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1,661 records · Page 81Linked to original sources
USGS2026

Water use in Louisiana, 2020

The U.S. Geological Survey (USGS), in cooperation with the Louisiana Department of Transportation and Development, collected water-withdrawal and water-use data from a 2020 inventory of water withdrawals in Louisiana. In 2020, approximately 8,700 million gallons per day (Mgal/d) of water was withdrawn from groundwater and surface-water sources in Louisiana, which represented a 0.22-percent decrease from 2015. Total groundwater withdrawals were about 1,900 Mgal/d, an increase of 7.1 percent from 2015, and total surface-water withdrawals were about 6,800 Mgal/d, a decrease of 2.1 percent from 2015 to 2020. Total water withdrawals, in million gallons per day, in 2020 for the various categories of use were as follows: public supply, 720; industry, 2,100; power generation, 4,100; rural domestic, 39; livestock, 7.0; rice irrigation, 930; general irrigation, 250; and aquaculture, 590. From 2015 to 2020, Louisiana’s total withdrawals for public supply increased by 1.4 percent, industry decreased by 2.3 percent, power generation decreased by 4.9 percent, rural domestic decreased by 1.2 percent, livestock increased by 11 percent, rice irrigation increased by 13 percent, general irrigation increased by 12 percent, and aquaculture increased by 20 percent. About 51 percent (approximately 960 Mgal/d) of all groundwater withdrawn was from the Chicot aquifer system and 24 percent (approximately 450 Mgal/d) was withdrawn from the Mississippi River alluvial aquifer. Since 2015, withdrawals from the Chicot aquifer system increased by 13 percent, and withdrawals from the Mississippi River alluvial aquifer increased by 18 percent. About 72 percent (4,900 Mgal/d) of all surface water withdrawn was from the Mississippi River main stem. This value represents a 1.1-percent decrease in withdrawals from 2015 to 2020. All water-withdrawal and water-use data presented in this report should be considered estimates. Because of rounding, totals and percentages presented in the tables, figures, and text in the report may differ slightly from totals or percentages calculated individually.

Louisiana↗
USGS2024

Reconciling bias in moderate magnitude earthquake ground motions predicted by numerical simulations

Recent studies found a significant underprediction in ground motion intensity measures for finite-fault simulations of moderate magnitude events in southern California relative to established ground motion models. This study aims to understand the source(s) of this bias by evaluating ground motion residuals. For this, simulations have been performed for a total of 27 well-recorded earthquakes in southern California. Systematic efforts have been employed to identify the source(s) of bias by ruling out factors that are insignificant. Preliminary findings indicate that the magnitude-area scaling used in the simulations is the likely major cause of the observed bias. Adjustment in the source attributes on event-by-event basis is underway to study if the observed bias can be reconciled.

Conference Paper↗
USGS2026

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2023

As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with Providence Water (formerly the Providence Water Supply Board), collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 16 tributaries were used to calculate loads of chloride and sodium during water year 2023 (October 1, 2022, through September 30, 2023). Water-quality samples were collected by Providence Water at 38 sampling stations on tributaries to the Scituate Reservoir during water year 2023. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2023. Annual mean streamflows for monitoring stations in this study ranged from 0.47 to 34.4 cubic feet per second during water year 2023. At the 16 continuous-record streamgages, tributaries transported about 3,000 metric tons of chloride and 1,900 metric tons of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 19 to 200 metric tons per square mile, and annual sodium yields ranged from 13 to 120 metric tons per square mile. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 65,000 million colony forming units per day for coliform bacteria, 870 million colony forming units per day for Escherichia coli , 200 kilograms per day for chloride, 8.2 grams per day as nitrogen for nitrite, 520 grams per day as nitrogen for nitrate, and 300 grams per day as orthophosphate for phosphate. The medians of the median yields were 25,000 million colony forming units per day per square mile for coliform bacteria, 600 million colony forming units per day per square mile for Escherichia coli , 65 kilograms per day per square mile for chloride, 4.6 grams per day per square mile as nitrogen for nitrite, 180 grams per day per square mile as nitrogen for nitrate, and 180 grams per day per square mile as orthophosphate for phosphate.

Rhode Island↗
USGS2025

Carbonatite-hosted residual REE deposits

Rare earth elements (REEs) occur in magmatic rocks but are especially enriched in carbonatite and alkaline silicates. If these rocks are chemically weathered, then the REEs may become further enriched within the regolith developed from these rocks. Primary magmatic REE minerals, as well as the various carbonate minerals and apatite, provide the REEs which, under pervasive chemical weathering, are incorporated within low-temperature REE minerals forming within the regolith. Many of these minerals, as well as their textures, are characteristic of this mode of formation. Lateritic conditions of weathering are instrumental in producing a thick, weathered, or regolith, profile, and the roles of sulfide oxidation, fluctuating groundwater tables, and downward mass wasting due to carbonate dissolution are identified as the most important controls on REE enrichment in the regolith.

Book chapter↗
USGS2025

The U.S. Geological Survey National Water Quality Network—Groundwater, 2024

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, 8 of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,089 wells in the network. All wells are sampled for physical properties, nutrients, major ions, trace elements, per- and polyfluoroalkyl substances (PFAS), and a subset of wells are sampled for pesticides, volatile organic compounds, radionuclides, and microbiological contaminants.

Contiguous United States↗
USGS2025

Alteration mapping in granitic gneiss using handheld geophysical and geochemical instruments: Implications for iron oxide-apatite and rare earth elements exploration

The Adirondack Mountains of New York, U.S.A. contain iron oxide-apatite (IOA) mineral deposits with variable concentrations of rare earth elements (REE). The IOA mineral deposits are typically hosted in the Lyon Mountain Granite Gneiss and are spatially correlated with extensive Na metasomatism (albitization) of the surrounding country rocks, although some mineral deposits also occur in metagabbro, paragneiss, and anorthosite hosts. The location of albitization zones is key to finding new IOA mineral deposits and better understanding the mineralization processes associated with their genesis. However, the Na alteration zones are generally not visibly identifiable in outcrop or hand specimens because the color and textural changes are subtle and are thus difficult to map. Here, we discuss the results from testing two spectroscopic techniques (handheld, field gamma-ray spectroscopy, and portable X-ray fluorescence (pXRF)) to characterize albitization zones surrounding IOA mineral deposits. The gamma-ray and pXRF spectrometers successfully distinguished the relative intensity of alteration in the Lyon Mountain Granite Gneiss based on the K abundance. The measured K content decreases towards the IOA mineral deposits, and the magnitude and width of the gradient are similar along the strike of each mineral deposit. Elevated Th and U values are present in host rocks adjacent to REE-bearing IOA mineral deposits. The pXRF and gamma-ray spectrometer K values are remarkably consistent with laboratory-based, whole-rock XRF compositional data and, therefore, useful for semi-quantitative analysis. Notably, albitization aureoles are consistent around REE-rich and REE-poor mineral deposits, suggesting that saline fluids are essential for the petrogenesis of IOA mineral deposits but may not be critical to REE mineralization. Ultimately, this study demonstrates the utility of handheld gamma-ray and pXRF spectrometry for identifying otherwise cryptic albitization gradients associated with IOA mineral deposits in granitic gneiss.

New York↗
USGS2026

Only very strong shaking can break a tree

A handful of credible accounts, both recent and historical, describe trees being broken during earthquakes. Apart from landslides and tsunamis, such accounts are uncommon, suggesting that trees break only when ground acceleration is extreme or when trees are especially vulnerable to breakage. Here, I consider the question: what ground acceleration is required to break a living tree? I present simplified first‐principles calculations, considering the properties of common trees, focusing on tall, thin trees that can be approximated as uniform vertical cantilevers. The results suggest that, possibly excepting tall trees with heavy canopies, standing trees can only be broken by shaking approaching or exceeding 1 g , as anticipated by the rarity of documented accounts of snapped trees. I briefly consider several well‐documented instances of tree damage during strong earthquakes, drawing inferences about local ground motions.

The Seismic Record↗
USGS2024

Intense alteration on early Mars revealed by high-aluminum rocks at Jezero Crater

The NASA Perseverance rover discovered light-toned float rocks scattered across the surface of Jezero crater that are particularly rich in alumina ( ~ 35 wt% Al 2 O 3 ) and depleted in other major elements (except silica). These unique float rocks have heterogeneous mineralogy ranging from kaolinite/halloysite-bearing in hydrated samples, to spinel-bearing in dehydrated samples also containing a dehydrated Al-rich phase. Here we describe SuperCam and Mastcam-Z observations of the float rocks, including the first in situ identification of kaolinite or halloysite on another planet, and dehydrated phases including spinel and apparent partially dehydroxylated kaolinite. The presence of spinel in these samples is likely detrital in origin, surviving kaolinitization, pointing to an ultramafic origin. However, the association of low hydration with increased Al 2 O 3 abundances suggests heating-induced dehydration which could have occurred during the lithification or impact excavation of these rocks. Given the orbital context of kaolinite-bearing megabreccia in the Jezero crater rim, we propose an origin for these rocks involving intense aqueous alteration of the parent material, followed by dehydration/lithification potentially through impact processes, and dispersion into Jezero crater through flood or impact-related processes.

Communications Earth & Environment↗
USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗
USGS2025

Young explosive eruptions from the Clear Lake volcanic field

The Clear Lake volcanic field is the northernmost and youngest field in a chain of volcanic fields in and near the California Coast Range mountains. For 2 million years, numerous eruptions have happened around (and through) Clear Lake. The most recent period of activity in the Clear Lake volcanic field probably started around 40,000 years ago and was mainly explosive eruptions concentrated on and near faults in and around the lake. The combination of hot magma and groundwater created explosive releases of hot steam. The craters, called maars, threw out volcanic ash, pumice, and lava fragments, which fell back to the ground and draped the surrounding landscape. The deposits are visible in many places around the southeast end of the lake.

California↗
USGS2025

Slow rupture, long rise times, and multi-fault geometry: The 2020 M6.4 southwestern Puerto Rico mainshock

The M 6.4 mainshock of the southwestern Puerto Rico seismic sequence on 7 January 2020, was one of the most impactful modern earthquakes in the northeastern Caribbean. Due to its offshore location and complex aftershock distribution, its source kinematics remain poorly constrained. This active sequence illuminated a complex set of previously unrecognized structures that indicate multiple causative faults may have slipped during its rupture. Here, we utilize seismic and geodetic observations to enhance model resolution, estimate the finite slip of the mainshock, and test a multi-segment, geologically realistic fault geometry. Our refined model finds a lower rupture velocity and longer rise times than typical for an event of this magnitude. This indicates a slow-evolving rupture process that resembles characteristics of a tsunami earthquake. Although this normal/strike-slip faulting event was not tsunamigenic, these qualities, if pervasive for this region, have important implications for future seismic monitoring and hazards in southwestern Puerto Rico.

Puerto Rico↗
USGS2026

HyFlood: A surrogate-model-based framework for compound coastal flooding

Compound coastal flooding is a major threat to low-lying coastal regions and is expected to intensify under future climate change projections. However, modeling the joint interaction of waves, storm surge, tides, and rainfall remains computationally demanding, limiting the development of fast and reliable forecast tools. Here we present HyFlood, a hybrid statistical-numerical downscaling framework capable of computing and mapping high-resolution compound flood hazards while substantially reducing the computational cost compared with fully process-based hydrodynamic modeling. HyFlood combines statistical sampling and selection algorithms with a cascade of reduced-complexity surrogate models that emulate nearshore wave transformation, surf-zone hydrodynamics, and coastal, fluvial, and pluvial flooding. The surrogate models employ machine-learning and regression algorithms applied to a low-dimensional representation of the flooding outputs, obtained through statistical dimensionality reduction. The framework is demonstrated in southern O'ahu, Hawai'i, a region exposed to elevated sea levels driven by tides, waves, and storm surge along with frequent precipitation-driven flash flooding. Validation of the surrogates against the physics-based model outputs demonstrates that HyFlood accurately reproduces daily maxima of spatially distributed flooding depths. This hybrid approach offers a scalable and efficient tool to better quantify how changes in flooding drivers translate into hazard and impact assessments, and to support compound-flood risk assessments and climate-change adaptation planning.

Hawaii↗
USGS2025

Stratigraphic notes—Volume 2, 2025

This is the second volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 .

Professional Paper↗
USGS2026

Stratigraphic notes—Volume 3, 2026

This is the third volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 .

Professional Paper↗
USGS2024

Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance

The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.

Earthquake Spectra↗
USGS2025

Waning greenhouse gas emissions from U.S. Federal lease coal production by the mid-21st century

This study presents estimates of future years (2024–2051) United States Federal lease coal production and the resulting greenhouse gas (GHG) emissions from the combustion, transport, and mining of that fuel. Results from the coal production estimate indicate a decline in production from Federal leases; with known production of 240 million short tons (mtn) in 2023 and a projected decline to 34.0 mtn by 2051, which represents a reduction to 14.2% of the 2023 value. In parallel with this projection, total GHG emissions are estimated to decrease from 402.2 million metric tons of carbon dioxide equivalent (MMT CO 2 eq.) in 2024 to 55.0 MMT CO 2 eq. in 2051, a decline to 13.7% of 2024 emissions estimates. The reductions in coal production and emissions are mainly the result of planned coal combustion power plant closures, with major projected closures in 2037 and 2048. However, GHG emissions estimates for future years can be uncertain as they rely heavily on coal production estimates from operators' public business plans and other publicly available resources. Forward looking plans of this type are subject to significant changes if economic and political factors deviate from current information. Results suggest that average GHG emissions over the time series breakout to 95% end point combustion, 3.7% transportation combustion emissions, and 1.3% fugitive emissions, although there is uncertainty associated with these figures. Uncertainty stemming from production projections, sector distributions, and emissions factors on the future emissions estimates increases with time, ranging from −28% to +48% within the 2024–2051 timeframe.

Alabama, Colorado, Montana, North Dakota, Utah, Wy↗
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↗
USGS2024

A methodology to estimate CO2 and energy gas storage resources in depleted conventional gas reservoirs

Depleted hydrocarbon reservoirs are subsurface geological structures capable of sequestering vast quantities of carbon dioxide (CO 2 ) as well as storing other energy gases for later usage, such as natural gas, and potentially hydrogen (H 2 ). Here we outline a methodology to quantify multi-gas storage resources in depleted conventional gas reservoirs for usage in assessments by the United States Geological Survey (USGS) at the scale of sedimentary basins. The methodology consists first of quantifying accessible pore volume in a depleted reservoir for natural gas storage using up to three equations. Input data are derived from commonly reported or estimated reservoir parameters and natural gas production volumes, and equations may be combined in linear models to improve pore volume estimates. Storage estimates from these equations are tested and validated for 31 reservoirs in the Michigan Basin Province, USA that were previously converted to underground gas storage facilities and have known (federally reported) natural gas storage capacities. Secondly, natural gas storage capacities can be transformed via fluid substitution calculations to estimate the storage resources for non-native fluids, applied here for, CO 2 , H 2 , and methane-H 2 blends, accounting for molecule-specific deviations from ideal gas behavior at reservoir pressures and temperatures as well as differing storage efficiencies. Importantly, the storage of non-native fluids may not be appropriate in all depleted gas reservoir settings due to potential risks like leakage, in particular in the case of H 2 storage, requiring additional knowledge of caprock sealing capacity. Given this caveat, we demonstrate the fluid substitution method for natural gas reservoirs of the Northern Niagaran Reef and Southern Niagaran Reef USGS plays in the Michigan Basin Province, as these trends of Silurian pinnacle reefs are capped with tight-sealing evaporite facies. The deterministic equations outlined from this methodology can be incorporated into future probabilistic USGS gas storage assessments for CO 2 , H 2 , and natural gas resources in the United States.

Michigan↗