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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↗

USGS2023

Connecting flood-related fluvial erosion and deposition with vulnerable downstream road-stream crossings

Fluvial erosion is increasingly responsible for infrastructure and building damages associated with floods as the intensity of extreme rainfalls hit rural and urban rivers in a variety of climate settings across the United States. Extreme floods in 2016 and 2018 caused widespread culvert blockages and road failures, including extensive damage along steep tributaries and ravines in the Marengo River, Wisconsin, watershed during 2016 and 2018. A study conducted by the U.S. Geological Survey (USGS), Wisconsin Wetlands Association (WWA), Ashland County, and the Northwest Wisconsin Regional Planning Commission (NWRPC) investigated the special concern of fluvial erosion hazards (FEHs) associated with gullying, streamside landslides, and the loss of wetland storage in headwaters. In 2019, a pilot study was begun to map and classify ephemeral and perennial streams and wetlands in terms of their sensitivity to FEHs. This study combined data from field-based rapid geomorphic assessments (RGAs) coupled with a stream network-wide geographic information system (GIS) approach for mapping stream segments, referred to as fluvial process zones (FPZ), sensitive to erosion, deposition, and channel change. The GIS approach used nationally available 10-meter (m) resolution topology and an extended stream network to map FPZs based on Strahler stream order, stream power, channel slope, presence of adjacent steep valley sides and headwater flats, and adjacent landform setting. Bankfull channel widths derived from RGA-based hydraulic geometry curves combined with drainage areas, an estimate of bankfull flow, and channel slope were used to calculate specific stream power for the FPZs. Lastly, the FPZs were characterized by their location within three major landform settings that affect erosion potential. The resulting vulnerability maps provided a screening framework to identify FPZs that are sensitive to incision, gullying and mass wasting along steep headwater ephemeral channels, as well as downstream perennial channels that have the potential for valley-side landslides, coarse sediment deposition, and channel change. Lastly, each FPZ was characterized in terms of hydrologic alteration associated with ditching. The vulnerability mapping products and rankings of sensitivity of FPZs will ultimately be used by Ashland County and their collaborators to prioritize natural flood management projects that mitigate FEHs, restore hydrology, and reconnect channels with adjacent wetlands and floodplains.

Wisconsin↗

USGS2026

Widespread landslide activity in an extreme wet season and implications for regional sediment management, eastern San Francisco Bay area, California

Watershed sediment production is expected to increase in a warmer future with more extreme rain, with cascading effects throughout drainage and sediment-transport networks. This study investigated landscape-scale sediment movement in the eastern San Francisco Bay area, California, USA, during the extreme 2016–2017 wet season that brought major rainfall, landslides, and flooding. Mapping 8,928 landslides across a 1,050-km 2 study area revealed new sediment yield of 510–956 t/km 2 , equivalent to denudation of 193–361 mm/ky. These results correspond closely to long-term denudation rates in the northern and central California Coast Ranges, indicating that mass wasting in very wet years dominates long-term sediment mobilization. However, due to long residence times in drainage networks, the 2017 landslides contributed at most ∼1%–2% of the estimated locally derived fluvial sediment transport to San Francisco Bay. Although the amount of sediment mobilized did not threaten municipal water supplies, small rangeland impoundments in this mixed-use landscape lost storage capacity to new sedimentation. Considering regional sediment supply and demand, even the exceptionally large sediment delivery in an extreme wet year cannot meet the need for sediment to accrete tidal wetlands in the bay. To keep pace with rising sea levels, this abnormally high terrestrial sediment input would need to occur in 50 of the next 75 years, an unlikely occurrence due to the prevalence of recent drought years. Shoreline protection and restoration in the bay would need additional sources of sediment, such as through management of dredged sediment through beneficial-reuse programs.

California↗

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↗

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

Integrating Sr isotopes, microchemistry, and genetics to reconstruct Salmonidae species and life history

Recent approaches to fisheries research emphasize the importance of the coproduction of knowledge in building resilient and culturally mindful fisheries management frameworks. Despite widespread recognition of the need for Indigenous knowledge and historical reference points as baseline data, archaeological data are rarely included in conservation biology research designs. Here we propose a novel multiproxy method to learn from former fisheries stewards by generating archaeological data on past salmonid population parameters. We used a newly developed, high throughput qPCR (HT-qPCR) chip, originally designed for environmental DNA (eDNA), for species identification of archaeological salmonid vertebrae. We combine this with the laser ablation split-stream (LASS) approach to identify ocean-migration versus freshwater residency. We test this multidisciplinary approach using both contemporary and archaeological salmonid samples and new radiocarbon dates from the Tronsdal Site on the Skagit River, Washington State, USA. This is a useful approach for extracting information about Salmonidae species and life history diversity from archaeological remains to reconstruct historic baselines for several population parameters in anadromous species with long periods of freshwater residency. The approach outlined in this paper may be particularly useful for research investigating past fisheries dynamics, offering hundreds to thousands of years of temporal depth for modern fisheries management, harvest policies, restoration ecology, and conservation biology.

Idaho, Oregon, Washington↗

USGS2026

Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California

The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes substantially to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides substantial volumes of agricultural products not just for California but for the United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface-water and groundwater resources in the valley. This situation has resulted in water management challenges in the Salinas Valley that generally relate to the distribution of the water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. Historically, to deal with the distribution issue, water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface-water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface-water supplies are insufficient. The availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand for groundwater and surface-water resources throughout the Salinas Valley has resulted in undesirable effects from unsustainable water use, such as surface-water depletion, groundwater-level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface-water and groundwater resources. To meet water demands and reduce the undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and climate variability. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resources Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley hydrogeologic system called the Salinas Valley System Model. The geologic framework is known as the Salinas Valley Geologic Framework and was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The surface-water model is called the Salinas Valley Watershed Model and simulates the Salinas River watershed. Monthly surface-water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.

California↗

USGS2025

A generalized deep learning model to detect and classify volcano seismicity

Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] ( 10.1029/2024JB029194 ) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network ( VOISS-Net ) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.

Volcanica↗

USGS1976

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

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

Open-File Report↗

USGS2025

Detecting hidden sedimentary geothermal systems in the Upper Colorado River Basin

Geothermal resources exist in sedimentary rock where circulation of water for efficient extraction or storage of heat is possible. Except in rare instances where hot water is expressed at the land surface, sedimentary geothermal resources are hidden, so the identification of these systems is optimally accomplished using predictive subsurface modeling. An integrated approach using detailed paleogeographic interpretations, subsurface geologic mapping, and numerical modeling has produced regional geologic and temperature models for the Upper Colorado River Basin, a large watershed in central North America that contains many sedimentary basins. These models identify areas of hidden sedimentary geothermal resource potential in low temperature (<90°C), moderate temperature (90–150°C), and high temperature (>150°C) fairways across the study area. These models incorporate maps of key horizons in outcrop and the subsurface to create a robust structural framework that can be used to target favorable geology for natural or engineered permeability. This framework is populated with lithologies derived from detailed palaeogeographical maps and over 40,000 bottom hole temperature (BHT) values were used to create a calibrated three-dimensional (3D) temperature model across the region. The resulting maps serve as a regional sedimentary geothermal play fairway screening tool for evaluating different grades of sedimentary geothermal resources and for identifying areas of interest where more detailed, prospect-scale studies can be undertaken.

Arizona, Colorado, New Mexico, Utah, Wyoming↗