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960 records · Page 54Linked to original sources
USGS2009

Analysis of vertical flow during ambient and pumped conditions in four monitoring wells at the Pantex Plant, Carson County, Texas, July-September 2008

The Pantex Plant is a U.S. Department of Energy/National Nuclear Security Administration (USDOE/NNSA)-owned, contractor-operated facility managed by Babcock & Wilcox Technical Services Pantex, LLC (B&W Pantex) in Carson County, Texas, approximately 17 miles northeast of Amarillo. The U.S. Geological Survey, in cooperation with B&W Pantex through the USDOE/NNSA, made a series of flowmeter measurements and collected other borehole geophysical logs during July–September 2008 to analyze vertical flow in screened intervals of four selected monitoring wells (PTX01–1012, PTX06–1044, PTX06–1056, and PTX06–1068) at the Pantex Plant. Hydraulic properties (transmissivity values) of the section of High Plains (Ogallala) aquifer penetrated by the wells also were computed. Geophysical data were collected under ambient and pumped flow conditions in the four monitoring wells. Unusually large drawdowns occurred at two monitoring wells (PTX06–1044 and PTX06–1056) while the wells were pumped at relatively low rates. A decision was made to redevelop those wells, and logs were run again after redevelopment in the two monitoring wells. Logs collected in monitoring well PTX01–1012 during ambient conditions indicate a dynamic environment that probably was affected by pumping of nearby irrigation or public-supply wells. During pumping, downward vertical flow of 0.2 to 2.1 gallons per minute that occurred during ambient conditions was either reversed or reduced. During pumping, a gradual trend of more positive flowmeter values (upward flow) with distance up the well was observed. Estimated total transmissivity for four production zones identified from Flow–B numerical model results taken together was calculated to be about 3,100 feet squared per day. Logs collected in monitoring well PTX06–1044 during ambient conditions before redevelopment indicate a static environment with no flow. During pumping there was upward vertical flow at rates ranging from 0.1 to about 1.5 gallons per minute. During pumping, a gradual trend of more positive flowmeter values (upward flow) with distance up the well was observed. Estimated total transmissivity before redevelopment for five production zones identified from Flow–B numerical model results, and transmissivity values for each zone, are considered to be in error because of the lack of communication between the well and the aquifer before redevelopment. After redevelopment, logs for well PTX06–1044 during ambient conditions indicate a near-static environment with minimal downward flow. During pumping there was upward vertical flow at rates ranging from 0.5 to about 4.8 gallons per minute. During pumping, a gradual trend of more positive flowmeter values with distance up the well was observed. Estimated total transmissivity after redevelopment for the same five identified production zones taken together was calculated to be about 520 feet squared per day. Logs collected in monitoring well PTX06–1056 during ambient conditions before redevelopment indicate a static environment with no flow. During pumping there was upward vertical flow at rates ranging from 0.3 to about 1.5 gallons per minute. During pumping, a gradual trend of more positive flowmeter values (upward flow) with distance up the well was observed. Estimated total transmissivity before redevelopment for four production zones identified from Flow–B numerical model results taken together was calculated to be about 450 feet squared per day. After redevelopment, logs collected in monitoring well PTX06–1056 during ambient conditions indicate a near-static environment with no flow except for a very small amount of downward flow near the bottom of the well. During pumping there was upward vertical flow at rates ranging from 0.7 to about 2.9 gallons per minute. Estimated total transmissivity after redevelopment for five production zones identified from Flow–B numerical model results taken together was calculated to be about 330 feet squared per day. Logs collected in monitoring well PTX06–1068 during ambient conditions indicate a static environment with no flow. During pumping there was upward vertical flow at rates ranging from 0.4 to 4.8 gallons per minute. During pumping, a gradual trend of more positive flowmeter values (upward flow) with distance up the well was observed. Estimated total transmissivity for four production zones identified from Flow–B numerical model results taken together was calculated to be about 200 feet squared per day.

Open-File Report↗
USGS2024

The National Ocean Biodiversity Strategy

President Biden has been clear that the ocean is central to life on Earth. As he has proclaimed, “the ocean powers millions of jobs; feeds and sustains us; and is a rejuvenating source of inspiration, exploration, and recreation.” The Biden-Harris Administration has worked hard to fulfill the President’s goal to protect and conserve at least 30% of U.S. waters by 2030. The ocean faces increased threats from warming, overfishing, increased acidity, and loss of biodiversity. It is now more important than ever to sustain the many benefits that the ocean, coasts, and Great Lakes provide, including food, a favorable climate, recreation, physical and mental health, and for many, a sense of cultural identity. Ocean life represents an irreplaceable heritage, the foundation of a habitable planet, and a vast trove of resources. Keeping our ocean healthy requires reliable information on the changing status of these living organisms, the drivers of biodiversity change, and options for effectively addressing those drivers. Over 2 million species are estimated to live in the ocean, yet only about 240,000 species have been described by scientists. Most of the ocean’s benefits result from those diverse species interacting with one another and the environment they create. To protect and conserve the ocean, we as a nation need to make better use of existing knowledge and prioritize acquiring new biodiversity knowledge to enable better policy and management decisions. The ability to monitor ocean species and habitats has expanded dramatically over the past decade, with innovations in technology, genomics, taxonomy, big data management and sharing, artificial intelligence, and machine learning. Yet large fractions of the U.S. ocean remain almost unknown. The National Ocean Biodiversity Strategy (strategy) reflects the urgent need to leverage these advances. The goals of this strategy must be guided by the nation’s diverse voices and ways of knowing, in order to maximize effective and equitable stewardship of the ocean’s diverse life and its benefits to people. The strategy is intended as a guiding document for government to advance three overarching goals: ● Goal 1: Drive delivery of ocean biodiversity knowledge at the national scale. Objectives include developing an Implementation Plan for achieving the strategy’s three goals; establishing a coordination mechanism to manage the implementation; and documenting gaps in biodiversity knowledge and the benefits of ocean biodiversity to people and economies. ● Goal 2: Strengthen tools and institutions to deliver ocean biodiversity knowledge. Objectives include establishing a robust information pipeline to support indicators and dynamic maps of ocean biodiversity, from the coasts to the deep sea. This pipeline should include expanded observing systems and comprehensive data management; science and technology solutions to accelerate the availability of biodiversity information; and plans to leverage previous investments to rebuild and expand the nation’s human capital and infrastructure to sustain foundational taxonomy and biodiversity science. ● Goal 3: Protect, conserve, restore, and sustainably use ocean biodiversity. Objectives include expanding the collection, delivery, and use of biodiversity knowledge to inform actions that advance ocean protection, conservation, restoration, and sustainable development. Government should lead in establishing and incentivizing diverse partnerships across scales and sectors to implement those actions and should educate and involve the public to discover and value the nation’s diverse ocean life. Achieving these goals will require commitments across society: new federal and private investments, coordination across sectors to address climate and equity challenges, and engagement of Indigenous Knowledge holders and frontline communities as full partners throughout planning and implementation. The Subcommittee on Ocean Science and Technology (SOST) IWG-Biodiversity will begin developing an Implementation Plan to describe and direct specific actions to implement the strategy. Successful implementation of the strategy will harmonize and expand collection and delivery of timely knowledge on ocean life to all of society. The strategy will also enable evidence-based management and protection of the ocean. Advancing the strategy will build human and institutional capital and partnerships that support both existing mandates and new needs to rebuild and sustain biodiversity, achieve healthy ocean ecosystems, and manage living resources. Implementing the strategy will deliver knowledge for monitoring, modeling, forecasting, and assessments that support food security, public health, and cultural values, and that more effectively protect, conserve, and restore nature.

Report↗
USGS2015

Analysis of storm-tide impacts from Hurricane Sandy in New York

The hybrid cyclone-nor’easter known as Hurricane Sandy affected the mid-Atlantic and northeastern United States during October 28-30, 2012, causing extensive coastal flooding. Prior to storm landfall, the U.S. Geological Survey (USGS) deployed a temporary monitoring network from Virginia to Maine to record the storm tide and coastal flooding generated by Hurricane Sandy. This sensor network augmented USGS and National Oceanic and Atmospheric Administration (NOAA) networks of permanent monitoring sites that also documented storm surge. Continuous data from these networks were supplemented by an extensive post-storm high-water-mark (HWM) flagging and surveying campaign. The sensor deployment and HWM campaign were conducted under a directed mission assignment by the Federal Emergency Management Agency (FEMA). The need for hydrologic interpretation of monitoring data to assist in flood-damage analysis and future flood mitigation prompted the current analysis of Hurricane Sandy by the USGS under this FEMA mission assignment. The analysis of storm-tide impacts focused on three distinct but related aspects of coastal flooding from Hurricane Sandy, including flooding inland along the tidal reach of the Hudson River. These aspects are (1) comparisons of peak storm-tide elevations to those of historical storms and to annual exceedance probabilities, (2) assessments of storm-surge characteristics, and (3) comparisons of maps of inundation extent that were derived from differing amounts of available storm-tide data. Most peak storm-tide elevations from Hurricane Sandy were greater than about 9.5 feet (ft) above North American Vertical Datum of 1988. Peak storm-tide elevations from Hurricane Sandy were compared with data for the intense nor’easter of December 11–13, 1992, and Hurricane Irene (August 27–28, 2011), which weakened to a tropical storm before arriving in New York. Peak storm-tide elevations from Hurricane Sandy were higher than those from the December 1992 nor’easter at 24 of 27 sites; most differences were greater than about 0.7 ft or 9 percent (above the historical storm tide). Peak storm-tide elevations from Hurricane Sandy were higher than those from Tropical Storm Irene at all sites; most differences were greater than about 2.5 ft or 48 percent. Data from permanent and temporary monitoring sites and HWM sites were compared with corresponding FEMA flood elevations for the 10-, 2-, 1-, and 0.2-percent annual exceedance probabilities in New York. Peak storm-tide elevations from Hurricane Sandy had annual exceedance probabilities less than or equal to 1 percent and (or) greater than 0.2 percent at a plurality of sites—184 of 413. Peak storm-tide elevations greater than or equal to the 0.2-percent flood elevation accounted for 81 of 413 sites. Peak storm-tide elevations less than the 10-percent flood elevation accounted for only 10 of 413 sites. Data from selected permanent monitoring sites in the USGS and NOAA networks were used to assess storm-surge magnitude associated with the peak storm tide, and magnitude and timing of the peak storm surge. Most magnitudes of the peak storm surge were greater than about 8.3 ft, and most magnitudes of the storm surge component of the peak storm tide were greater than about 7.8 ft. Timing of peak storm surge arrival with respect to local phase of tide controlled where the most extreme peak storm-tide levels and coastal flooding occurred. This finding has bearing not only for locations impacted by the highest storm tides from Hurricane Sandy, but also for those that had the greatest storm surges yet were spared the worst flooding because of fortuitous timing during this storm. Results of FEMA Hazus Program (HAZUS) flood loss analyses performed for New York counties were compared for extents of storm-tide inundation from Hurricane Sandy mapped (1) pre-storm, (2) on November 11, 2012, and (3) on February 14, 2013. The resulting depictions of estimated total building stock losses document how differing amounts of available USGS data affect the resolution and accuracy of storm-tide inundation extents. Using the most accurate results from the final (February 14, 2013) inundation extent, estimated losses range from $380 million to $5.9 billion for individual New York counties; total estimated aggregate losses are about $23 billion for all New York counties. Quality of the inundation extents used in HAZUS analyses has a substantial effect on final results. These findings can be used to inform future post-storm reconstruction planning and estimation of insurance claims.

New York↗
USGS2019

Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the stochastic empirical loading and dilution model

The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration to simulate stormwater quality. To assess the effects of runoff, SELDM uses a stochastic mass-balance approach to estimate combinations of pre-storm streamflow, stormflow, highway runoff, event mean concentrations (EMCs) and stormwater constituent loads from a site of interest. In addition, SELDM can be used to assess the effects of stormwater Best Management Practices (BMPs), which are designed to mitigate the adverse effects of runoff into a waterbody. Adverse effects of stormwater on receiving waters are one of the greatest unsolved water-quality problems Nationwide. State DOTs, municipalities, Federal facilities, and private property owners who manage impervious surfaces need information about the potential magnitude of their contributions and the potential effectiveness of methods to mitigate the adverse effects of runoff. Because the efficacy of at-site controls are limited, information about the potential effectiveness of alternative strategies is needed. The USGS, in cooperation with the Oregon Department of Transportation (ODOT), conducted a study to research methods in which SELDM can be used to enhance the efficiency of ODOT’s stormwater program, support the development of a stormwater banking program, and meet environmental goals. Results can be used to develop a strategic, systems-level approach to stormwater management by considering entire watersheds instead of individual road crossings. Two watersheds, Bear Creek and Mill Creek, in western Oregon were selected for analysis. Within each watershed, seven road crossings were selected for demonstrating the utility of SELDM in nested basins. Precipitation statistics, pre-storm streamflow, runoff coefficients, and hydrograph recession factors were calculated for each location and used in SELDM to simulate flow, water-quality concentrations, and constituent loads in the upstream basin, from the highway (or developed area), and downstream from the road crossing. Three water-quality constituents were selected for modeling: suspended-sediment concentration (SSC), total phosphorus (TP), and total copper (TCu). Using water-quality transport curves, the relations between streamflow and SSC and between streamflow and TP were simulated. Concentrations of TCu were simulated by configuring a linear relation between SSC and TCu. A generic BMP was simulated using the median treatment statistics for flow reductions, hydrograph extensions, concentration reductions, and minimum irreducible concentrations from nine BMP categories with data from the 2012 International BMP database. Five simulation scenarios were modeled for demonstrative purposes. These simulations were used to evaluate potential effects of different watershed properties, water-quality inputs, and stormwater mitigation measures. Instream EMCs were compared to hypothetical water-quality criteria for suspended sediment, total phosphorus, and total copper to demonstrate the concept of water-quality risk analysis. For all five scenarios, it was assumed that highway runoff concentrations were independent of location or average annual daily traffic. These five scenarios are as follows: • Simulation Scenario 1—Natural Conditions (hereafter Simulation Scenario 1) represents conditions in an undeveloped watershed. This scenario demonstrates that the strategic placement of a hypothetical road crossing within a watershed could be used to avoid exceeding water-quality standards of TP and SSC, but that no location choice results in meeting TCu standards. Implementation of BMP had the most pronounced effects on downstream water-quality constituent EMCs at road crossings with the highest ratio of highway catchment area to upstream drainage area, but the largest effect of BMP treatment on mean annual load is based on highway catchment area alone. • Simulation Scenario 2—Current Conditions (hereafter Simulation Scenario 2) represents current watershed conditions, where all developed area upstream from the road crossing was modeled as a highway and combined with the undeveloped part of the upstream drainage area (scenario 2A) and where the output from scenario 2A is used for the upstream area (developed area and the undeveloped area), and where the road crossing is added as usual (scenario 2B). Scenario 2 results indicate that attaining water-quality standards is more difficult with upstream developed areas. Specific road-crossing sites can be selected to achieve the fewest water-quality exceedances per year, but water-quality targets are not met without BMP implementation, and in some instances are not achievable even with BMP implementation. Results from this scenario also serve to quantify the upper limit of constituent reduction if funding were available to implement BMPs to large areas of development, and to quantify how much area would need BMP implementation to achieve water-quality targets. • Simulation Scenario 3—Alternative Road Layouts (hereafter Simulation Scenario 3) was designed to assess the sensitivity of SELDM to various road layouts. In this scenario, different highway configurations were superimposed at one road crossing. Results indicate that downstream waterquality constituent EMCs did not exhibit much variation, but annual water-quality constituent loads varied considerably. • Simulation Scenario 4—Varying Road Width (hereafter Simulation Scenario 4) was designed to assess the sensitivity of SELDM to road width. Similar to scenario 3, the results indicate little variation in downstream water-quality constituent EMCs, but annual water-quality constituent loads increased in proportion to road width. • Simulation scenario 5—Changes to Impervious Area (hereafter Simulation Scenario 5) was designed to investigate the effects of changing amounts of imperviousness upstream from the road crossing. Results indicate that the downstream water-quality constituent EMCs are highly correlated with the percentage of impervious area upstream.

Oregon↗
USGS2014

Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida

The urbanization of central Florida has progressed substantially in recent decades, and the total population in Lake, Orange, Osceola, Polk, and Seminole Counties more than quadrupled from 1960 to 2010. The Floridan aquifer system is the primary source of water for potable, industrial, and agricultural purposes in central Florida. Despite increases in groundwater withdrawals to meet the demand of population growth, recharge derived by infiltration of rainfall in the well-drained karst terrain of central Florida is the largest component of the long-term water balance of the Floridan aquifer system. To complement existing physics-based groundwater flow models, artificial neural networks and other data-mining techniques were used to simulate historical lake water level, groundwater level, and spring flow at sites throughout the area. Historical data were examined using descriptive statistics, cluster analysis, and other exploratory analysis techniques to assess their suitability for more intensive data-mining analysis. Linear trend analyses of meteorological data collected by the National Oceanic and Atmospheric Administration at 21 sites indicate 67 percent of sites exhibited upward trends in air temperature over at least a 45-year period of record, whereas 76 percent exhibited downward trends in rainfall over at least a 95-year period of record. Likewise, linear trend analyses of hydrologic response data, which have varied periods of record ranging in length from 10 to 79 years, indicate that water levels in lakes (307 sites) were about evenly split between upward and downward trends, whereas water levels in 69 percent of wells (out of 455 sites) and flows in 68 percent of springs (out of 19 sites) exhibited downward trends. Total groundwater use in the study area increased from about 250 million gallons per day (Mgal/d) in 1958 to about 590 Mgal/d in 1980 and remained relatively stable from 1981 to 2008, with a minimum of 559 Mgal/d in 1994 and a maximum of 773 Mgal/d in 2000. The change in groundwater-use trend in the early 1980s and the following period of relatively slight trend is attributable to the concomitant effects of increasing public-supply withdrawals and decreasing use of water by the phosphate industry and agriculture. On the basis of available historical data and exploratory analyses, empirical lake water-level, groundwater-level, and spring-flow models were developed for 22 lakes, 23 wells, and 6 springs. Input time series consisting of various frequencies and frequency-band components of daily rainfall (1942 to 2008) and monthly total groundwater use (1957 to 2008) resulted in hybrid signal-decomposition artificial neural network models. The final models explained much of the variability in observed hydrologic data, with 43 of the 51 sites having coefficients of determination exceeding 0.6, and the models matched the magnitude of the observed data reasonably well, such that models for 32 of the 51 sites had root-mean-square errors less than 10 percent of the measured range of the data. The Central Florida Artificial Neural Network Decision Support System was developed to integrate historical databases and the 102 site-specific artificial neural network models, model controls, and model output into a spreadsheet application with a graphical user interface that allows the user to simulate scenarios of interest. Overall, the data-mining analyses indicate that the Floridan aquifer system in central Florida is a highly conductive, dynamic, open system that is strongly influenced by external forcing. The most important external forcing appears to be rainfall, which explains much of the multiyear cyclic variability and long-term downward trends observed in lake water levels, groundwater levels, and spring flows. For most sites, groundwater use explains less of the observed variability in water levels and flows than rainfall. Relative groundwater-use impacts are greater during droughts, however, and long-term trends in water levels and flows were identified that are consistent with historical groundwater-use patterns. The sensitivity of the hydrologic system to rainfall is expected, owing to the well-drained karst terrain and relatively thin confinement of the Floridan aquifer system in much of central Florida. These characteristics facilitate the relatively rapid transmission of infiltrating water from rainfall to the water table and contribute to downward leakage of water to the Floridan aquifer system. The areally distributed nature of rainfall, as opposed to the site-specific nature of groundwater use, and the generally high transmissivity and low storativity properties of the semiconfined Floridan aquifer system contribute to the prevalence of water-level and flow patterns that mimic rainfall patterns. In general, the data-mining analyses demonstrate that the hydrologic system in central Florida is affected by groundwater use differently during wet periods, when little or no system storage is available (high water levels), compared to dry periods, when there is excess system storage (low water levels). Thus, by driving the overall behavior of the system, rainfall indirectly influences the degree to which groundwater use will effect persistent trends in water levels and flows, with groundwater-use impacts more prevalent during periods of low water levels and spring flows caused by low rainfall and less prevalent during periods of high water levels and spring flows caused by high rainfall. Differences in the magnitudes of rainfall and groundwater use during wet and dry periods also are important determinants of hydrologic response. An important implication of the data-mining analyses is that rainfall variability at subannual to multidecadal timescales must be considered in combination with groundwater use to provide robust system-response predictions that enhance sustainable resource management in an open karst aquifer system. The data-driven approach was limited, however, by the confounding effects of correlation between rainfall and groundwater use, the quality and completeness of the historical databases, and the spatial variations in groundwater use. The data-mining analyses indicate that available historical data when used alone do not contain sufficient information to definitively quantify the related individual effects of rainfall and groundwater use on hydrologic response. The knowledge gained from data-driven modeling and the results from physics-based modeling, when compared and used in combination, can yield a more comprehensive assessment and a more robust understanding of the hydrologic system than either of the approaches used separately.

Florida↗
USGS2005

High-resolution seismic-reflection image of the Chesapeake Bay impact structure, NASA Langley Research Center, Hampton, Virginia

A 1-kilometer-long (0.62-mile-long) seismic reflection and refraction profile collected at the National Aeronautics and Space Administration (NASA) Langley Research Center, Hampton, Va., provides a detailed image of part of the annular trough of the buried, 35-million-year-old Chesapeake Bay impact structure. This profile passes within 5 meters (m; 16.4 feet (ft)) of a 635.1-m-deep (2,083.8-ft-deep), continuously cored and geophysically logged test hole at the Langley Center (the USGS-NASA Langley corehole). High-resolution seismic reflection images (having a common-depth-point spacing of 2.5 m (8.2 ft)) of the upper 1,000 m (3,281 ft) along the seismic profile were generated by using refraction velocities and corehole sonic velocities to convert from time sections to depth sections. Time-distance, unmigrated depth-distance, and migrated depth-distance images show lateral variations in the geologic units observed in the USGS-NASA Langley corehole. A high-amplitude reflection at 630 to 625 m (2,067 to 2,051 ft) depth on the migrated depth image correlates with the top of weathered granite (the Langley Granite) at 626.3 m (2,054.7 ft) in the Langley core. Additional high-amplitude reflections below that depth likely represent a weathering profile developed in the upper part of the granite. Diffractions on the unmigrated images suggest that the granite contains numerous inhomogeneities that may consist of mineral veins and mineralized faults and fractures, as seen in the granite cores. Above the granite, crater unit A (minimally to moderately disturbed sands and clays of the Cretaceous Potomac Formation) is characterized by semicontinuous, horizontal and moderately inclined reflections that are broken by pervasive, subvertical, small-offset faults. Sediments of the lower beds of crater unit A below 558.1 m (1,831.0 ft) in the core have horizontal bedding and are nearly pristine. Above that depth, the upper beds of crater unit A contain thick fluidized sand intervals and fractured clay-silt beds. The contact between the granite and crater unit A is essentially horizontal on the migrated depth profile and shows minor relief produced by a few steeply dipping faults. Above crater unit A, the lower beds of crater unit B are lithologically similar to the upper beds of crater unit A and display similar impact-generated deformation. In the migrated depth image, crater unit A and the lower beds of crater unit B are combined into one unit. A thin zone (0.3 m (1.0 ft) thick) of injected glauconitic sediment at the base of the lower beds (at 442.5 m (1,451.7 ft) depth) is the only occurrence of exotic material in the lower beds of crater unit B in the core. The upper beds of crater unit B (above 427.7 m (1,403.3 ft) depth) are represented by discontinuous, locally weak, isolated, or inclined reflections on the migrated depth image. In the core, the upper beds of crater unit B are divided into megablocks and megablock zones that consist of fragmented sediments of the Potomac Formation. The megablocks are separated by matrix zones that consist of smaller blocks of sediments of the Potomac Formation suspended in a matrix of native disaggregated sediments of the Potomac Formation and injected, exotic disaggregated, glauconitic Upper Cretaceous and lower Tertiary marine sediments. Angular relationships and offsets of reflections across the high-relief contact between the upper beds of crater unit B and the underlying combined crater unit A and the lower beds of crater unit B suggest that the contact is a dip-slip fault locally. Above a contact with crater unit B at a depth of 269.4 m (884.0 ft), the Exmore beds are represented by strong, continuous and discontinuous, overstepping reflections that suggest division of the Exmore into four laterally discontinuous depositional subunits. Two of these subunits are present near the Langley corehole on the seismic images and are recognized in the core (Gohn and others, this volume, chap. C). In the Langley core, the Exmore beds consist of clasts of Cretaceous and Tertiary preimpact sediments and cataclastic, shocked, pre-Mesozoic igneous rocks suspended in a matrix of calcareous, muddy, quartz-glauconite sand and granules that contains shocked quartz. The dipping, truncated, and disrupted reflections within crater units A and B are interpreted to represent a 550-m-wide (1,805-ft-wide), stratabound collapse structure. This structure does not affect the underlying basement granite or the lower beds of crater unit A, nor does it affect the base of the Exmore beds above crater unit B. The collapse structure is not bounded laterally by major normal faults. Instead, structural displace ments appear to be distributed among abundant short, smalloffset faults and intervals of fluidized sediment. Fluidized sands above 558 m (1,831 ft) depth in crater unit A are interpreted as a low-strength zone that accommodated the widespread, latestage, gravitational collapse of the impact structure. The pro posed Langley collapse structure may be analogous to stratabound grabens in the outer zone of the Silverpit crater (North Sea). The Exmore beds are interpreted as impact-generated, ocean-resurge deposits. The upper contact of the Exmore section is a wavy, semicontinuous reflection that may represent large bedforms produced by resurge currents or returning impact-generated tsunamis, or it may represent the unmodified blocky or hummocky top of the final Exmore debris flow. Typically continuous, nearly horizontal reflections characterize the upper Eocene to Pleistocene postimpact section of dominantly marine sediments.

Virginia↗