virginia (W. Va.), and the City of Gary’s consulting engineer with groundwater-quality and flow data to allow them to assess the seven sites as potential alternate sources of water for the City of Gary to augment its existing supply. For the six sites where discharge could be measured, discharge ranged from a minimum of 0.082 cubic feet per second (ft 3 /s) to a maximum of 3.685 ft 3 /s. Of the six sites measured, only two, Harmon Branch at Thorpe, W. Va. (USGS site 372201081303501) and the abandoned public-supply water wells near Havaco, W. Va. (USGS site 372358081344601), had discharge in excess of 1.00 ft 3 /s. Discharge from the abandoned public supply wells was 3.685 ft 3 /s on September 20, 2023, and 2.888 ft 3 /s on October 16, 2023, and discharge from Harmon Branch at Thorpe, W. Va., was 1.049 ft 3 /s on September 22, 2023, and 1.038 ft 3 /s on October 17, 2023. Discharge in the abandoned underground mine air shaft (USGS site 372224081340901) could not be assessed, but the air shaft drains an abandoned mine that likely contains water stored in approximately 1.7 square miles (mi 2 ) of abandoned underground coal mines in the Pocahontas No. 3 coal seam, and possibly an additional 0.9 mi 2 of leakage from the overlying Pocahontas No. 4 coal seam. Discharge for the six sites measured for the study was measured during a period between September 20 and October 18, 2023, and corresponded to the 12th to the 15th percentile of flow-duration statistics for the Tug Fork downstream of Elkhorn Creek at Welch, W. Va. streamgage (USGS site 03212750). Water-quality data for the seven sites sampled overall were acceptable with respect to drinking water standards. Of the 203 constituents analyzed, only a few failed to meet applicable U.S. Environmental Protection Agency (EPA) drinking water standards. Iron exceeded the 300 micrograms per liter (μg/L) secondary maximum contaminant level (SMCL) at only 1 of the 7 sites (14.3 percent) sampled. Iron concentrations ranged from a minimum of less than (<) 5.00 μg/L to a maximum of 724 μg/L with a median concentration of 7.62 μg/L. Manganese exceeded the 50.0 μg/L SMCL at 2 of the 7 sites (28.6 percent) sampled. Manganese concentrations ranged from a minimum of 1.93 μg/L to a maximum of 271 μg/L with a median concentration of 4.03 μg/L. No sites sampled exceeded the arsenic maximum contaminant level (MCL) of 10 μg/L. Arsenic concentrations ranged from a minimum of <0.100 μg/L to a maximum of 2.35 μg/L with a median arsenic concentration of 0.200 μg/L. None of the seven sites sampled for selenium for this study exceeded the EPA MCL of 50.0 μg/L. Selenium concentrations ranged from a minimum of <0.050 μg/L to a maximum of 5.26 μg/L with a median concentration of 3.21 μg/L. All seven sites were sampled for volatile organic compounds (VOCs), semivolatile organic compounds (SVOCs), and polychlorinated biphenyls (PCBs), but most had concentrations below the detection limit. Of the 10 PCB compounds analyzed for the seven sites sampled, none contained detectable concentrations of PCBs or Aroclor compounds. Of the 44 SVOCs analyzed at each of the seven sites sampled, only 1 SVOC, acenaphthene, was detected, at a concentration of 0.02 μg/L. Of the 96 VOCs analyzed, from each of the seven sites sampled, only two were found at detectable concentrations. Trichloromethane was detected only at 1 of the 7 (14.3 percent) sites sampled at a concentration of 0.027 μg/L, and benzene was detected at the same site and 3 additional sites (4 of the 7 sites or 57.1 percent of the sites sampled) at concentrations of 0.028, 0.029, 0.021, and 0.035 μg/L, but none exceeded the EPA MCL for benzene of 5.00 μg/L. Total coliform bacteria are ubiquitous in the environment, and their presence only suggests the potential for contamination by near-surface processes. Escherichia coli ( E. coli ) bacteria are derived from either human or animal fecal material and can be an indicator of potential contamination by pathogenic bacteria or viruses. Total coliform bacteria were detected at all 7 sites sampled at concentrations ranging from 17.5 to greater than (>) 2,420 most probable number per 100 mL (MPN/100 mL) of sample, with a median total coliform concentration of 1,553 MPN/100 mL. Escherichia coli bacteria were detected at 4 of the 7 sites sampled at concentrations ranging from <1 to 11.9 MPN/100 mL, with a median E. coli concentration of 5.1 MPN/100 mL.

West Virginia↗
USGS2026

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

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

Arizona, California, Idaho, Nevada, Oregon, Utah↗
USGS1976

Geology and mineral deposits of the Needle Mountains District, Southwestern Colorado

The Needle Mountains district is set in highly fractured Precambrian granitic rocks that have intruded and metamorphosed older Precambrian metasedimentary rocks. The Precambrian rocks are overlain by outliers of Paleozoic strata and intruded by a late Tertiary stock. Past mineral production reportedly was limited to silver and gold ores presumably taken from small fissure veins. Although the economic potential of the district has not been adequately explored, some evidence indicates potential for base metal deposits.

Colorado↗
USGS2024

Sensitivity of Alabama freshwater gastropod species to nickel exposure

Snails are effective bioindicators due to their prolific distribution, high level of endemism, and capacity to accumulate contaminants. Freshwater snails have unique ecological niches which are imperiled by land‐use change and the introduction of hazardous chemicals. To assess how environmental alterations affect gastropods, lab‐based studies are needed to characterize the toxicity of specific stressors. This can help guide policy decisions and remediation efforts. The aim of this research was to characterize acute toxicity of nickel (Ni) on endemic snails ( Somatogyrus georgianus [Walker, 1904], Elimia cahawbensis [Lea, 1861], and Elimia spp.) and measure the accumulation of Ni and mineral elements including calcium (Ca), magnesium, potassium, and sodium (Na). Snails were exposed to six concentrations (25–800 µg/L) of Ni for 96 h. Among the studied snail species, E. cahawbensis was the most sensitive to Ni, with the lowest lethal concentration where 50% of the organisms died (LC50) at 88.88 µg/L Ni after 96 h. The LC50 at 96 h for S. georgianus was 167.78 µg/L Ni, and 393.13 μg/L Ni for Elimia spp. Except for Elimia spp., mortality of the other two snail species corresponded to the whole‐body uptake of Ni. Nickel exposure also influenced Ca and Na uptake for Elimia spp. All three endemic species are potential candidate species for evaluating localized effects of human activities, and the present study provides a first step in characterizing how snails would be affected by environmental alterations. More research could further characterize potential effects of other human stressors on these endemic snail species. Future research into subindividual responses and routes of exposure can further elucidate variations in species sensitivity.

Alabama↗
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↗
USGS1976

Distribution functions for statistics derived from bivariate normal and bivariate two-parameter log-normal populations

The distribution functions for statistics that may be used to assess the significance of differences between sample means, standard deviations, coefficients of skewness, and coefficients of variation are obtained by Monte Carlo experiments. The distributions are expressed as functions of sample size, cross correlation, and skewness. In general, the distributions are more sensitive to cross correlation than to skewness. As sample size increases, however, the distributions tend to become more sensitive to skewness.

Open-File Report↗
USGS2026

Structural evolution and slip rate variations through time of the Puente-Hills blind-thrust fault beneath Los Angeles: Implications for seismic hazard and folding kinematics

Using seismic reflection profiles, historical well logging data, and luminescence and radiocarbon ages, we determine a Pleistocene-Holocene slip history for the central, Santa Fe Springs segment of the Puente Hills blind-thrust fault (PHT), a major seismogenic fault situated beneath the urbanized Los Angeles metropolitan region. We analyze the geometry of correlative stratigraphic units in the forelimb and backlimb of the overlying growth-fold, the Santa Fe Springs anticline, and determine the uplift of seven age-correlative markers. Uplift measurements are converted to thrust displacements on the underlying PHT using a structural method laid out by Don et al. (2022, https://doi.org/10.1785/0120220048 ) that accounts for the geometry of the fault. These data indicate that deep thrust displacement on the PHT is partially consumed updip in the creation of a hanging-wall fault-bend fold, with forelimb growth strata recording <80% of the slip documented within the backlimb. Chronological data from growth strata yield age constraints for folding and faulting on the underlying PHT, providing a detailed incremental slip history derived from both the forelimb and backlimb folding for seven discrete growth horizons, spanning the past 1.4 million years. The resulting six incremental slip rates demonstrate that fault slip has varied through time from the middle Pleistocene to the Holocene. Moreover, these results reveal synchronous acceleration of both the central, Santa Fe Springs and western, Los Angeles segments of the fault system since late Pleistocene time (after 200 ka) and slip rates of greater than 2 mm/yr on the downdip, backlimb, fault-ramp below the anticline.

California↗
USGS2024

New developments at the Center for Engineering Strong-Motion Data (CESMD)

The Center for Engineering Strong-Motion Data (CESMD), an internationally utilized joint center of the U.S. Geological Survey (USGS) and the California Geological Survey (CGS), provides a single access point for earthquake strong-motion records and station metadata from the CGS California Strong-Motion Instrumentation Program (CSMIP), the USGS National Strong-Motion Project (NSMP), the USGS Advanced National Seismic System, and other affiliates. The CESMD has been continuously improving its webtools to facilitate the access of strong-motion data and metadata for use in post-earthquake response and for scientific and engineering research applications. The Center provides raw and processed strong-motion data via the Engineering Data Center (EDC) and the Virtual Data Center (VDC) web portals. This paper focuses on the strong-motion products provided by the EDC where more than 48,000 records with peak ground accelerations greater than 0.1% g from over 2400 earthquakes are currently hosted. and on the ongoing efforts to develop data access tools and applications. The new developments and ongoing efforts in the EDC include: 1) enhancements to the CESMD webservices to facilitate access to station metadata, earthquake information, and strong motion records 2) new features to the interactive map interface, improving the visualization and access to earthquake, station, and record information, 3) efforts to develop a new web application tool for data format conversion from a number of data formats, 4) efforts to unify varying waveform data formats into a consistent format, 5) ongoing efforts to compile seismic station site geology, measured or inferred Vs30 values, shear-wave profiles, NEHRP site class, and available structural instrument deployment schematics, and 6) a special studies pages for research topic-specific ground motion datasets that offer uniform processing of records from a variety of sources.

Conference Paper↗
USGS2026

Riverscape heterogeneity shapes population diversity for a migratory fish

Habitat patch dynamics can scale up to influence population demography and diversity with implications for resilience to environmental stochasticity. But how the spatial arrangement and size of habitat patches interact with other components of habitat heterogeneity to shape population diversity at larger spatial scales is not well understood. For riverine fishes, there is increasing evidence that tributary streams provide critical demographic support to main stem rivers. However, the extent to which main stem rivers rely on demographic contributions from tributaries, and the factors underlying this dependence, have not been assessed. Here, we used genetic stock identification to evaluate the effect of tributaries on population diversity of Yellowstone cutthroat trout ( Oncorhynchus virginalis bouvieri ) occupying the main stem Snake River, Wyoming, USA. We found that the main stem relied almost entirely on tributaries for demographic support, but main stem composition varied spatially among river sections. Distance between habitat patches, catchment area, and groundwater availability acted in concert to determine the contribution of specific tributaries to the main stem, but contributions were ultimately modulated by habitat connectivity. We also found evidence for multi-scale spatial structure in tributary contributions, providing insight into untested drivers of main stem river population diversity. Our results demonstrate how spatially discrete and distributed riverscape attributes influence population diversity at broader spatial scales, illustrating how ecosystem resilience emerges from the dynamic, two-way exchange of individuals and energy across habitat networks. Management plans for large rivers that address the ecological contributions of tributaries may be needed to achieve optimal outcomes. Similarly, conservation strategies that exclusively focus on headwater streams may fail to capture the broader habitat requirements necessary to maintain robust cold-water fish populations and associated recreational fisheries, particularly under global environmental change.

Wyoming↗
USGS2024

A journey to the center of the USGS National Strong-motion Project processing and beyond

The United States Geological Survey (USGS) National Strong Motion Project (NSMP) has the primary U.S. government responsibility to acquire, process, and disseminate significant strong-motion earthquake ground motion records measured at surficial free-field stations, structures (buildings, dams, and bridges, and geotechnical arrays to the earthquake engineering community. As a result of the deployment of modern seismic instrumentation and growth of tools such as web-services, earthquake data from U.S. and international seismic networks are more accessible than ever. Our mission is to provide raw and processed strong-motion waveforms with PGA values greater than 0.1%g for M3.0 earthquakes and larger in California and M4.0 and larger within the conterminous US, Hawaii, Puerto Rico, and Alaska. Datasets of interest to the engineering and geophysics communities, such as event sequences in areas of induced seismicity and significant global events, are also processed and posted at the Center for Engineering Strong Motion Data (CESMD) at strongmotioncenter.org when available through collaboration with the international strong-motion data community. Here we outline (1) the NSMP’s current workflow to acquire, process, and distribute data at CESMD; (2) our new endeavours and collaborations focusing on comparison and integration of waveform processing software, development of techniques for metadata quality checks before and after earthquakes, and construction of a dynamic site characterization repository; and (3) our topics for possible collaboration topics across the global strong-motion community.

Conference Paper↗
USGS2025

Estimating earthquake source depth using teleseismic broadband waveform modeling at the USGS National Earthquake Information Center

The U.S. Geologic Survey National Earthquake Information Center (NEIC) monitors global seismicity, producing a catalog of earthquake source parameters in near-real-time to provide information that can help mitigate the societal impact of earthquakes. The NEIC commonly relies on teleseismic observations to constrain earthquake source parameters (e.g., location, depth, magnitude, and mechanism) due to a lack of local and regional observations. For these ‘teleseismic’ events, depth phase (i.e., pP , sP ) arrival time observations provide the best estimate on source depth. However, depth phases are often difficult to accurately identify and/or pick. Therefore, NEIC relies on waveform modeling, such as those determined from W-phase ( M ww ), body wave ( M wb ), and regional ( M wr ) moment tensor estimations, to provide constraints on source depth. While depth estimates from these approaches are informative, higher frequency observations provide more precise estimates because depth phases are more prominently observed at higher frequencies. Here, we present NEIC’s relatively high-frequency (~0.04 to 1 Hz) teleseismic waveform modeling approach, termed Synthetic Depth Phase Modeling (SynDepth), for determining source depth. SynDepth was developed to provide NEIC with a tool that enables rapid, accurate, and quantifiable estimates of earthquake source depth in cases where locator depths are not reliable. This relatively simple and fast procedure searches over 1 km-incremented source depths and an expanding triangular source-time function to find the best-fitting solution. We compare automatic SynDepth solutions for a dataset of 1,216 earthquakes (M5.5-M7.6) between 2017 and 2021 to NEIC-derived depth estimates from other methods. Our approach provides a robust depth estimate for earthquakes lacking local arrival time data, and it minimizes the need for analyst review of depth-phase picks ( pP , sP ) or using predefined ‘fixed’ depths.

Seismological Research Letters↗
USGS2026

Streamflow, base-flow, and precipitation trends and simulated effects of groundwater withdrawals from the North Fork Red River aquifer on base flows upgradient from Lake Altus, western Oklahoma, 1980–2022

The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, used five scenarios created from a previously published numerical groundwater-flow model (1980–2013) and historical streamflow records (1980–2022) to investigate the relation between groundwater withdrawals from the North Fork Red River aquifer and inflows to Lake Altus from the North Fork Red River in western Oklahoma. The five scenarios were (1) a scaled-equal-proportionate-share (EPS) groundwater-withdrawal scenario, (2) a study-area-scaled-reported groundwater-withdrawal scenario, (3) a zonal-scaled-reported groundwater-withdrawal scenario, (4) a historical drought-threshold scenario, and (5) a base-flow and evapotranspiration depletion scenario. For the scaled-EPS groundwater-withdrawal scenario, EPS groundwater withdrawals were often much higher than reported groundwater withdrawals and greatly decreased base flows for most scale factors. For the study-area-scaled-reported groundwater-withdrawal scenario, base flows were reduced more but by smaller percentages during wet periods than during dry periods when scaling simulated reported groundwater withdrawals. For the zonal-scaled-reported groundwater-withdrawal scenario, scaling simulated reported groundwater withdrawals within selected zones with more groundwater withdrawals did not always affect base flows more than scaling reported groundwater withdrawals within zones with less groundwater withdrawals. For the historical drought-threshold scenario, curtailing groundwater withdrawals at the drought thresholds increased annual base flows to Lake Altus by about 1,169 to 3,665 acre-feet. For the base-flow and evapotranspiration depletion scenario, the distance between a groundwater well and a stream was a major factor affecting base flow to the North Fork Red River when increasing groundwater withdrawals; however, spatially variable hydrologic properties and saturated-zone evapotranspiration could also affect the relation between base flows and groundwater withdrawals.

Oklahoma↗
USGS2026

Utilization of multiple geochronology techniques to constrain the age of laterization and mineralization of the world-class Mount Weld rare earth element deposit, Western Australia

Pervasive chemical weathering on stable cratons may form thick regoliths and elemental enrichment, but constraining the age of regolith formation is challenging. In this study we utilize multiple geochronological techniques on different minerals from the world-class Mount Weld rare earth element (REE) deposit, formed by lateritic weathering of a carbonatite, to constrain the age of formation and provide insight into landscape evolution. The oldest dates, ca. 100 to 38 Ma, are from Lu-Hf dating of churchite [HREE(PO 4 )·2(H 2 O)], a heavy REE phosphate mineral. Growth bands on individual minerals show a younging outwards. 40 Ar/ 39 Ar geochronology of cryptomelane [K(Mn 4+ ,Mn 2+ )₈O₁₆] yielded dates from ca. 40 to 27 Ma. Similarly, (U-Th)/He geochronology of goethite [FeO(OH)] yielded dates ranging from ca. 45 to 19 Ma. Integrating results into regional constraints, suggests 1) churchite formed by mineral saturation in a karst-like setting below the water table from ca. 100 to 40 Ma, 2) with minor uplift and erosion, cryptomelane and goethite formed at or near the water table between ca. 45 and 19 Ma, 3) after ca. 15 to 10 Ma chemical weathering within the profile had ended. Other studies document that the region experienced minimal uplift and a wet, warm climate from ca. 100 Ma to 15 Ma. These conditions and the high carbonate content of the carbonatite promote extensive chemical weathering, a deep weathering profile, and the preservation of the weathered section. This study highlights the use of multiple geochronological techniques utilizing different minerals to provide insight into how laterites form and to constrain the timing and history of the formation of this important mineral deposit.

Western Australia↗
USGS2025

Refinements to the attenuated propagation of local earthquake shaking (APPLES) ground-motion-based earthquake early warning algorithm

We refined the Attenuated ProPagation of Local Earthquake Shaking (APPLES) ground-motion-based earthquake early warning (EEW) approach, and directly compare APPLES performance with that of the source-characterization-based U.S. ShakeAlert EEW system for a suite of historical earthquakes in the U.S. West Coast and Japan. APPLES is an extension of the Propagation of Local Undamped Motion (PLUM) algorithm in which observed shaking intensity at seismic stations is used to forward-predict intensity distributions to surrounding areas using an attenuation model derived from an intensity prediction equation. We test new configuration options within APPLES, such as using the second highest estimated ground motion rather than the maximum, to better match median ground-motion observations and reduce alerts for small magnitude earthquakes, both of which are key alerting priorities within ShakeAlert. We evaluate these configurations alongside ShakeAlert by comparing the ground-motion estimation accuracy and available warning times relative to station observations and ShakeMap distributions. Our preferred APPLES configuration produces accurate ground-motion estimates and corresponds better with median observations compared to ShakeAlert’s estimates. This preferred configuration substantially reduces alert issuance for M < 5.0 earthquakes compared to the previous APPLES configuration, and alert-release criteria can further restrict alerts to primarily M ≥ 5.5 earthquakes without requiring magnitude estimation. Prioritizing matching median-observed ground motions may reduce APPLES warning times compared to configurations that were tuned to avoid missed alerts (such as those that use the maximum estimated ground motions), which can lead to shorter warning times compared to ShakeAlert for the same alert threshold. However, station-based warning time assessments demonstrate that APPLES can outperform ShakeAlert for high target thresholds. APPLES is a simple, independent EEW approach that may improve the robustness of EEW for the West Coast of the U.S.

California, Oregon, Washington↗
USGS2026

Using a temporary emigration model to estimate abundance of stream fishes from hybrid removal surveys with and without block nets

Monitoring programs are often faced with a decision to allocate resources into either robust spatiotemporal coverage to estimate a population index (e.g., not true abundance) or confirming closed sampling conditions (e.g., with block nets) for an unbiased population estimate at the cost of spatiotemporal coverage. However, making accurate and precise abundance estimates at robust spatiotemporal scales is possible when combining open and closed sampling designs with integrated modeling techniques. We used simulations and a case study of backpack electrofishing surveys in the Santa Ana River, California to test the efficacy of an integrated abundance model (temporary emigration model, TE) to estimate abundance of fishes using removal sampling methods with a hybrid sampling design (sampling with and without block nets during removal sampling). We found that the TE model performed well under most modeling scenarios (sample size, amount of closure violation, number of samples collected during closure), although at least a few samples with block nets were necessary for all parameters to be estimable. When applied to fish surveys in the Santa Ana River, we found that catch of the fishes fit to the TE model (Santa Ana Sucker, Arroyo Chub, Channel Catfish, Largemouth Bass, Yellow Bullhead) showed little evidence that the closure assumption was violated when block nets were not used. Additionally, we found that the abundance of non-native fishes negatively affected the abundance of the native Santa Ana Sucker, which was also found to adversely affect the native fish’s access to critical habitat consisting of gravel and cobble substrate. Our results indicate that the TE model presents a viable solution to common sampling problems that impact many monitoring programs, where precise and accurate population estimates can be made at large spatiotemporal scales even when most samples violate the closure assumption.

California↗