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1,663 records · Page 71Linked to original sources
USGS2025

Statewide cumulative human health risk assessment of inorganics-contaminated groundwater wells, Montana, USA

Across the United States, rural residents rely on unregulated and generally unmonitored private wells for drinking water, which may pose serious health risks due to unrecognized contaminants. We assessed the nature, degree, and spatial distribution of cumulative health risks from inorganic contaminants in groundwater. Our analysis included nearly 84,000 data points from 6500+ wells, across 51 of Montana's 98 watersheds, using a public groundwater database. We compared a drinking water screening level cumulative risk assessment (CRA) for inorganics based on the U.S. Environmental Protection Agency (EPA) protective health thresholds (Maximum Contaminant Level Goals, Health Advisories [MCLG-HAs]) to a CRA based on EPA public supply enforceable Maximum Contaminant Levels (MCLs). Based on median concentrations of 19 inorganics (antimony, arsenic, barium, beryllium, boron, cadmium, chromium, copper, fluoride, manganese, molybdenum, nickel, nitrate, lead, selenium, strontium, thallium, uranium, zinc), 75% of watersheds had MCLG-HA-based cumulative risk values > 1.0; arsenic and uranium contributed the most risk, followed by strontium, fluoride, manganese and boron. Hence, this screening level (Tier I) CRA indicated widespread potential for unrecognized human health risk to private well users from inorganic contaminants considering both carcinogenic and non-carcinogenic risks. Sensitivity analysis showed that benchmarks applied (MCLG-HAs versus MCLs) exerted the largest control on results. Our findings identify priority regions for Tier 2 risk assessments to elucidate local sources and distributions of geogenic versus anthropomorphic contaminants. Our study is the first statewide assessment of cumulative health risk from groundwater that we are aware of, and results support increased statewide drinking water education and testing to reduce human health risks from contaminated private well water.

Montana↗
USGS2025

Timing of hydrothermal alteration and Au-Sb-W mineralization, Stibnite-Yellow Pine district, Idaho

The Stibnite-Yellow Pine district of central Idaho was mined from the early 1900s until the 1990s, extracting gold, antimony, tungsten, and mercury from veins and disseminated and replacement ores in mountainous terrain along the headwaters of the Salmon River. Mining during the two World Wars supplied critical antimony and tungsten to the war efforts. Recent exploration has delineated mineral resources of over 187 metric tons Au, 274 metric tons Ag, and 93,000 metric tons Sb. Mineralization is hosted in Cretaceous Idaho batholith granitic rocks and a sequence of Neoproterozoic to Paleozoic metasedimentary strata of carbonate and siliciclastic compositions. Historical studies outlined some of the complex paragenesis but debated the absolute age of mineralization. New petrographic and geochronologic work documents a sequence of five hydrothermal events in the Stibnite-Yellow Pine district. Event 1 is related to Cretaceous magmatic and hydrothermal activity and includes events ranging in age from 86 to 75 Ma, including sparse quartz-molybdenite veins dated at 86 Ma. Disseminated gold mineralization of event 2 is associated with sericitic alteration and sulfidation of igneous biotite and replacement of plagioclase by potassium feldspar, largely in granodiorite. Gold is present in zoned arsenian pyrite in both disseminated ores and in crosscutting carbonate-quartz veins containing pyrite and arsenopyrite. The large Yellow Pine deposit, localized at a dilatant bend in the Meadow Creek fault, hosts such disseminated and vein gold. Event 2 is interpreted as the major gold-forming event; 40 Ar/ 39 Ar ages of sericite and potassium feldspar alteration range, respectively, from 70 to 59 and 66 to 56 Ma. The long span is interpreted to reflect the age of gold mineralization and local overprinting by event 3. A narrower range from 66 to 61 Ma is interpreted to date the peak of gold mineralization and alteration. Event 3, tungsten mineralization with scheelite, is texturally later than event 2 gold and localized along the Meadow Creek structure. Event 3 scheelite has been dated by isotope dilution-thermal ionization mass spectrometry (ID-TIMS) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) U-Pb methods at 57 Ma. Event 4, best developed in the West End area, includes gold-silver–bearing quartz-carbonate-pyrite veins and breccias with epithermal textures and potassium feldspar alteration envelopes. Adularia from event 4 yields 40 Ar/ 39 Ar plateau ages of 52 to 51 Ma. Event 5 antimony and mercury mineralization consists of stibnite veins and breccia cements at the Yellow Pine and Hangar Flat deposits as well as cinnabar veins and replacements at the peripheral Fern and Hermes deposits; it is constrained by an LA-ICP-MS U-Pb date on scheelite (ca. 47 Ma) intergrown with stibnite. Minor propylitic and argillic alteration is evident in 47 Ma igneous dikes, which do not contain economic mineralization. The Au-Sb-W ores in the Stibnite-Yellow Pine mining district formed over an extended time period from about 70 to 45 Ma in multiple pulses that were localized along the Meadow Creek fault zone. Each event corresponds to episodes of magmatism and/or hydrothermal activity in the region. Insignificant event 1 skarn and molybdenum mineralization is similar in age to the Thompson Creek porphyry molybdenum deposit in central Idaho. Event 2 gold mineralization occurred during a magmatic gap in central Idaho but was synchronous with magmatism in the Bitterroot lobe further north; event 2 is similar in age to orogenic gold-arsenic mineralization at the Beartrack mine in eastern Idaho. Event 3 scheelite mineralization coincides with tungsten mineralization at the Quartz Creek deposit, late magmatism in the Bitterroot lobe, and rapid exhumation of the Atlanta lobe of the Idaho batholith. Event 4 gold mineralization is coincident with the onset of regional Challis magmatism and extension. Event 5 antimony and mercury mineralization is time-equivalent to epithermal gold mineralization in the nearby Thunder Mountain volcanic field and the peak of Challis magmatism.

Idaho↗
USGS2025

Critical minerals in orogenic (gold) and Coeur d’Alene-type mineral systems of the United States

Orogenic and Coeur d’Alene-type mineral systems are produced by metamorphic devolatilization of thick volcanic or siliciclastic sedimentary rock sequences and the focused flow of hydrothermal fluids upwards along crustal-scale faults. Most orogenic systems are found along the Cordilleran orogen, stretching from California northwards into Alaska, whereas most Coeur d’Alene-type systems occur in the Proterozoic Belt Basin in Idaho and Montana. Although the deposit types in these systems are exploited for precious and base metals, potential exists for the production of critical minerals necessary for current (2025) societal needs in the United States. Publicly available geochemical data compiled for these mineral systems, coupled with mineralogical characteristics, indicate that several critical minerals could potentially be recovered from unmined resources and processed mine waste: arsenic, antimony, tellurium, cobalt, and tungsten from orogenic gold deposits and zinc, antimony, arsenic, and manganese from Coeur d’Alene-type systems. These critical minerals reside primarily in arsenopyrite (arsenic), scheelite (tungsten), siderite (manganese), sphalerite (zinc), tetrahedrite (antimony and arsenic), stibnite (antimony), and telluride (tellurium) minerals.

continental United States↗
USGS2025

Data gap analysis for estimation of agricultural return flows in the Upper Gunnison River Basin, Colorado

The Gunnison River and many tributaries in the Upper Gunnison River Basin provide water to irrigate agricultural crops. The application of irrigation water can recharge some aquifers locally by water percolating below the root zone and eventually flowing back to the stream or river through the subsurface. Diverting surface water for irrigation reduces streamflow during the irrigation season but can provide temporary storage of water and supplement streamflow after the snowmelt runoff season. Understanding the timing and quantity of agricultural return flows could help resource managers make informed decisions and adapt to potential changes in water management and availability that could affect irrigation practices. In 2024, the U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, began a study to characterize agricultural return flows in the Upper Gunnison River Basin by using endmember mixing analysis and developing a groundwater model. Both approaches require data from multiple sources, but data gaps exist in the East River study reach and other reaches of interest (Ohio Creek, Tomichi Creek, and Cochetopa Creek). The East River Basin, which is the initial focus of the study, has fewer data gaps than the other basins. Data gaps could be addressed by installing additional surface water and groundwater monitoring sites, making regular streamflow measurements on tributaries, and completing tests to characterize local aquifer properties.

Colorado↗
USGS2026

New measurements indicate that natural geologic methane emissions from microseepage in the Michigan Basin are likely negligible

The magnitude of natural geologic methane (CH 4 ) emissions to the atmosphere (including emissions of fossil CH 4 from offshore and onshore gas and oil seeps, diffuse microseepage, mud volcanoes, volcanic vents, and geothermal areas) is highly uncertain. The largest component of geologic emissions is thought to be microseepage, which is the diffuse flux of CH 4 from soils across large areas of productive hydrocarbon basins. The accuracy of existing bottom-up estimates of microseepage is limited by low spatial coverage of published microseepage measurements. We present the first soil—atmosphere CH 4 flux measurements from Michigan Basin, USA. Results from 335 measurements taken during summer and winter seasons across a large portion of the basin suggest microseepage is nonexistent in the sampled region. Even areas with predictive features for microseepage (e.g., underlying mature, organically rich source rocks, proven gas accumulations, faults, and lineaments) yield null or negative fluxes, suggesting that CH 4 emissions from microseepage are negligible throughout our study region. A Monte Carlo method was used to place an upper limit on the regional-mean microseepage flux, in which synthetic patchy microseepage distributions were generated and tested against our observations to assess the impact of possible emission hot spots that were missed by our sampling strategy. Our analysis finds it is very unlikely that regional-mean emissions are as high as assumed in a previous global microseepage study. The observed lack of seepage may be explained by groundwater flow, active methanotrophy, glacial sediments, and bedded salt deposits, which could inhibit vertical gas migration and release to atmosphere.

Michigan↗
USGS2025

Estimating the probability of export restrictions to inform mineral criticality

To assess risks associated with advanced technologies’ supply chain disruptions, governmental agencies and others have developed mineral “criticality” assessments, with criticality described using the economic impact and probability of supply chain disruptions. Previous work developed subjective supply risk indicators to approximate this probability, typically combining several factors such as supply diversity and trading partners’ political stability, where indicator weightings can substantially impact results. This work explicitly quantifies export barrier probability using an ensemble of machine learning classifiers, with probability estimates informed by exogenous variables, including prior barrier implementation and global export dominance. Major differences in high-probability countries and commodities are observed across models, but the ensemble method highlights Indonesia, China, Tanzania, and the United States as particularly high risk. The Supplementary Data File provides export barrier probability estimates for each analyzed country-commodity pair, enabling a direct, quantitative, objective contribution to assessing mineral criticality, enhancing risk identification and prioritization for policymakers.

Resources, Conservation, and Recycling↗
USGS2024

Analysis of factors affecting plume remediation in a sole-source aquifer system, southeastern Nassau County, New York

Several plumes of dissolved, chlorinated solvents, including trichloroethylene, have been identified in a sole-source aquifer near the former Northrop Grumman Bethpage Facility and Naval Weapons Industrial Reserve Plant sites in southeastern Nassau County, New York. Past investigations have documented that the groundwater contamination originated from this industrial area and now extends to the south, in the direction of groundwater flow. The intermixed plumes are commonly referred to as the “Navy Grumman groundwater plume.” Detailed groundwater-flow modeling was needed for the New York State Department of Environmental Conservation (NYSDEC) to evaluate design options necessary for the construction, operation, optimization, maintenance, and monitoring of a groundwater extraction and treatment cleanup plan selected in a December 2019 Amended Record of Decision by the NYSDEC to comprehensively address these plumes. Consequently, the NYSDEC began a cooperative study with the U.S. Geological Survey in 2020 to better understand the local hydrogeologic framework using two independent approaches to characterize aquifer heterogeneity and update an existing regional groundwater-flow model to provide transient boundary conditions for new inset groundwater-flow models of the plume area. We developed these detailed inset models for the two independent aquifer characterizations using history-matching techniques coupled with a novel approach to risk-based management optimization of the remedial design. We also used the updated regional model to assess this optimized groundwater extraction and treatment design for potential saltwater intrusion. The ensembles of parameters resulting from history matching provided a platform with which to evaluate capture by water-supply and remedial wells using particle-tracking techniques. Using the ensemble to select a risk stance, we performed multiobjective optimization to identify various configurations of remedial pumping that are consistent with external constraints and that favor potentially competing objectives. Multiple solutions provide tradeoffs that NYSDEC can consider. In general, pumping redistribution may help to prevent further contamination migration downgradient. These and other study results are intended to support decisions for the remedial design focused on the local area encompassing the full extent of the Navy Grumman groundwater plume.

New York↗
USGS2026

From model to action: Identifying the gaps in coastal marsh models for decision making

Coastal salt marsh modeling projects are designed to answer questions about where salt marshes may migrate, how they can migrate, and how they will be impacted by changing water levels. While this information is vital for climate-resilient marsh conservation, translating these findings into actionable results remains a challenge. The authors examined the actionability of marsh modeling efforts in the United States by analyzing data collected from semi-structured interviews of marsh model users ( n = 24) across two ongoing projects along the U.S. East Coast and the Gulf of America (Gulf of Mexico). By qualitatively analyzing the interview data, the authors found that the tasks of practitioners who use coastal marsh model outputs fall into three major themes: (1) marsh restoration, (2) planning with uncertainty, and (3) conserving habitat for marsh-reliant species. For each of these themes, the authors identify unmet needs, including high spatial resolution information for local planning, accessible descriptions of uncertainty to increase user confidence, and the incorporation of human dimensions data (e.g., human alterations to the landscape such as impoundments and culverts) for a comprehensive understanding of the coastal salt marsh. Marsh modeling projects should strategize how to fulfil these unmet user needs so that marsh modeling outputs can better support decisions related to marsh conservation and restoration.

Gulf of America, United States East Coast↗
USGS2026

Uncertainty quantification of geologic energy storage in depleted gas reservoirs using material balance equations embedded in a hierarchical errors-in-variables model

The storage potential for gas in geologic settings, such as depleted hydrocarbon reservoirs and solution-mined salt caverns, is becoming salient to future energy infrastructure planning. Technologies such as carbon capture, utilization, and storage, carbon dioxide-enhanced oil recovery, and natural gas and hydrogen storage help meet growing energy demands, reduce carbon emissions to meet climate goals, and provide energy security amid geopolitical uncertainties. Therefore, estimates of underground gas storage capacity could be useful for efficiently navigating the energy transitions. Material balance is a fundamental method in reservoir engineering for estimating original gas in place and potential storage capacity at the scale necessary for national assessments of subsurface pore space resources. However, the deterministic method cannot accommodate multiple data sources or quantify uncertainty in predictions. In this study, a method that embeds material balance equations within a hierarchical errors-in-variables model is proposed which allows the estimation of the distributions of reservoir properties needed for assessments. Uncertainties associated with these reservoir properties have traditionally been expert-elicited, whereas the uncertainty estimates from the proposed models are data-driven. Capacity and uncertainty estimates can be used in a probabilistic resource assessment, supplementing information traditionally used by assessors or even replacing this expert elicitation step when data are unavailable. Various regression models are compared in a case study of the Michigan Basin, a large contributor to the United States’ current natural gas storage capacity. In particular, errors-in-variables models help ameliorate regression dilution and can quantify uncertainty in predictions of pressure in addition to storage capacity. Overfitting is addressed by quantifying generalization error and model averaging in simple and stratified cross-validation against reported working gas capacity, representing the varying quality and quantity of available data. Incorporating a statistical framework into existing numerical methods in reservoir engineering can improve the quality of estimation, and in particular, this method brings rigor to uncertainty quantification as part of a larger effort by the U.S. Geological Survey to assess domestic energy gas storage resources in depleted hydrocarbon reservoirs.

Mathematical Geosciences↗
USGS1999

Concentrations and distribution of manmade organic compounds in the Lake Tahoe Basin, Nevada and California, 1997-99

The U.S. Geological Survey, in cooperation with the Tahoe Regional Planning Agency and the Lahontan Regional Water-Quality Control Board, sampled Lake Tahoe, major tributary streams to Lake Tahoe, and several other lakes in the Lake Tahoe Basin for manmade organic compounds during 1997-99. Gasoline components were found in all samples collected from Lake Tahoe during the summer boating season. Methyl tert -butyl ether (MTBE), benzene, toluene, ethylbenzene, and xylenes (BTEX) were the commonly detected compounds in these samples. Most samples from tributary streams and lakes with no motorized boating had no detectable concentrations of gasoline components. Motorized boating activity appears to be directly linked in space and time to the occurrence of these gasoline components. Other sources of gasoline components to Lake Tahoe, such as the atmosphere, surface runoff, and subsurface flow, are minor compared to the input by motorized boating. Water sampled from Lake Tahoe during mid-winter, when motorized boating activity is low, had no MTBE and only one sample had any detectable BTEX compounds. Soluble pesticides rarely were detected in water samples from the Lake Tahoe Basin. The only detectable concentrations of these compounds were in samples from Blackwood and Taylor Creeks collected during spring runoff. Concentrations found in these samples were low, in the 1 to 4 nanograms per liter range. Organochlorine compounds were detected in samples collected from semipermeable membrane devices (SPMD's) collected from Lake Tahoe, tributary streams, and Upper Angora Lake. In Lake Tahoe, SPMD samples collected offshore from urbanized areas contained the largest number and highest concentrations of organochlorine compounds. The most commonly detected organochlorine compounds were cis- and trans-chlordane, p , p' -DDE, and hexachlorobenzene. In tributary streams, SPMD samples collected during spring runoff generally had higher combined concentrations of organochlorine compounds than those collected during baseflow conditions. Upper Angora Lake had the fewest number of organochlorine compounds detected of all lake samples. Dioxins and furans were not detected in SPMD samples from two sites in Lake Tahoe or from two tributary streams. The number of polycyclic aromatic hydrocarbon (PAH) compounds and their combined concentrations generally were higher in samples from Lake Tahoe than those from tributary streams. Areas of high-motorized boating activity at Lake Tahoe had the largest number and highest concentrations of PAH's. PAH compounds were detected in samples from SPMD's in four of six tributary streams during spring runoff, all tributary streams during baseflow conditions, and at all lake sites. The most commonly detected PAH's in tributary streams during spring runoff were phenanthrene, fluoranthene, pyrene, and chrysene, and during baseflow conditions were phenanthrene, 1-methylphenanthrene, diethylnaphthalene, and pyrene. Upper Truckee River, which has an urban area in its drainage basin, had the largest number and highest combined concentration of PAH's of all stream samples. Bottom-sediment from Lake Tahoe had detectable concentrations of p-cresol, a phenol, in all but one sample. A sample collected near Chambers Lodge contained phenol at an estimated concentration of 4 micrograms per kilogram (µg/kg). Bottom-sediment samples from tributary streams had no detectable concentrations of organochlorine or PAH compounds. Several compounds were detected in bottom sediment from Upper Angora Lake at high concentrations. These compounds and their concentrations were p , p' -DDD (10 µg/kg), p , p' -DDE (7.4 µg/kg), 2,6-dimethylnaphthalene (estimated at 190 µg/kg), pentachlorophenol (3,000 µg/kg), and p-cresol (4,400 µg/kg).

California, Nevada↗
USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California↗
USGS2025

Evidence of mineral alteration in a salt marsh subterranean estuary: Implications for carbon and trace element cycling

Subterranean estuaries (STE) in salt marshes are biogeochemically active zones where interactions between terrestrial groundwater and seawater drive complex cycling of carbon and trace elements, influenced by mineral dissolution. These systems, characterized by fine-grained organic-rich peat overlying permeable coastal aquifers, play a crucial role as a blue carbon sink, yet their geochemical dynamics remain poorly understood. We investigated dissolved trace elements, carbon, silica, and radium isotopes in a salt marsh STE (Sage Lot Pond, Waquoit Bay, MA) over seasonal and annual cycles. Our results reveal that groundwater and estuarine water circulation through marsh peat and aquifer sediments leads to enrichments of dissolved organic and inorganic carbon (DOC and DIC), Si, Ba, and Mn, with variable source/sink behavior of Fe and net removal of U. Submarine groundwater discharge dominated Ba fluxes, whereas pore water drainage from marsh peat acted as the main sink for U and source of Si. Fe cycling was variable, with terrestrial Fe largely removed as groundwater passed through the STE, consistent with Fe-sulfide and amorphous phase formation. Radium isotope ratios identified two distinct subsurface flow pathways, influenced by metal-oxide cycling and organic matter breakdown. Si production was decoupled from DIC, suggesting Si originates from mineral alteration, whereas DIC results from both mineral weathering and microbial respiration. Silicate mineral alteration, coupled with marsh pore water drainage, accounts for up to 16% of annual DIC exports (66 g C m −2 y −1 ), highlighting the importance of STEs in coastal carbon and trace element cycling, especially as marshes face environmental change.

Massachusetts↗
USGS2000

Use of a ground-penetrating radar system to detect pre- and post-flood scour at selected bridge sites in New Hampshire, 1996-98

Ground-penetrating radar was used to measure the depth and extent of existing and infilled scour holes and previous scour surfaces at seven bridges in New Hampshire from April 1996 to November 1998. Ground-penetrating-radar survey techniques initially were used by the U.S. Geological Survey to study streambed scour at 30 bridges. Sixteen of the 30 bridges were re-surveyed where floods exceeded a 2-year recurrence interval. A 300-megahertz signal was used in the ground-penetrating radar system that penetrated through depths as great as 20 feet of water and as great as 32 feet of streambed materials. Existing scour-hole dimensions, infilled thickness, previous scour surfaces, and streambed materials were detected using ground-penetrating radar. Depths to riprap materials and pier footings were identified and verified with bridge plans. Post data-collection-processing techniques were applied to assist in the interpretation of the data, and the processed data were displayed and printed as line plots. Processing included distance normalization, migration, and filtering but processing was kept to a minimum and some interference from multiple reflections was left in the record. Of the 16 post-flood bridges, 22 ground-penetrating-radar cross sections at 7 bridges were compared and presented in this report. Existing scour holes were detected during 1996 (pre-flood) data collection in nine cross sections where scour depths ranged from 1 to 3 feet. New scour holes were detected during 1998 (post-flood) data collection in four cross sections where scour depths were as great as 4 feet deep. Infilled scour holes were detected in seven cross sections, where depths of infilling ranged from less than 1 to 4 feet. Depth of infilling by means of steel rod and hammer was difficult to verify in the field because of cobble and boulder streambeds or deep water. Previous scour surfaces in streambed materials were identified in 15 cross sections and the depths to these surfaces ranged from 1 to 10 feet below the streambed. Riprap materials or pier footings were identified in all cross sections. Calculated record depths generally agree with bridge plans. Pier footings were exposed at two bridges and steel pile was exposed at one bridge. Exposures were verified by field observations.

New Hampshire↗
USGS2026

Utilizing hydrophones to detect streambed mobilization in the Wild and Scenic reach of the Rio Chama

This paper describes a study that deployed underwater acoustic sensors (hydrophones) to detect streambed mobilization in the Wild and Scenic reach of the Rio Chama, New Mexico. Fine sediment accumulation in the gravel‑cobble bed affects brown trout spawning habitat, and understanding incipient motion thresholds is essential for planning effective environmental flushing flows released from El Vado Dam. Two hydrophone stations were operated during 2021–2022, capturing audio data during a high‑flow pulse in late 2021. Acoustic processing techniques, including spectral analysis and threshold‑based impact detection, were used to identify sediment‑generated noise associated with coarse sediment transport. Results indicate detectable sediment mobilization during the high‑flow pulse, demonstrating hydrophones’ potential as a passive monitoring tool for environmental flow planning and sediment‑management decision support.

Conference Paper↗
USGS2024

Turbidite correlation for paleoseismology

Marine turbidite paleoseismology relies on the assumption of synchronous triggering of turbidity currents by earthquake shaking to infer rupture extent and recurrence. Such inference commonly depends on age dating and correlation of the physical stratigraphy of deposits carried by turbidity currents (i.e., turbidites) across great distances. Along the Cascadia subduction zone, which lies offshore the Pacific Northwest, USA, turbidite facies in core photographs, X-ray computed tomography images, and magnetic susceptibility (MS) data exhibit differences in character over relatively short distances, which implies that not all deposits can be correlated with confidence. Thus, subjective correlation based on expected similarity over great distances and weak age constraints does not independently support paleoseismic models. We present a new method for correlating turbidites along the Cascadia margin that can yield a more objective and repeatable stratigraphic framework to underpin earthquake recurrence. We use dynamic time warping to correlate MS logs and measure correlation coefficients of core pairs to evaluate correlation strength. We then compare these measures to a distribution of correlation coefficients of randomly generated turbidite sequences and find that only a small number of core pairs can be correlated more confidently than randomly stacked turbidites. This methodology promises a more robust correlation strategy for future stratigraphic studies.

Oregon, Washington↗
USGS2025

Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York

Nitrogen transported along groundwater flow paths in coastal aquifers can contribute substantially to nitrogen loading into surface water receptors, particularly in hydrologic systems dominated by groundwater discharge. Nitrogen entrained in the aquifer is a function of land use and associated nitrogen sources at the time of groundwater recharge, which may differ considerably from present-day sources. Legacy nitrogen can result in substantial discrepancies between observed present-day nitrogen loading to surface water receptors and loading estimated from present-day sources. Additionally, legacy nitrogen can continue to discharge into surface waters after nitrogen mitigation actions have been undertaken. Here, we use a numerical modeling framework to compare three methods of estimating time-varying historical nitrogen loads to four water bodies (receptors) on eastern Long Island, New York. The methods span a range of data requirements and process complexity, from instantaneous receptor loads calculated from steady-state groundwater contributing areas, to transient loads estimated by explicitly simulating legacy groundwater nitrogen transport over a century with large changes in nitrogen sources and hydrologic conditions. The effects of legacy nitrogen on estimated receptor loads varied temporally and spatially within the study area. Depending on antecedent nitrogen inputs and hydrologic conditions, historical annual nitrogen loads estimated from transient simulations accounting for legacy nitrogen can be quite similar (<10% difference) or substantially different (±100%) from those estimated from simpler instantaneous methods. Continued input of present-day nitrogen sources using methods that account for legacy nitrogen results in asymptotic increases in receptor nitrogen loads over time, indicating that simulated present-day receptor nitrogen loads are not in equilibrium with present-day inputs. For these receptors in disequilibrium, models simulating transient groundwater nitrogen transport could be used to account for legacy nitrogen lag times to help resource managers evaluate the potential effectiveness of proposed nitrogen mitigation actions.

EarthArXiv↗
USGS2024

Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings

Accounting for uncertainties in seismic site response is crucial to improving the performance of one-dimensional (1D) ground response analyses (GRAs) at downhole array recording sites. In addition to site effects, uncertainties in 1D-GRAs can also be contributed from the seismic source and/or path. Though often representing not more than one percent of the distance (path) from the source, site conditions are known to have an enormous influence on ground shaking. In this study, we focus on the site shear-wave velocity ( V S ) structure, which is the main ingredient for estimating the variability of site response. As such, V S can manifest aleatory uncertainties related to the effects of small-scale spatial heterogeneities within the near surface, thus V S can substantially modify ground shaking during earthquakes. We apply a novel V S randomization approach to propagate the small-scale heterogeneities of V S to estimate seismic site response within a non-stationary probabilistic framework. The randomization approach generates samples of V S profiles that are used to perform several 1D-GRAs and obtain an averaged site response and related variability. The proposed method is implemented on data recorded at two downhole array sites with different subsurface soil conditions: a soft soil site on Treasure Island (California, United States of America) and a rock outcrop site in Cadarache (South-East France). We show that synthetic surface-to-borehole transfer functions from 1D-GRAs provide an acceptable fit to the empirical transfer functions from low-motion earthquake records and succeed in reproducing most of the site-specific seismic response variability. The remaining mismatch between transfer functions is likely due to insufficient precision on the seismic bedrock and the impedance contrast. The variability in site response is discussed with emphasis on the role of V S small-scale heterogeneities, attenuation, and input motion incidence angle in ground motion variability for the site and soil conditions at both locations.

California↗
USGS2025

Site-specific, extended ShakeMaps for earthquake engineering applications

The U.S. Geological Survey (USGS) routinely produces ShakeMaps of shaking intensity across the globe. Due to practical constraints, the number of response spectral periods was limited to three standard periods (0.3, 1.0, and 3.0 sec). We have recently developed the tools that are necessary to expand this functionality to include 22 periods (matching the current U.S. National Seismic Hazard Model periods) as well as the orientation-independent components (e.g., “RotD50”). We refer to ShakeMap products that include these extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool called the “ShakeMap Sampling Tool” (SST) that gives all the estimated shaking metrics for a specific location (or list of locations). Additionally, we develop a web application where users can input locations of interest and view/download the SST results. We further familiarize users with the concept of “Composite ShakeMaps.” For earthquakes sequences such as a mainshock and larger foreshocks and aftershocks, this provides a map of the maximum value of each shaking metric, which is useful for overall loss estimates, the full extent of ground failure triggering potential, and a better portrayal of the repeated shaking levels at a given point for a series of earthquakes. Such a site-specific shaking history facilitates earthquake forensics at building or infrastructure sites for which damage may be of concern, as described in the Disproportionate Damage Earthquake trigger specified in the IEBC (2018, Section 405.2.2) and in developing ATC-145 guidelines (Guidelines for Post-Earthquake Assessment, Repair, and Retrofit of Buildings). The composite ShakeMap can be combined with the SST for a variety of earthquake-hazard applications, such as systematically inferring triggering shaking estimates at specific sites of geotechnical interest for landsliding, liquefaction, and lateral-spreading hazards.

Kahramanmaraş↗