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A U.S. Geological Survey program to monitor and assess channel reconfiguration activity is described. A data base available on the world wide web will enable land-management agencies and other interested parties to evaluate the long-term success of various channel reconfiguration projects. A demonstration project on the Lake Fork of the Gunnison River, Colorado, illustrates the program objectives and approach.
Precipitation is one of the dominant drivers of landscape erosion and evolution; however, the effects of typical rainfall compared with less frequent, high-magnitude precipitation events on erosion remain unclear. Volcanic islands are ideal locations to study such phenomena due to their simple geometries, nontectonic construction, and strong spatiotemporal rainfall gradients. However, spatial variation in surface age, created during their construction, often complicates their degradation histories by introducing temporal changes in erosion rates as drainage networks develop. Réunion Island (western Indian Ocean) presents a clear example of this, with an east–west gradient in both surface age and mean annual precipitation, as well as infrequent cyclones that alter the background rainfall pattern. In this study, we analyze the effects of surface age, average rainfall, and rainfall variability on basin development and fluvial erosion across the island. We calculate basin-averaged values of basin morphology, age, precipitation, river discharge, eroded volumes, and erosion rates, and use these to analyze the dominant drivers of landscape evolution through a series of correlation analyses. Our results indicate a temporal dependence on the influence of precipitation, with young surfaces being dominantly eroded by high-rainfall events and older surfaces eroded by mean annual rainfall patterns. Furthermore, we show that drainage development of shield volcanoes follows similar trends to other volcano types, and suggest that surface permeability and groundwater structure are important controls on runoff-driven erosion on shield volcanoes. These results add new components to the question of how precipitation impacts erosion.
This study investigates the influence of soil relative density on strike-slip surface fault rupture manifestations using three-dimensional numerical simulations performed with the discrete element method (DEM). The simulations capture the formation of distinctive fault strands within complex flower structures using tens of millions of grains. The tendency for dense soils to localize shear manifests as multiple localized shear bands within wide zones of deformation in strike-slip fault rupture, whereas diffuse shear deformation develops within narrow zones in loose soils. The spatial extents of soil deformation are consistent between simulations having similar relative densities but with different quantities of grains. However, individual shears are more distinguishable in assemblages of finer grains than in assemblages of coarser grains. The simulations show the progressive development of new shears within the bounds of previously developed shears. Shear activity transitions inward as fault activity diminishes along the outermost shears and continues along newly developed shears until a vertically dipping throughgoing shear structure develops that accommodates most of the fault displacement thereon. The throughgoing fault develops at smaller fault displacements in looser soils because the first shear rupture propagates closer to the vertical direction and does not undergo as much inward translation of shear activity, as is observed in denser soils. In all simulations, ground surface uplift develops between nonintersecting active shears, and ground surface subsidence tends to develop where new shears intersect previous shears. The surface traces in these simulations are shown to be consistent with analog models and case histories of surface fault rupture occurring in different shallow subsurface materials. Although computationally costly, these modeling results are valuable for providing a strong numerical supplement to traditional analog models used to represent the mechanics of strike-slip zones in soil, and they provide quantifiable stresses and large-strain deformations throughout the model domain.
Groundwater resources frequently trend toward unsustainable levels because, absent effective institutions, individual water users generally act independently without considering the impacts on other users. Hydro-economic models (HEMs) of human-natural systems can play a positive role toward successful groundwater management by yielding valuable knowledge and insight. The current study explores how an HEM that captures essential physical and economic characteristics of a system can shed light on the system's processes and dynamics to benefit stakeholders, managers, and also researchers. These propositions are illustrated using the Harney Basin, Oregon, which has seen large groundwater declines in the past 20 years. The HEM shows that: (a) although current groundwater pumping rates will gradually raise costs and reduce well yields, irrigators gain the highest aggregate economic return by continuing current pumping; (b) lowland areas of the basin are hydrologically connected, which limits the efficacy of remedies focused on regulations only in some portions of the basin; (c) community expectations regarding the efficacy of several proposed solutions are overly optimistic; and (d) the study's scenarios identify interventions that would stabilize the groundwater system and prevent additional adverse impacts on residential and livestock wells and groundwater-dependent ecosystems. These interventions would require limiting groundwater pumping by nearly half and reducing annual profits by $7.5–$9.0M. The HEM also demonstrated its value to researchers: its insights shifted attention toward questions about Oregon's existing groundwater institutions and their inability to adaptively manage the transition from abundant groundwater to scarce groundwater in a timely manner.
On Earth and Mars, aeolian transport causes sand grains to become abraded, resulting in mineralogic and textural changes. Understanding how sands evolve, or mature, with transport via experimental studies is important for understanding the origins, geologic history, and cycling of sediments, as well as dust production. Previous experimental works have used a variety of methods to simulate aeolian transport in the laboratory, but practical limitations and similitude concerns have limited such research. Here, we present and validate the Sand AbrasioN Device for Aeolian Research (SANDAR), a modified air mill that uses pressurized air to circulate sand around a small abrasion chamber, simulating the effects of aeolian transport. This device is re-circulating to simulate long-distance transport, and it allows for repeated analyses of well-constrained sediment samples, revealing their evolution over time. It is compatible with the grain sizes (74–500 μm) and grain impact velocities (∼0.6–3.7 m/s) typically expected for natural aeolian environments, and is also adaptable for diverse applications simulating different wind conditions. We show that the SANDAR achieves similitude of kinetic energy with respect to saltating sand on both Earth and Mars. SEM and optical microscope imaging reveal that the SANDAR produces microtextures on the surfaces of sand grains similar to those found with natural aeolian transport, demonstrating that it effectively simulates the mechanical effects of aeolian processes. Thus, the SANDAR is a valid tool for use in experimental research to improve our understanding of sedimentary processes across the Solar System.
We use the Third Uniform California Earthquake Rupture Forecast Epidemic Type Aftershock Sequence model, which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and multi-fault earthquakes. A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was examined as well. We demonstrate that the probability of one-or-more loss exceedances (occurrence exceedance probability) is greater for the Poisson model because it has fewer seismically quiet time windows. The discrepancy between dollar loss estimates with a given exceedance probability is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 h and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window (aggregate exceedance probability) was therefore also examined, for which the Poisson model again implies higher risk at intermediate losses but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our study, in part because application specific details will likely be important, but our results highlight how full time dependence can be reckoned with once authoritative forecast models are made available.
Sequoia sempervirens (coast redwood) tree rings have the potential to annually resolve late-Holocene earthquakes on the northern San Andreas Fault based on direct (e.g., physical damage) and indirect (e.g., co-seismic environmental change) impacts, but scarcity of suitable samples and challenges crossdating this long-lived species have limited progress. More precise dating of the pre-1906 (penultimate) earthquake can improve hazard assessment and understanding of rupture segmentation. We target old trees (maximum >815 yr) along the North Coast section of the fault (increment cores via rope-climbing, 11 living trees; plunge cuts, 23 stumps) and employ complementary disturbance detection methods including radial-growth averaging (tree- and series-level), cataloging anatomical indicators (e.g., traumatic resin ducts, TRD), and dating structural components (e.g., reiterated trunks, leans). Multi-centennial ring-width chronologies at Fort Ross (1569−2023) and Gualala (1397−2023) promote continued study with incomplete crossdating limiting utilization of some series. Growth pulses (reductions, releases) and TRD dispersed across the record reflect dynamic environments that obfuscate detection of earthquake signals. The 1906 earthquake did not leave strong signatures on most trees, and when it did, within-tree response varied from normal presentation to discoloration, TRD, and missing rings. Synchrony of indicators at both locations identified 1678−1680 (6 of 15 trees) and 1698−1700 (8 of 16 trees) as the strongest disturbances among dated rings in the time range of the penultimate earthquake, peaking at 1698 (15.7 % of possible growth and anatomical indicators), but the triggering mechanisms for these events are unknown.
This is the first 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 . This first volume ("Stratigraphic notes—Volume 1, 2022") includes articles that provide guidance for those who wish to submit papers to “Stratigraphic Notes,” as well as information on how to make your manuscripts compliant for geologic names reviews and how to organize your paper’s content to facilitate inclusion of new or revised names in Geolex. This volume also includes some specific guidance on conducting geologic names reviews of geologic and hydrogeologic reports.
Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.
We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.
Submerged marine terraces in Puget Sound, deformed across the Seattle fault zone (SFZ), indicate that only one earthquake as large as M~7.5 has occurred in at least the past 11 kyr. Previous paleoseismic studies document a M~7.5 earthquake between 923–4 CE, which uplifted coastal marine terraces by as much as 8 m. We demonstrate that this earthquake was the only such event since ~11 ka by mapping and quantifying deformation of older marine terraces, now submerged in Puget Sound. The submerged terraces, attributed to a late-glacial sea-level lowstand, record both glacial isostatic rebound and tectonic deformation. Vertical offset of the ~11 ka terraces within the SFZ is comparable to that of the marine terraces uplifted in 923 CE, implying no additional large (M>~7.5) earthquake on the SFZ since ~11 ka. This result implies a longer recurrence interval than current hazard estimates, which assumes recurrence of M>7.1 events every 5 kyr. Our mapping of SFZ deformation since ~11 ka also supports fault segmentation and contiguous block uplift between the Seattle and Tacoma fault zones.
Executive Summary Greater sage-grouse populations ( Centrocercus urophasianus ; hereafter sage-grouse) are threatened by a suite of disturbances and anthropogenic factors that have contributed to a net loss of sagebrush-dominant shrub cover in recent decades. Declines in sage-grouse populations are largely linked to habitat loss across their range. A key component of conservation and land use planning efforts for sage-grouse involves the continued monitoring and modeling of habitat requirements and suitability across its range. The Bureau of Land Management (BLM) is addressing the management of sage-grouse habitats on BLM-authorized public lands throughout the western United States through a land use planning amendment and associated environmental impact statement (86 FR 66331). More than 25 percent of the range-wide distribution of sage-grouse is within Nevada and northeastern California, and information on sage-grouse distribution and habitat requirements is important to guide appropriate management decisions. Therefore, the BLM has identified the need for updated spatially explicit information on sage-grouse habitat in Nevada and northeastern California to guide the land use planning amendment and associated management decisions. To address this need, researchers with the U.S. Geological Survey, in close cooperation with multiple State and Federal resource agency partners, including BLM, Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW), sought to map sage-grouse distribution and produce example habitat designations in these states. Herein, we report results of our primary study objective, which was to map sage-grouse habitat and create example habitat management areas, based on more than a decade of location and survival data collected from marked sage-grouse across the study region coupled with lek count survey data managed by the NDOW and the CDFW. We expanded on previously developed methodology to incorporate information on habitat selection and survival during reproductive life stages and specific seasons with updated sage-grouse location and known fate datasets, while also including brood-rearing areas that are understood to be threatened and important for population persistence. We combined predictive habitat map surfaces for each life stage and season with updated information on current occupancy patterns to classify habitat based on its suitability and probability of occupancy. We carried out additional steps to delineate specific example habitat management areas, specifically (1) incorporated corridors connecting key nesting and brood-rearing habitat, (2) corrected outputs for pre-wildfire habitat conditions within areas burned in the last 16 years, and (3) masked out areas of anthropogenic development. Our methodological example of deriving habitat management areas was intended to help inform decisions by BLM and other land managers regarding conservation and management of sage-grouse. Associated data products in the form of habitat maps provide updated, detailed, and comprehensive information about the status of habitats and can be useful to partner agencies in their efforts to designate and rank habitats for this species of high conservation concern in Nevada and California, with full recognition that on-the-ground field data and local sources of information and expertise should be used in conjunction with inferences from these models.
Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.
We use the age and fragility of 13 precariously balanced rocks (PBRs) in Massachusetts, New Hampshire, and southwestern Maine to evaluate the estimated probabilistic seismic hazard (PSH) from the U.S. Geological Survey’s National Seismic Hazard Model (NSHM), and also develop a map of maximum postglacial earthquake magnitudes in the region. The PBRs are erratic boulders left behind by the retreat of the Laurentide ice sheet between 13 and 18 ka, and published ice retreat maps are used to estimate their fragility ages. The fragilities and ages of the rocks appear to be consistent with the NSHM, in that the estimated earthquake magnitudes and resulting ground motions that would topple them are only expected on timescales longer than their fragility ages. This result, on the North American passive margin, contrasts with PBR studies at active plate boundaries, where the PBR constraints imply large reductions to estimated PSH. It may be that the PBRs are not old enough in the eastern United States to reveal the same PSH modeling issues as those revealed in the plate boundary settings. The study provides constraints on maximum magnitudes of postglacial earthquakes across much of Massachusetts, New Hampshire, and southwestern Maine, with the constraints limited to the ages of the PBRs.
Alluvial soils and fill materials in and near the floodplain of East Fork Poplar Creek in Oak Ridge, Tennessee, are contaminated with various trace metals (primarily mercury), organic compounds, and radionuclides that were lost to the stream as a result of past operations at the Y-12 Plant, a nuclear-processing facility located within the U.S. Department of Energy’s Oak Ridge Reservation. Observation wells were installed in the shallow (above bedrock) aquifer in and near the floodplain of East Fork Poplar Creek and water-quality samples were collected to determine if contaminants found in the soils and fill are also present in the shallow ground water. The shallow aquifer in the East Fork Poplar Creek flood plain consists primarily of alluvial silt and clay with lesser amounts of sand and gravel. Thickness of the shallow aquifer ranges from essentially zero to as much as 20 feet. A silty-clay glei horizon is present between the base of the alluvium and the top of bedrock at most flood-plain locations and, where present, likely impedes downward ground-water movement. Water in the shallow aquifer near East Fork Poplar Creek occurs under water-table conditions. Recharge to the shallow aquifer is principally from precipitation, and discharge is through springs and seeps to East Fork Poplar Creek and its tributaries. During spring, summer; and fall, evapotranspiration also accounts for the removal of water in storage in the shallow aquifer. Water levels in the shallow aquifer fluctuate seasonally in response to variations in recharge and evapotranspiration. Generally, the depth to water in the observation wells ranged from about 1 to 4 feet below land surface in late winter, and from about 2 to 7 feet below land surface in late fall. During extremely dry periods, the water table recedes below the top of bedrock in some flood-plain areas, possibly causing East Fork Poplar Creek to lose water to the shallow aquifer along some reaches. Contaminants found in water samples collected from several of the observation wells in concentrations (total and (or) total-recoverable) which equaled or exceeded drinking-water standards established by the U.S. Environmental Protection Agency are antimony, chromium, lead, mercury, selenium, total phenols, and strontium-90. Total and dissolved uranium concentrations exceeded 1.0 microgram per liter in samples from nearly 70 percent of the wells in the East Fork Poplar Creek flood plain. Organic compounds that were identified in low concentrations in samples from a few wells in the flood plain are: Arochlor 1260, benzo(a)anthracene, benzo(b)fluoranthene, chrysene, 3,3-dichlorobenzidine, di-n-butylphthalate, N-nitrosodiphenylamine, and pyrene. Water from one well in the East Fork Poplar Creek flood plain at a contaminated fill site contained 37and 8 micrograms per liter of trichloroethene and trans-1,2-dichloroethene, respectively. Comparison of the results of total and (or) total-recoverable trace-metal determinations with those from dissolved determinations demonstrates that elevated concentrations of these substances in water collected from several of the wells in the East Fork Poplar Creek flood plain resulted from sorption of trace metals (and possibly organic compounds and radionuclides) by fine sediment suspended in the samples. The occurrence of contaminated sediment in these samples is suspected to be the result of borehole contamination during well installation.
StreamStats is a U.S. Geological Survey (USGS) web application that provides streamflow statistics, such as the 1-percent annual exceedance probability peak flow, the mean flow, and the 7-day, 10-year low flow, to the public through a map-based user interface. These statistics are used in many ways, such as in the design of roads, bridges, and other structures; in delineation of floodplains for land-use zoning and setting of insurance rates; for regulatory purposes, such as the permitting of wastewater discharges; and for hydrologic and climate change studies. StreamStats was first developed for Massachusetts and released in 2001. The application provided users with the ability to obtain streamflow statistics computed from data collected at USGS streamgages and to obtain estimates of streamflow statistics for user-selected ungaged sites. Massachusetts StreamStats used geographic information system software and digital mapping to compute drainage-basin characteristics, which were then used in statistical models to estimate streamflow statistics for the user-selected sites. The statistical models were in the form of equations that were developed through a process known as regression analysis. StreamStats was the first known web application with the ability to do interactive geoprocessing. The utility of Massachusetts StreamStats was instantly apparent, leading the USGS to develop a version of StreamStats that could be implemented nationally. USGS State offices normally were required to develop custom regression equations and prepare local digital mapping data needed for implementing StreamStats for their States. Funding needed to complete this work usually was provided through cooperative agreements between the USGS and State agencies. In 2004, Idaho became the first to be released in the national version of StreamStats. By 2023, 44 States were fully implemented and six were undergoing implementation. StreamStats has undergone many modifications over the years to keep up with changes to the underlying software and to add functionality. Customized functionality and separate linked StreamStats applications were developed for several States. Meeting the high demand for additions and improvements to StreamStats while also adhering to budgetary constraints has, at times, been challenging. The StreamStats development team has identified numerous additional improvements that could be made to provide better performance and more functionality. The lessons learned from the experience of building and operating StreamStats for nearly 25 years could be relevant to others interested in pursuing efforts of a similar scale.
Estimates of low-flow characteristics and flow duration for the period of record at continuous-record streamflow gages are essential in hydrologic studies and water-resources management. This report provides estimates of low flow for 1, 3, 7, 14, 30, 60, and 90 consecutive days for recurrence intervals of 2, 5, 10, and 20 years for continuous-record streamflow gages. These estimates were used in correlation methods to estimate low flow at partial-record streamflow sites for 1, 3, and 7 consecutive days for a recurrence interval of 10 years; and 3 consecutive days for a recurrence interval of 20 years.
Decline in availability of fresh groundwater has expanded interest in brackish groundwater resources; however, the distribution of brackish groundwater is poorly understood. Water resources in sedimentary basins across the United States often overlie oil and gas development. Mapping of groundwater total dissolved solids (TDS) using data from oil well geophysical logs has become an important technique for identifying fresh and brackish groundwater. Existing geophysical log analysis methods use porosity and temperature to relate formation resistivity to TDS. Typically, natural geothermal gradients are used to estimate temperature at the location of collected resistivity. However, in thermally enhanced oil fields, steam is injected into the subsurface to mobilize high viscosity oil, creating variable temperature distributions. Furthermore, TDS derived from resistivity also depends on the fractions of dominant ions. Typically, chloride and bicarbonate fractions must be determined. It is also necessary to model TDS across many geologic units with heterogenous porosity distributions. Collectively, each quantity used to estimate TDS (resistivity, porosity, temperature, bicarbonate fraction) varies in space and time, and available data points are rarely collocated. Here, we present a new method of mapping groundwater TDS that continuously models each quantity together with a joint Gaussian process. This method enables mapping fresh and brackish water with practically available data. We apply this method to the San Ardo Oil Field in Monterey County, California, where steam injection occurs. In some areas of the aquifer system overlying the oil zone, the temperature is ∼75 °C, roughly twice the natural background value. Groundwater TDS is typically <1,500 mg/L in the aquifer and increases with depth to ∼9,000 mg/L in the oil-producing zone. A low-permeability clay layer delineates the fresh and brackish water, likely by inhibiting surface recharge from penetrating the deeper zones, allowing higher-TDS connate water to remain in place. Weaker lateral TDS trends may be controlled by recharge patterns associated with the Salinas River. Our model reveals with high certainty that groundwater has freshened in one localized part of the oil-producing zone and suggests with less certainty that more widespread freshening has also occurred. The lowering of TDS was possibly from decades of low-TDS steam injection and the associated fluid production and disposal operations.