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1,193 records · Page 46Linked to original sources
USGS2025

Geochemical and hydrological investigations of historical data collected at the Lee Acres Landfill and Giant Bloomfield Refinery, New Mexico, 1985–2020

The Lee Acres Landfill and Giant Bloomfield Refinery are adjacent properties near the City of Farmington, New Mexico, each having undergone monitoring and remediation related to historical site activities. At the landfill, site cleanup has included the installation of a capillary barrier over former liquid waste lagoons and periodic monitoring of groundwater elevations and groundwater quality. At the refinery, remediation has focused on several petrochemical and crude oil release areas and included soil excavation, groundwater treatment, and regular monitoring of groundwater elevations and quality. Groundwater at both sites has higher concentrations of volatile organic compounds and trace metals than background aquifer concentrations. In 2022, the U.S. Geological Survey compiled the Lee Acres-Giant Bloomfield Refinery Database (LAGBRD), which contains publicly available groundwater-elevation data and organic and inorganic groundwater-quality data from both sites, spanning from 1985 to 2020. Data from the LAGBRD and precipitation data from other sources were used to better understand the cause of relatively high manganese concentrations observed in some groundwater wells at the site through comparison of groundwater chemistry to chemical end members, interpretation of spatial and temporal patterns in the groundwater chemistry, and interpretation of groundwater flow properties. In this study, elevated chloride concentrations in groundwater downgradient from the landfill have been attributed to landfill leachate based on the temporal and spatial variability of chloride concentrations and chloride-to-bromide ratios. Installation of a capillary barrier and surface-water runoff controls at the landfill in 2005 appears to have altered infiltration patterns at that site, resulting in a decrease in chloride at some wells but an increase in chloride and dissolved manganese at others. The timing and relation among groundwater elevation, chloride concentration, and manganese concentration suggest that leachate stored in the vadose zone provides a continued source of contamination to groundwater.

New Mexico↗
USGS2026

Tracking baseflow supply dynamics using SWOT data from small groundwater-dominated lakes

In situ surface-water monitoring strategies are biased towards larger perennial streams and lakes and are generally not designed to track mechanisms of baseflow supply contributed by the dynamic storage of aquifers. Additionally, small (< 1 km 2 ) groundwater-influenced lakes and wetlands globally have little in situ monitoring infrastructure. We explored the utility of remotely sensed Surface Water Ocean Topography Satellite (SWOT) data, collected from 2023 onward, to characterise the seasonal and multi-year water-level trends of groundwater flow-through kettle lakes distributed across the permeable sediments of eastern Massachusetts, USA. This analysis indicated that water levels for kettle lakes with areas down to approximately 0.05 km 2 are resolvable in the study area. Our examination of 17 kettle lakes found that SWOT water-surface elevation data closely tracked groundwater levels in adjacent monitoring wells where available, including the timing of seasonal patterns (highest levels generally in late spring), although there was some variation between years and there was a substantial lag in the timing of high water levels for a lake located downgradient from a 30-m-thick vadose zone. Furthermore, SWOT-observed water-level increases in kettle lakes tracked with baseflow increases in two adjacent groundwater-dominated streams, as would be expected from increased hydraulic gradients. Unlike spectral remote sensing, SWOT data are generally not affected by cloud cover, resulting in a potential for groundwater-dominated lakes to be sentinels of dynamic storage patterns, including identification of baseflow drought lags, which are currently ill-defined hydrological processes. SWOT monitoring of groundwater-influenced surface waters shows potential for augmenting existing monitoring wells and streamgages as continuous monitors of groundwater levels and baseflow supply in permeable terrain.

Massachusetts↗
USGS2025

Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery

The U.S. Geological Survey and the U.S. Fish and Wildlife Service have developed a three-tiered strategy for monitoring eelgrass ( Zostera marina ) beds at Izembek Lagoon, Alaska, that targets different spatial and temporal scales. The broadest-scale monitoring (tier-1) uses satellite imagery about every 5 years to delineate the spatial extent of eelgrass beds throughout the lagoon. This report describes the most recent (mid-2020s) tier-1 eelgrass monitoring at Izembek Lagoon. The monitoring effort began by canvasing all satellite imagery collected during summer, under clear daytime skies and at low-tide, since the last tier-1 effort in 2006. Two eelgrass maps of Izembek Lagoon were generated by first creating maps of spectrally unique classes from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing those spectral classes with information about eelgrass conditions based on field data. Specifically, maps depicting various eelgrass metrics, such as percentage of cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons of the 2016 and 2020 Sentinel-2 maps showing eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined during 2006–20 were most prevalent in the central part of Izembek Lagoon. More recently, during 2016-20, areas of possible biomass decline were more prevalent in the southern part of the lagoon. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data allows conditions to be compared over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.

Alaska↗
USGS2024

Models no not provide proof: An example of model ambiguity and application of isotopic data in a mine pit lake

Geochemical and hydrologic models of pit lakes are commonly used in environmental regulatory decisions to predict future water quality and hydrologic conditions and to understand existing pit lakes. Models may be used to quantify sulfide oxidation, predict thermal/chemical stratification and mixing, and better understand connections between pit lakes and aquifers. One concern related to the hydrologic character of pit lakes is if they are terminal (a groundwater sink with no outflow) or flowthrough (both receiving groundwater inflow and discharging to groundwater). This question was pertinent to the Liberty pit lake, a small acidic pit lake formed in a former Cu deposit in south-central Nevada where potentiometric and geochemical data potentially indicate pit-lake outflow. Potential discharge to groundwater from the pit lake was evaluated using a water-balance model, but uncertainty in hydraulic parameters led to ambiguity in the hydrologic character. Stable isotopes of water were then sampled from the pit lake and adjacent groundwater wells, which unambiguously indicated the lack of an evaporative signature in downgradient groundwater because the groundwater did not plot on a hypothetical mixing line between evaporated pit lake water and observed meteoric recharge. This methodology provided a more effective and more data-driven approach for understanding pit-lake hydrology. Although predictive models are required to quantify reasonable bounds on future conditions, many models contain substantial uncertainty and are not well suited in some environments. Datasets that provide more clear lines of evidence could be collected from existing pit lakes whenever possible to inform water-rock interaction, limnological behavior, and connectivity to adjacent groundwater.

Nevada↗
USGS2024

Recent advances in characterizing the crustal stress field and future applications of stress data: Perspectives from North America

The stress field controls patterns of crustal deformation, including which faults are likeliest to cause earthquakes or transmit fluids. Since the 1950s, maps of maximum horizontal stress ( S Hmax ) orientations have advanced dramatically, and the style of faulting (relative principal stress magnitudes) has recently been mapped in some regions as well. This perspectives paper summarizes developments in characterizing stress orientations and (relative) magnitudes, including new seismic and borehole methods, as well as progress in identifying the causes of stress variations. Despite these advances, adding far more spatiotemporal detail would allow geoscientists to address many of today's key challenges regarding natural hazards, energy development, and geodynamics. In particular, it is critically important to characterize stress heterogeneity at multiple scales while also recognizing the coherent variability of the stress field. The second part of the paper considers how more detailed stress datasets could prove essential to addressing some of the grand questions in geoscience, including deciphering the poorly understood feedbacks between crustal dynamics and surface processes, improving earthquake and eruption forecasts, and determining the origins and shared properties of plate boundaries.

Geological Society, London, Special Publications↗
USGS2026

Estimation of parental abundance using hierarchical Bayesian modeling with data augmentation

Pedigree-based estimation methods leverage the fact that each offspring in a cohort is genotypically “marked” by its parents and represent a recent and promising toolset for estimating population dynamics. This includes pedigree accumulation estimators that model the “accumulation” of inferred unique parents within a given cohort to estimate parental abundance. Unlike close-kin mark-recapture approaches, which rely on intercohort comparisons, pedigree accumulation modeling can be completed solely using intracohort samples. This is particularly advantageous for semelparous species, where intercohort pairs are impossible and adult life stages can be difficult to sample without affecting their likelihood of successfully reproducing. Previous work has evaluated a range of estimators for such datasets, concluding that the non-parametric Chao estimator provides the most accurate and precise estimates for feasible levels of sampling effort. We used simulated data to evaluate an alternative estimator based on hierarchical modeling and data augmentation in a Bayesian framework. Results indicate that estimates from the hierarchical Bayesian estimator had comparable accuracy and better precision than both the previously tested Chao1 estimator and the improved iChao formulation across a range of sample sizes and sex ratios. Furthermore, the Bayesian estimator was far more robust to simulated errors in pedigree reconstruction, especially the presence of false negatives. Hierarchical Bayesian pedigree accumulation models can also provide additional insight into underlying reproductive ecology through their use of an explicit observation process, allowing for the incorporation or estimation of species- and population-specific reproductive dynamics. More broadly, the parametric nature of these models offers opportunities to efficiently pool information among datasets as well as to propagate uncertainty within more complex models.

Ecology and Evolution↗
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↗
USGS2024

Improving crop-specific groundwater use estimation in the Mississippi Alluvial Plain: Implications for integrated remote sensing and machine learning approaches in data-scarce regions

Study region The Mississippi Alluvial Plain (MAP) in the United States (US). Study focus Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km 3 /year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately. New hydrological insights for the region We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R 2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.

Journal of Hydrology Regional Studies↗
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↗
USGS2026

Distinguishing natural from mining-related metal sources by including streambank groundwater data in a stream mass loading study

Distinguishing stream metal loading caused by mine features from that caused by natural background sources remains challenging, yet this distinction is essential for making effective remedial decisions at many legacy mine sites. We combine a stream tracer injection and synoptic sampling study with data from shallow near-stream groundwater wells to estimate left-bank versus right-bank metal loading contributions at the 100-m spatial scale. The study was performed in the East Mancos River, a mountain headwater stream in Colorado, USA. The dominant source of elevated stream metal concentrations could be either groundwater infiltration through right-bank Doyle Mine waste piles or natural acid rock drainage from hydrothermally altered bedrock located mainly on the left bank. For the five metals of concern (Cu, Al, Zn, Cd, and Mn), we find that 15 % of the load contributed by diffuse groundwater inputs in the section potentially influenced by Doyle mine waste originates from the right bank. This right-bank potential mine contribution equates to only 3 % of the total watershed instream load for these metals. Furthermore, apparent 3 H/ 3 He groundwater ages in segments contributing most of the right-bank metal loading are sufficiently old (9–12 yr) to suggest that infiltration through the waste piles, located only 140–180 m from the stream, is unlikely. Estimated potential Doyle mine loading contributions can therefore be considered maximum values. Study results thus indicate that Doyle mine waste piles are a minor source of metal loading under low-flow conditions, and streambank groundwater data can provide valuable additional information in stream mass loading studies.

Colorado↗
USGS1983

Use of digital land-cover data from the Landsat satellite in estimating streamflow characteristics in the Cumberland Plateau of Tennessee

Characteristics of Streamflow at ungaged sites in coal-mining areas of the Cumberland Plateau may be estimated with regression equations that relate streamflow characteristics to the physiographic and climatic characteristics of the corresponding drainage basins. An experiment was performed to compare the accuracy of equations using basin characteristics derived from maps and climatological records (control group equations) with the accuracy of equations using basin characteristics derived from digital processing of Landsat spectral data as well as maps and climatological records (experimental group equations). Results of this experiment show that (with the exception of low flows and four of six annual peak logarithms) drainage area can explain more than 90 percent of the variance in all streamflow characteristics in both groups of equations. Seventeen of 39 experimental group equations that have two basin characteristics each are different from the corresponding control group equations. Five of the 17 differing experimental group equations have no counterpart in the control group because of lack of significance in control group basin characteristics, seven are slightly more accurate, and five are not measurably different in accuracy. When the equations in both groups are arranged into six flow categories, there is no substantial difference in accuracy between equations using basin characteristics derived from maps and climatological records (control group) and equations using basin characteristics derived from Landsat tapes as well as maps and climatological records (experimental group) for this particular study area, the Cumberland Plateau of Tennessee.

Tennessee↗
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↗
USGS2024

A global assessment of SAOCOM-1 L-band stripmap data for InSAR characterization of volcanic, tectonic, cryospheric, and anthropogenic deformation

SAOCOM-1 is an L-band (23.5 cm) synthetic aperture radar (SAR) constellation made up of two satellites launched in 2018 and 2020 by Comisión Nacional de Actividades Espaciales (CONAE, Argentina). In this contribution, we present a global summary of interferometric SAR (InSAR) observations of ground deformation with SAOCOM-1 stripmap data for tracking volcanic, tectonic, glacier, and anthropogenic deformation. These examples include: 1) episodes of unrest at volcanoes in the Aleutian Islands, Southern Andes, and Italy, with line-of-sight (LOS) deformation from 4 cm/yr in InSAR time series to ~70 cm in interferograms; 2) dike intrusions in Hawai’i; 3) earthquakes in the Andean fold and thrust belt and the East Anatolian fault; 4) ice flow of the Southern Patagonia icefield; and 5) subsidence due to lithium brine extraction in the Salar de Atacama basin (northern Chile). Comparisons between SAOCOM-1, ALOS-2 SM3, Sentinel-1, and TerraSAR-X/ TanDEM-X/PAZ (TSX/TDX/PAZ) mean velocities from InSAR time series show a 1:1 ± 3% correlation in the LOS velocity, which highlights the high accuracy of SAOCOM-1 data. The minimum deformation that we measured in individual interferograms is 4 ± 0.6 cm. One limitation of SAOCOM-1 is the lack of a global acquisition program, which reduces its global and broader applications. Considering the repeat periods, background observation program, and lack of a controlled orbital tube, the best suited targets for SAOCOM-1 InSAR are two. First, volcanoes that deform with secular rates located in vegetated regions in mid- and high-latitudes, and/or that undergo transient episodes of fast deformation in which C-band coherence is lost quickly. Second, glaciers where coherence can be sustained during the repeat period of eight days.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2025

Summary of selenium in the lower Gunnison River Basin, Colorado—Information and data gaps

The Cretaceous Mancos Shale is a geologic source of selenium in the lower Gunnison River Basin. Natural weathering processes and human activity mobilize selenium from the Mancos Shale and derived materials, and surface water, groundwater, and sediment all affect the transport of selenium from source areas to receiving streams and biota. Selenium accumulates through the aquatic food chain, and its toxic effects can result in invertebrate mortality and mortality, decreased reproduction, and deformities to fish and birds. The Bureau of Reclamation, in cooperation with the State of Colorado and Gunnison River Basin water users, is implementing a Selenium Management Program to reduce selenium concentrations in the lower Gunnison River Basin of Colorado. Goals of the Selenium Management Program are to (1) achieve compliance with the State of Colorado chronic aquatic-life standard for dissolved selenium (4.6 micrograms per liter) in the Gunnison River near Grand Junction, Colorado; (2) sufficiently improve water-quality conditions to assist in the recovery of endangered species in the Gunnison and Colorado Rivers by reducing selenium concentrations; and (3) support continued water uses in the basin. Many previous studies have contributed to the understanding of selenium in the environment; however, monitoring and research data gaps exist in the lower Gunnison River Basin. The purpose of this report is to summarize information regarding selenium in the lower Gunnison River Basin and describe strategies for scientific research and monitoring to potentially improve understanding of selenium sources; processes affecting the mobilization, transport, and fate of selenium; and the effects of selenium-mitigation projects in the lower Gunnison River Basin. Monitoring and research data gaps discussed in this report include geologic mapping and geochemical source characterization, long-term and ongoing monitoring of the surface-water and groundwater networks, developing and refining statistical models, characterizing selenium on suspended sediment, modeling selenium in the food web, evaluating best management practices, and more.

Colorado↗
USGS2026

Groundwater and surface-water interactions in the Waihe‘e-Kahalu‘u watershed, O‘ahu, Hawai‘i—Analysis of historical data and numerical groundwater-model simulations

The Waihe‘e-Kahaluʻu watershed and surrounding areas lie in a dike-impounded groundwater setting of the Ko‘olau Range, O‘ahu, Hawai‘i, where groundwater withdrawal from wells and tunnels have resulted in reductions in streamflow. Resource managers and surface-water users seek information that can be used to balance the needs of competing uses of groundwater and streamflow in the watershed. This study assesses the effects of four groundwater developments in the Waihe‘e-Kahalu‘u watershed—Kahaluu Tunnel, Waihee Tunnel, Kahaluu Well, and Waihee Incline Wells—on Kahalu‘u and Waihe‘e Streams. Analyses of historical streamflow, withdrawal, and rainfall data indicate that base flow (the component of streamflow that is supplied from groundwater discharge) in Kahalu‘u and Waihe‘e Streams decreased in response to withdrawals from wells and tunnels within and outside the watershed. Groundwater-model simulations indicate that shutdown of selected tunnels and wells in the Waihe‘e-Kahaluʻu watershed will result in increases of groundwater discharge, but not all of the increase will occur in streams within the watershed; increases will also occur in streams outside the basin, the ocean, and tunnels other than those that were shut down. The analysis of historical data and model simulations is consistent in showing that the effects of withdrawal changes on streams are not constrained by the topographic boundaries of watersheds. Stream base flows in the Waihe‘e-Kahalu‘u watershed are subject to a complex interaction of multiple withdrawals from wells and tunnels installed at various times within and outside the watershed. The correspondence between withdrawals and base-flow changes is consistent with the conceptual model and understanding of the connection between groundwater and streamflow in the dike-impounded groundwater setting of the Waihe‘e-Kahalu‘u watershed and the Ko‘olau Range.

Hawaii↗
USGS2026

Petrography and mineralogy of selected pre-Middle Jurassic basement rocks beneath the Atlantic and Gulf Coastal Plains in Florida

Florida is covered by flat-lying sedimentary strata of the Atlantic and Gulf Coastal Plains. These strata have accumulated since Middle Jurassic time. The pre-Middle Jurassic, or basement, rocks that underlie the Coastal Plain in Florida are known only from drill cores and cuttings recovered from a relatively small number of boreholes. This data report presents petrographic observations and the results of X-ray diffraction analyses of basement rocks from 18 boreholes across Florida in support of the identification, discrimination, and correlation of units for a subcrop geologic map of pre-Middle Jurassic rocks composing Florida’s sub-Coastal Plain geology.

Florida↗
USGS1999

The mineral economy of Brazil--Economia mineral do Brasil

This study depicts the Brazilian government structure, mineral legislation and investment policy, taxation, foreign investment policies, environmental laws and regulations, and conditions in which the mineral industry operates. The report underlines Brazil's large and diversified mineral endowment. A total of 37 mineral commodities, or groups of closely related commodities, is discussed. An overview of the geologic setting of the major mineral deposits is presented. This report is presented in English and Portuguese in pdf format.

Data Series↗
USGS2024

Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake

The 30 November 2018, magnitude (Mw) 7.1 earthquake in Southcentral Alaska triggered substantial landslides, liquefaction, and ground cracking throughout the region, resulting in widespread geotechnical damage to buildings and infrastructure. Despite a challenging reconnaissance and remote-sensing environment, we constructed a detailed digital inventory of ground failure associated with the event from several sources. Sources included information derived from remotely sensed data, and data compiled from literature, social media postings, and earthquake damage information compiled by local, state, and federal agencies. Each instance of ground failure within the inventory contains information on the location and type of observed ground failure, and the methods and data used to document the occurrence. Where high-quality data, such as LIDAR or satellite imagery, were available and showed the ground-failure instance clearly, the extent is mapped as a polygon or polyline. All other locations are mapped as points. There are a total of 886 ground-failure instances documented within the inventory (400 landslides, 286 liquefaction features, and 200 features unattributed to specific processes). A semi-quantitative confidence scheme is used to describe mapping certainty associated with each ground-failure feature. This inventory represents a relatively moderate ground-failure-triggering event that occurred in a subarctic environment. This data paper describes the content within the inventory, the inventory data collection procedures, and limitations of the data. Events of this type are not often documented in detail; thus, adding the inventory data to the US Geological Survey Open Repository of Earthquake-Triggered Ground-Failure Inventories further diversifies the datasets available to the scientific community to be used to better understand and model earthquake-triggered ground failure.

Alaska↗