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USGS2026

Multiple machine-learning estimation of groundwater levels and trends for the regional Mississippi River Valley alluvial aquifer

The Mississippi River Valley alluvial aquifer provides irrigation, public, and domestic water supplies across the south-central United States. Declining groundwater levels require improved characterization of changing conditions. Traditional potentiometric-surface mapping does not use all available water-level data or quantify uncertainty. To address these limitations, we developed a data-driven multiple machine-learning (MML) framework delivered through two open-source R packages. The covMRVAgen1 software assembles covariates to 155,960 monthly groundwater levels from 57,695 wells; the mmlMRVAgen1 software trains Cubist and Random Forest models, blends them, and makes 1-kilometer gridded predictions of monthly potentiometric surfaces for the period January 1980–December 2022. The MML approach provides a methodological foundation for region-scale spatiotemporal groundwater prediction and uncertainty quantification, generating 90-percent prediction limits with appropriate empirical coverage. Model performance is acceptable, with a root-mean-square error of about 4.2 feet, standard deviation of 24.82 feet, and a normalized Nash–Sutcliffe efficiency of 0.973.

Arkansas, Illinois, Louisiana, Mississippi, Missou↗

USGS2026

Effects of a low-lipid diet on the gut microbiome and head kidney transcriptome of juvenile Chinook Salmon

Objective Pacific salmon Oncorhynchus spp. reared in production hatcheries are typically fed high-lipid, energy-dense diets to achieve large size and high body condition prior to release. In contrast, juveniles in natural environments tend to consume low-lipid, high-protein diets, and fish reared for research or conservation purposes are sometimes fed diets that are formulated to mimic natural diets and promote wild-like phenotypes. Understanding how these alternative diets affect fish health beyond growth and body condition could ultimately contribute to improving hatchery fish fitness. Methods In this work, we evaluated changes in the fecal microbiome and gene expression of juvenile Chinook Salmon O. tshawytscha on a standard high-lipid hatchery diet versus a low-lipid diet formulated to mimic the nutrition profile of natural-origin fish. To evaluate the time scale at which diet alters the fecal microbiome, we collected longitudinal samples over a 12-week period and switched the diets of a subset of fish twice during the experiment. We used 16S ribosomal RNA gene amplicon sequencing to characterize fecal microbiome differences between fish on the two diets as well as hatchery-reared fish at a production hatchery, hatchery fish that had been captured after release into a stream, and natural-origin, stream-reared fish of similar ages. Additionally, we conducted RNA sequencing on head kidney samples from laboratory-reared fish to evaluate changes in gene expression in this important immune organ. Results We found that the low-lipid diet and the hatchery diet resulted in microbiomes that differed from the microbiome of natural-origin fish and from each other and that diet-driven changes to the microbiome could occur in under 14 d. The low-lipid diet did not result in a microbiome that resembled the microbiome of naturally produced fish. Instead, the low-lipid diet resulted in a microbiome community that was distinct from those of fish reared on the hatchery diet and fish sampled from the wild. The RNA sequencing results indicated differential enrichment of pathways related to immunity, metabolism, and hormone synthesis between fish that were fed the two experimental diets. Conclusions The results suggest that additional environmental factors influence the microbiome more strongly than diet formulation or that the low-lipid diet has a smaller effect on the microbiome than a natural, invertebrate-based diet. Given that the gut microbiome and systemic immune function contribute significantly to disease resistance, our findings highlight the importance of understanding how diets fed to fish in captivity may affect fish health beyond growth and body condition metrics.

Journal of Aquatic Animal Health↗

USGS2024

Geospatial PDF map of the compilation of GIS data for the mineral industries and related infrastructure of Africa

Introduction In 2021, the U.S. Geological Survey's (USGS) National Minerals Information Center (NMIC) completed the project titled "Compilation of geospatial data for the mineral industries and related infrastructure of Africa." This project aimed to leverage the expertise and capabilities of the NMIC to collect, synthesize, and interpret geospatial data to inform on the extractive resources of the African region and expand the NMIC's understanding on the impact of mineral industry of African nations in the global economy. The African region, which comprises the independent nations that make up the African continent and its associated islands and dependencies, consists of a total of 58 mineral producing countries. The primary objective of this effort was to create a fully attributed Geographic Information System (GIS) portraying existing mining infrastructure, resources, and development capacity across Africa along with the related infrastructure capable of supporting current (for the reference year 2018) and future extractive industry operations in the region. The compiled GIS geodatabase with supporting documentation including comprehensive metadata was published as a USGS data release titled "Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of Africa." This georeferenced portable document format (GeoPDF) map sheet presents a new geographic information product containing a partial representation of the GIS data. This GeoPDF map provides a visual comparison of the distribution of mineral industry and related infrastructure GIS data, which contributes to a deeper understanding of the intersections and complexities of the extractive industries within Africa.

Open-File Report↗

USGS2023

Preliminary geologic map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California

This investigation delineates the geologic framework of an area of 75 square kilometers (km 2 ) located west of the Salton Sea in southern California (fig. 1, on sheet 1). The study area encompasses the south flank of the Santa Rosa Mountains and the eastern part of the Borrego Badlands (sheet 1). In this study area, regionally important stratigraphic and structural elements collectively inform the late Cenozoic geologic evolution of the Anza-Borrego sector of the Salton Trough province. Critical stratigraphic and structural elements in the map area include the following: The well exposed sequence of late Cenozoic, nonmarine sedimentary rocks that filled the Anza-Borrego subbasin (fig. 1) of the Salton Trough; A tectonic boundary that—in the southern Santa Rosa Mountains—separates the sedimentary strata from underlying crystalline rocks of Peninsular Ranges type. This tectonic boundary, named the West Salton Detachment Fault System by Axen and Fletcher (1998), is projected to underlie all late Cenozoic sedimentary strata in the Anza-Borrego subbasin of the Salton Trough; A variety of transpressional, transtensional, and strike-slip structures that have deformed the late Cenozoic sedimentary strata and collectively guided syntectonic and posttectonic depositional events within the Anza-Borrego subbasin of the Salton Trough; and The southeasternmost surface expression of the Clark Fault, a major strand of the dextral San Jacinto Fault Zone. Geologic mapping and analysis for this investigation focused on clarifying geologic relations among these four stratigraphic and structural aspects in the map area.

California↗

USGS1976

An environmental assessment of impacts of coal development on the water resources of the Yampa River basin, Colorado and Wyoming; Phase I work plan

Coal resources of the western United States are being developed at ever-increasing rates, causing concerns of the effects of mining and associated activities on the environment. The Yampa River basin in northwestern Colorado and south-central Wyoming is undergoing economic development of its coal, oil and gas, and uranium resources. The Yampa River basin assessment is a 21-year program of the U.S. Geological Survey. It is designed primarily to assess the availability and quality of the basin's water resources. The basin assessment also will evaluate potential environmental and selected socioeconomic impacts of energy-resource development plans proposed by mining and power companies. This report serves as a project work plan for the basin assessment's first-phase work activities. Economic development in the Yampa River basin will result in higher levels of residuals (noneconomic byproducts) being discharged into the environment. Residuals-management encompasses the technological and economic interrelationships that should be considered in order to comply with Federal and State environmental-control regulations regarding air quality, water quality, and disposal of solid wastes. The basin assessment, the first phase that is described by this report, is designed to provide Federal, State, and local decision-makers with the basic environmental information needed to formulate and to evaluate policies for the development of energy resources. The techniques applied and conclusions reached in the Yampa River basin assessment should aid similar studies of other energy-rich basins in the western United States.

Colorado, Wyoming↗

USGS2024

U.S. Geological Survey Karst Interest Group proceedings, Nashville, Tennessee, October 22-24, 2024

Karst hydrogeologic systems represent challenging and unique conditions to scientists studying groundwater flow and contaminant transport. Karst terrains are characterized by distinct and beautiful landscapes, caverns, and springs, and many of the exceptional karst areas are designated as national or state parks. The range and complexity of landforms and groundwater flow systems associated with karst terrains are enormous, perhaps more than any other aquifer type. The U.S. Geological Survey (USGS) Karst Interest Group (KIG), formed in 2000, is a loosely knit, grassroots organization of USGS and non-USGS scientists and researchers devoted to fostering better communication among scientists working on, or interested in, karst aquifers. The primary mission of the KIG is to encourage and support interdisciplinary collaboration and technology transfer among scientists working in karst areas. To accomplish its mission, the KIG has organized a series of workshops. To date (2024), nine KIG workshops, including the workshop documented in this report, have been held. The abstracts and extended abstracts provide a snapshot in time of past and current karst related studies. The USGS Water Availability and Use Science Program funded the workshop and proceedings. The planning committee for the ninth workshop includes Thomas D. Byl (USGS and Tennessee State University), Allan K. Clark (USGS), Laura M. DeMott (USGS), Eve L. Kuniansky (USGS, Emeritus), Benjamin V. Miller (USGS), and Lawrence E. Spangler (USGS, Emeritus). The workshop proceedings are edited by Eve L. Kuniansky and Lawrence E. Spangler. The field trip guide was produced by Benjamin V. Miller and Brian Ham (Tennessee Department of Environment and Conservation) and included in the proceedings from the KIG’s 2021 virtual workshop to be used on the optional field trip held on Thursday, October 24, 2024.

Open-File Report↗

USGS2024

Methods to evaluate and improve the modeling of rupture directivity in assessment of seismic hazard

In recent years, there have been several advancements related to the modelling of near-source effects of earthquake rupture on strong ground shaking, leading to an improved characterization of ground motions and resulting seismic hazard. Some of these modifications have stemmed from physics-based numerical modelling of the earthquake rupture process, using physics-based dynamic rupture simulations. These contributions have led to a better understanding of how fault rupture characteristics, geometry, and the style of faulting can interact with the hypocenter-dependence on the path from source to site that may ultimately guide the development of seismic directivity models. Moving forward, the application of modern techniques can be used to incorporate these source characteristics and near-fault ground motion behavior that contribute to the azimuthally varying effects that result in rupture directivity. One example is the application of machine learning methods to support more automated integration of new predictor variables in model development and open more evaluation opportunities to access residuals. Here, we utilize several techniques to take advantage of the plethora of synthetic data and its ability to supplement preexisting trends observed in data. We showcase two examples of how models can be either developed, expanded upon, or constrained using artificial neural network model (ANNs). We evaluate the performance of the ANN with existing methods, comparing misfit, potential limitations, and ability to continue to improve upon these methods in the future. One approach uses a set of simulations with corresponding synthetic ground motions from the Southern California Earthquake Center (SCEC) CyberShake study to develop a ground motion model adapted to incorporate seismic directivity information using an ANN. This large database (TBs) enables us to train the model to capture magnitude, period, and distance variations and how these parameters relate to amplification from hypocenters located along finite-faults. In some cases, there is reduced misfit from better representing source features that aren’t included in base ground motion models that neglect hypocenter location (e.g. azimuthal variation, source-to-site terms). Another ANN method uses a shallow-layered neural network model to better fit a hypocenter-independent model. This method adjusts the median and aleatory variability to account for the averaged impact of various hypocenter distributions to fit the underlying directivity adjustment model. This method serves as a template to apply to other directivity models, improving computational efficiency and more readily enabling integration in hazard codes.

California↗

USGS2024

Investigation of land cover within wetland complexes at Dixie Meadows, Churchill County, Nevada, from October 2015 to January 2022

The U.S. Geological Survey investigated land cover at subannual time steps within six wetland areas in Dixie Valley, Churchill County, Nevada, from October 2015 to January 2022. As requested by the U.S. Fish and Wildlife Service, we used aerial photography and satellite remote sensing data to map surface water and other land cover types within the wetland complexes. We identified five land cover classes using the green normalized difference vegetation index (gNDVI) and its inverse relationship to the normalized difference water index (NDWI) within three U.S. Department of Agriculture National Agriculture Imagery Program aerial images (acquired in 2015, 2017, and 2019) and 110 European Space Agency Sentinel-2 satellite images (acquired 2015–2022). The relative wetness of soil conditions within each land cover class is estimated by comparison to previously published observations of relative conductivity measured by 79 field-based sensors within the wetlands from 2019 to 2021. We mapped the areal coverage of the five land cover classes for approximately 385 acres (1,559,000 square meters [m²]) comprising six individual wetland complexes as well as a larger 1,298- acre (5,254,000-m 2 ) area of interest inclusive of the wetland complexes and adjacent landscape. Land cover of open water (Class 5) primarily within ponds at one of the wetland complexes comprised 8,333 m 2 , on average, of the wetland complexes. Land cover of mixed shallow surface water, saturated soil, and vegetation (Class 4) comprised 111,723 m 2 on average of the wetland complexes. Land cover of dense green vegetation canopy cover (Class 3) that often (46 percent of observations) had underlying surface water or saturated soil conditions comprised 592,522 m 2 on average of the wetland complexes. The remaining areas of the wetland complexes not mapped as these three land cover types (Classes 2 and 1) had sparse vegetation or bare soil cover and commonly (greater than or equal to 67 percent of observations) had dry soil conditions. The investigation of land cover detailed in this report could inform future efforts to map land cover more precisely via higher resolution remote sensing or ground-based surveying or could be incorporated with other environmental monitoring data to characterize habitat and hydrology of the wetland complexes at Dixie Meadows.

Nevada↗

USGS2025

REDPy: A Python tool for automated repeating earthquake detection and visualization

Detecting and cataloging seismic events are among the most fundamental tasks in seismology. Many standardized tools for these tasks exist, including the open‐source package repeating earthquake detector in Python (REDPy). REDPy generates an organized catalog of seismic events from continuous waveform data, in which events are automatically separated into groups (“families”) by their waveform similarity through cross‐correlation. REDPy also automatically generates various outputs that allow a user to visualize important trends in the catalog, which may be used in real time or in retrospective analyses to allow rapid identification of interesting features. The code was designed for near‐real‐time volcano monitoring but is applicable across a broad range of use cases in seismology and seismoacoustics. In this article, the utility and performance of REDPy are demonstrated on two highly seismogenic volcanic eruption sequences: the onset of the dome‐building eruption of Mount St. Helens, Washington, from 2004 to 2005, and the entirety of the summit caldera collapse sequence of Kīlauea, Hawai‘i, in 2018. This article is meant to be a companion to the documentation of the code; in addition to detailing the basic required inputs, script functionality, and resulting outputs, the reasonings behind several important design decisions are also discussed.

Seismological Research Letters↗

USGS2024

Developments in African industrial minerals for renewable energy

Introduction Africa is emerging as a leading source for minerals used in the manufacture of batteries for electric vehicles and in other renewable energy applications. New graphite, lithium, and rare-earth mines have or could be opened in African countries from 2017 through 2026. Estimates of production capacities for graphite, lithium, and rare-earth mines for 2023 and beyond are based upon supply-side assumptions, such as announced plans for new capacity construction and bankable feasibility studies, as well as projected trends that could affect current producing facilities in 2023 and planned new facilities projected to come online by 2026. Forward-looking information, including estimates of future production capacities, graphite flake distributions, and timing of the start of operations, are subject to risk factors and uncertainties that could cause actual events or results to differ significantly from expected outcomes. Projects listed in this report are presented as an indication of industry plans and are not a U.S. Geological Survey (USGS) prediction of what will take place. Only projects with planned startup dates are included in this report; ther graphite, lithium, and rare-earth projects in Africa without startup dates were known to be in various stages of development but are not included in this fact sheet.

Fact Sheet↗

USGS1976

Water-quality study of a reach of the Merced River in Yosemite National Park and vicinity, California, April 1973 through September 1974

A 25-mile (40-kilometre) reach of the Merced River was studied to provide the National Park Service with water-quality data prior to the operation of a new sewage-treatment plant. Data were collected periodically at four Merced River and two inflow stations. Discharge varied seasonally with highest flow occurring at the time of spring snowmelt runoff. Lowest flow occurred during late summer, coinciding with high park visitor use and elevated water temperature. Water-quality variables investigated were discharge, temperature, major chemical constituents, selected trace metals, specific conductance, suspended sediment, turbidity, dissolved oxygen, pH, alkalinity, carbon dioxide, total organic carbon, nitrogen, phosphorus, algal growth potential, coliform bacteria, periphyton, and benthic invertebrates. Diel measurements were made at some stations to delineate daily fluctuations in selected water-quality variables. Results indicate that water in the reach of the Merced River studied was of good quality. The river had low concentrations of dissolved solids (8 to 41 milligrams per litre) and low alkalinity values (2 to 24 milligrams per litre of alkalinity as CaCO 3 ). Mean concentrations of nitrogen and phosphorus were highest in the Merced River at Rancheria Flat. Algal growth potential tests showed that phosphorus was limiting algal growth at Happy Isles Bridge, El Capitan Bridge, and South Fork Merced River, whereas nitrogen was limiting growth at Rancheria Flat. Input of excessive nitrogen and phosphorus concentrations in the Merced River during the summer low-flow period, and mixing with warm tributary inflow could cause excessive algal growth and production. The algal types found were diatoms, green algae, and blue-green algae. Biomass/chlorophyll a ratios in the Merced River were low (0.3 to 7.7). Benthic invertebrates consisted chiefly of Diptera, Ephemeroptera, and Plecoptera.

California↗

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

Hyperspectral (VNIR-SWIR) analysis of roll front uranium host rocks and industrial minerals from Karnes and Live Oak Counties, Texas Coastal Plain

VNIR-SWIR (400–2500 nm) reflectance measurements were made on the surfaces of various cores, cuttings and sample splits of sedimentary rocks from the Tertiary Jackson Group, and Catahoula, Oakville and Goliad Formations. These rocks vary in composition and texture from mudstone and claystone to sandstone and are known host rocks for roll front uranium occurrences in Karnes and Live Oak Counties, Texas. Spectral reflectance profiles, 569 in total, were reduced to 125 representative spectral signatures, which were analyzed using the U.S. Geological Survey's (USGS) Material Identification and Characterization Algorithm (MICA). MICA uses an automated continuum-removal procedure together with a least-squares linear regression to determine the fit of observed sample spectral absorption features to those of reference mineral standards in a spectral library. The reference minerals include various clay, mica, carbonate, ferric and ferrous iron minerals and their mixtures. In addition, absorption feature band-depth analysis was done to identify rock surfaces exhibiting absorption features related to uranium and zeolite minerals, which were not included in the command files used to execute MICA. Rocks from each of the four geologic units produced broadly similar spectral signatures as a result of comparable mineral compositions, but there were some notable differences. For example, Ca- and Na-montmorillonite was matched most frequently to the spectral absorption features in 2-μm (∼2000–2500 nm) wavelengths, while goethite occurred often at 1-μm (∼400–1000 nm) wavelengths. The latter is related to limonitic iron-staining in and around oxidized zones of the uranium roll front as described in previous papers. Rocks of the Jackson Group differed from those of the Catahoula, Oakville and Goliad units in that the former exhibited spectral features we interpret as being due to the presence of lignite-bearing mudstone layers. Goliad rocks exhibit spectral features related to dolomite, gypsum, anhydrite, and an unidentified green clay mineral that is possibly glauconite . Jackson Group rocks also exhibit weak but well-resolved absorption features at 964 and 1157 nm related to either or both zeolite minerals clinoptilolite and heulandite. These zeolite minerals and a few spectra exhibiting hydrous silica absorption features are indicative of alteration of volcanic glass in tuffaceous mudstone and claystone layers. A few sample spectra exhibited strong absorption features at around 1135 nm related to the uranium mineral coffinite. Both the 1135 nm coffinite and 1157 nm zeolite absorption features overlap somewhat, potentially making them difficult to distinguish without additional hyperspectral field, laboratory or remote sensing data. The results of this study were compared to mixtures of minerals described for ore, gangue and alteration minerals in deposit models for sandstone-hosted uranium, sedimentary bentonite and sedimentary zeolite. Use of these spectra can help facilitate mapping of both waste materials from the legacy mining of the above commodities, as well as future exploration and resource assessment activities.

Texas↗

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↗

USGS2024

Geospatial PDF map of the compilation of GIS data for the mineral industries of select countries in the Indo-Pacific region

Introduction In 2024, the U.S. Geological Survey's (USGS) National Minerals Information Center (NMIC) completed the project titled "Compilation of geospatial data for the mineral industries of select countries in the Indo-Pacific." This project aimed to leverage the expertise and capabilities of the NMIC to collect, synthesize, and interpret geospatial data to inform on the extractive resources of select countries in the Indo-Pacific region (area of study) and expand the NMIC's understanding on the impact of mineral industry of these countries in the global economy. The 19 countries of interest in the Indo-Pacific study area include Bangladesh, Bhutan, Brunei, Burma, Fiji, Malaysia, Mongolia, Nauru, New Caledonia, New Zealand, Papua New Guinea, Philippines, Singapore, Solomon Islands, South Korea (Republic of Korea), Sri Lanka, Taiwan, Timor-Leste, and Vietnam. The primary objective of this effort was to create a fully attributed Geographic Information System (GIS) portraying existing mining infrastructure, resources, and production capacities across the Indo-Pacific study area as well as highlight mineral production and processing sites under development and potential areas of future extractive industry operations and development in the region. The compiled GIS geodatabase with supporting documentation including comprehensive metadata was published as a USGS data release titled "Compilation of Geospatial Data (GIS) for the Mineral Industries of Select Countries in the Indo-Pacific." This georeferenced portable document format (GeoPDF) map sheet presents a new geographic information product containing a partial representation of the GIS data. This GeoPDF map provides a visual comparison of the distribution of mineral industry GIS data, which contributes to a deeper understanding of the intersections and complexities of the extractive industries within the select countries in the Indo-Pacific region.

Open-File Report↗

USGS1976

Corwin Springs Known Geothermal Resources Area, Park County, Montana

The Corwin Springs Known Geothermal Resources Area (KGRA) is contiguous to Yellowstone National Park along a part of the northern boundary of the park near Gardiner, Park County, Mont. The area contains two known sites of hot-spring activity--LaDuke Spring, 2.8 km southeast of the small resort community of Corwin Springs, and Bear Creek Spring, 2.6 km east of Gardiner. LaDuke Spring issues from brecciated quartzite and has a flow rate of 380 1/min, a surface water temperature of 65°C, a silica-geothermometer temperature of 68.7°C, and a Na-K-Ca geothermometer temperature of 76.8°C. Bear Creek Spring issues from limestone and has a flow rate of 4 1/min, a surface water temperature of 32°C, a silica temperature of 46.7°C, and a Na-K-Ca temperature of 87.2°C. The springs, which are actively depositing travertine, are on or near the trace of the Gardiner fault-a high-angle reverse fault which forms the southwestern boundary of the Beartooth uplift. Features that make the Corwin Springs KGRA potentially significant include: (1) Proximity of the Corwin Springs area to significant Pliocene and Pleistocene volcanism in Yellowstone National Park and related geothermal activity, (2) existence of a large potential geothermal reservoir in the northern extension of the Sepulcher Mountain graben, (3) localization of thermal activity along the Gardiner fault in the Corwin Springs area, (4) occurrence of negative gravity anomaly centered over the northern end of the Sepulcher Mountain graben, (5) existence of negative magnetic anomaly in the Corwin Springs area, (6) location of the area within the Intermountain seismic belt, (7) evidence of recent tectonism in the area, as demonstrated by Pleistocene and Holocene faulting, and (8) observed surface temperatures and estimated geochemical temperatures of the two known hot springs (features which do not indicate high subsurface temperatures).

Montana↗

USGS2025

Rapid emplacement of the Keaiwa Lava Flow of 1823 from the Great Crack in the Southwest Rift Zone of Kilauea volcano

The Keaīwa Lava Flow of 1823 in the Southwest Rift Zone of Kīlauea volcano is unusual for its expansive pāhoehoe sheet flow morphology and lack of constructive vent topography, despite having a similar tholeiitic basalt composition to other lavas erupted from Kīlauea. This lava flow issued from a ∼10-km-long continuous fissure now known as the Great Crack, and has an unusually thin sheet flow morphology with margin thicknesses of ∼15–110 cm (average of 42 cm). Based on field observations of the lava flow at its fissure vent (e.g., drain-back features), we propose that the Great Crack formed, or at least significantly widened, just prior to and syn-eruptively with this 1823 eruption. The absence of pyroclastic cones or spatter ramparts indicates that the eruption consisted of a rapid outpouring of relatively degassed lava as the fissure unzipped. The rapidly moving lava flow overtopped pre-existing tumuli and scoria cones (e.g., Lava Plastered Cones) up to ∼10 m tall. Glass and whole-rock chemistry yield homogeneous compositions for the lavas erupted from the Great Crack, with glass compositions of 6.40 ± 0.10 wt% MgO and whole-rock compositions of 7.39 ± 0.07 wt% MgO. Lava pads erupted from a short western fissure system are richer in mafic minerals (e.g., olivine and clinopyroxene), and show slightly more MgO-rich whole-rock compositions (7.79 ± 0.05 wt%). MgO-in-glass thermometry on juvenile spatter yield eruption temperatures of 1153 ± 13°C that are typical of Kīlauea lavas. Thus, the extensive sheet-like lava flow morphology is not a direct consequence of unusual magmatic or rheological conditions (i.e., low viscosity). Instead, the flow morphology is associated with high effusion rates caused by sudden drainage of uprift magma as it erupted from the Great Crack. Lava flow modeling on a 2-m-resolution digital elevation model indicates that a minimum bulk effusion rate of ∼5800 m 3 /s (∼3500 m 3 /s dense rock equivalent) and a minimum flow velocity of ∼11 m/s are required for the lava flow to overcome the topography of the Lava Plastered Cones. This effusion rate is among the highest inferred for eruptions in Hawaiʻi and around the world. This study highlights a less frequent eruption style at Hawaiian volcanoes characterized by a sudden outpouring of lava from an unusual fissure system. Local eyewitness accounts indicate that the 1823 eruption was preceded by seismicity. Given the complex magmatic-volcanic-tectonic relations across Kīlauea, we speculate that the south flank could have slipped over one or more events that ultimately triggered unzipping of the Great Crack and passive release of briefly stored uprift magma. An eruption similar to 1823 at Kīlauea or Mauna Loa, with an eruptive timeframe that could be as short as an hour, with high effusion rates and rapid flow front velocities, would not easily allow for a timely response.

Hawaii↗

USGS2024

Agricultural return flow dynamics on a reach of the East River, Colorado, as assessed by mass balance

The U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, studied historical streamflow in a reach of the East River, Colorado, to gain a preliminary understanding of return flow dynamics. Return flow is agricultural irrigation water that is not consumed by evapotranspiration and instead reaches streams by surface and subsurface flow paths. The study reach had a contributing area of 50 square miles and contained 5.23 square miles of pastures irrigated with water diverted from the East River and its tributaries. By comparing upstream inflows to downstream outflows, the net water balance of the study reach from 1994 to 2023 was assessed. Two general hydrologic conditions for the study reach were identified. One hydrologic condition was characterized by a net loss or consumption of water, termed here as general deficit. This general deficit condition extended about 16 years, from 1997 to 2012. During general deficit years, there was usually a notable net loss of streamflow from April through July, and a small net gain, possibly related to return flows, occurred in August about 75 days after the minimums for losses. The second hydrologic condition was characterized by a net gain of water, termed here as general surplus. This second condition extended about 10 years, from 2014 to 2023. During general surplus years, two separate transitions from net loss to net gain commonly occurred during June through August. Losses during general surplus years were smaller than losses during general deficit years, the respective gains were larger, and times between losses and gains were about 18 and 22 days. Differences between the two hydrologic conditions could reflect interactions among irrigation water, available capacity to store additional shallow groundwater, and streamflow. However, deciphering the causes for the shifts between the two general hydrologic conditions was beyond the scope of this report.

Colorado↗