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At least 685 records · Page 38Linked to original sources

USGS1999

Publications of the U.S. Geological Survey, 1998

This catalog is a list of (1) books and maps that were published during 1998 and (2) articles by U.S. Geological Survey personnel in non-U.S. Geological Survey journals and books that came to our attention in 1998; it supplements the permanent catalogs "Publications of the Geological Survey, 1879-1961," "Publications of the Geological Survey, 1962-1970," and "Publications of the U.S. Geological Survey, 1971 through 1981."

Publications of the US Geological Survey↗

USGS2000

Publications of the U.S. Geological Survey, 1999

Publications of the US Geological Survey↗

USGS2001

Publications of the U.S. Geological Survey, 2000

This catalog is a list of (1) books and maps that were published during 2000 and (2) articles by U.S. Geological Survey personnel in non-U.S. Geological Survey journals and books that came to our attention in 2000; it supplements the permanent catalogs "Publications of the Geological Survey, 1879-1961," "Publications ofthe Geological Survey, 1962-1970," and "Publications of the U.S. Geological Survey, 1971 through 1981."

Publications of the US Geological Survey↗

USGS2026

Deep learning models for mapping surficial geology in selected physiographic regions of New York

Surficial geologic mapping is required for decisions including infrastructure and water-resource development and management. Deep learning, a type of machine learning that uses training data to self-learn and perform tasks, is explored as a tool to help increase efficiency of the labour- and time-intensive mapping process. Deep learning models were trained, and their potential to aid in mapping surficial geology was explored for two physiographic regions in New York: the high-relief Allegheny Plateau and the low-relief Erie-Ontario Lowlands. Key to the development of deep learning models is the availability of highly detailed surficial geologic maps in each of these regions from which the models can learn. Through exploring different groupings of surficial deposits and their corresponding spatial data, deep learning models were iteratively developed to reproduce published mapping for greater than 79% of the training areas, and with similar accuracy in test areas within the same physiographic region. These models were trained using only two inputs: high-resolution lidar data and previously published surficial geologic maps. This straightforward approach is intended to make the methods and models created easily reproducible using widely accessible datasets. This research describes the strengths and limitations of lidar-derived surficial geologic models and how broadly grouping surficial types, characteristics of different physiographic regions, and testing models in physiographic regions outside of their training areas affect model creation and performance. In addition, the models created could be used as a tool for mapping surficial geology in similar physiographic regions, in addition to establishing a framework for creating similar models elsewhere.

New York↗

USGS2003

Three-dimensional geologic modeling and visualization of the Virttaankangas aquifer, southwestern Finland

A need exists for a reliable and long-term water supply for the 285,000 inhabitants of the Turku area in southwestern Finland . In response to this need, there are plans to replace the present water supply from the surface sources with artificially infiltrated groundwater from a Quaternary esker aquifer called the Virttaankangas aquifer . New sedimentological studies of the Virttaankangas area have revealed the complexities of the esker system and its surrounding glacial, glaciofluvial, and glaciolacustrine geology. This led to the characterization of the hydrogeological units of the aquifer , the result of which has been a three - dimensional (3-D) truly integrated solids model that represents the geometry, interrelationships, and hydrostratigraphy of the study area. The 3-D model was made with Earth Vision geologic modeling software. The 3-D geological model of the Virttaankangas aquifer can be used for planning the infiltration of river water into the aquifer and to understand the geologic and geographic boundaries of the hydrogeologic units hosting the groundwater reserve and the geologic relationships between the units. Another major outcome of this study is a powerful visualization tool that will be provided to municipal and government authorities who must understand the geologic complexities involved with water-resource planning prior to their decision making.

southwest Finland↗

USGS2024

Geologic constraints on the formation and evolution of Saturn’s mid-sized moons

Saturn’s mid-sized icy moons have complex relationships with Saturn’s interior, the rings, and with each other, which can be expressed in their shapes, interiors, and geology. Observations of their physical states can, thus, provide important constraints on the ages and formation mechanism(s) of the moons, which in turn informs our understanding of the formation and evolution of Saturn and its rings. Here, we describe the cratering records of the mid-sized moons and the value and limitations of their use for constraining the histories of the moons. We also discuss observational constraints on the interior structures of the moons and geologically-derived inferences on their thermal budgets through time. Overall, the geologic records of the moons (with the exception of Mimas) include evidence of epochs of high heat flows, short- and long-lived subsurface oceans, extensional tectonics, and considerable cratering. Curiously, Mimas presents no clear evidence of an ocean within its surface geology, but its rotation and orbit indicate a present-day ocean. While the moons need not be primordial to produce the observed levels of interior evolution and geologic activity, there is likely a minimum age associated with their development that has yet to be determined. Uncertainties in the populations impacting the moons makes it challenging to further constrain their formation timeframes using craters, whereas the characteristics of their cores and other geologic inferences of their thermal evolutions may help narrow down their potential histories. Disruptive collisions may have also played an important role in the formation and evolution of Saturn’s mid-sized moons, and even the rings of Saturn, although more sophisticated modeling is needed to determine the collision conditions that produce rings and moons that fit the observational constraints. Overall, the existence and physical characteristics of Saturn’s mid-sized moons provide critical benchmarks for the development of formation theories.

Space Science Reviews↗

USGS2006

The influence of geology and land use on arsenic in stream sediments and ground waters in New England, USA

Population statistics for As concentrations in rocks, sediments and ground water differ by geology and land use features in the New England region, USA. Significant sources of As in the surficial environment include both natural weathering of rocks and anthropogenic sources such as arsenical pesticides that were commonly applied to apple, blueberry and potato crops during the first half of the 20th century in the region. The variation of As in bedrock ground water wells has a strong positive correlation with geologic features at the geologic province, lithology group, and bedrock map unit levels. The variation of As in bedrock ground water wells also has a positive correlation with elevated stream sediment and rock As chemistry. Elevated As concentrations in bedrock wells do not correlate with past agricultural areas that used arsenical pesticides on crops. Stream sediments, which integrate both natural and anthropogenic sources, have a strong positive correlation of As concentrations with rock chemistry, geologic provinces and ground water chemistry, and a weaker positive correlation with past agricultural land use. Although correlation is not sufficient to demonstrate cause-and-effect, the statistics favor rock-based As as the dominant regional source of the element in stream sediments and ground water in New England. The distribution of bedrock geology features at the geologic province, lithology group and map unit level closely correlate with areas of elevated As in ground water, stream sediments, and rocks. ?? 2006 Elsevier Ltd. All rights reserved.

Applied Geochemistry↗

USGS2021

Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study

Financial risk due to geological uncertainty is a major barrier for geothermal development. Production from a geothermal well depends on the unknown location of subsurface geological structures, such as faults that contain hydrothermal fluids. Traditionally, geoscientists collect many different datasets, interpret the datasets manually, and create a single model estimating faults' locations. This method, however, does not provide information about the uncertainty regarding the location of faults and often does not fully respect all observed datasets. Previous researchers investigated the use of stochastic inversion schemes for addressing geological uncertainty, but often at the expense of geologic realism. In this paper, we present algorithms and open-source code to stochastically invert five typical datasets for creating geologically realistic structural models. Using a case study with real data from the Patua Geothermal Field, we show that these inversion algorithms are successful in finding an ensemble of structural models that are geologically realistic and match the observed data sufficiently. Geoscientists can use this ensemble of models to optimize reservoir management decisions given structural uncertainty.

Nevada↗

USGS2010

Global geological mapping of Ganymede

We have compiled a global geological map of Ganymede that represents the most recent understanding of the satellite based on Galileo mission results. This contribution builds on important previous accomplishments in the study of Ganymede utilizing Voyager data and incorporates the many new discoveries that were brought about by examination of Galileo data. We discuss the material properties of geological units defined utilizing a global mosaic of the surface with a nominal resolution of 1 km/pixel assembled by the USGS with the best available Voyager and Galileo regional coverage and high resolution imagery (100–200 m/pixel) of characteristic features and terrain types obtained by the Galileo spacecraft. We also use crater density measurements obtained from our mapping efforts to examine age relationships amongst the various defined units. These efforts have resulted in a more complete understanding of the major geological processes operating on Ganymede, especially the roles of cryovolcanic and tectonic processes in the formation of might materials. They have also clarified the characteristics of the geological units that comprise the satellite’s surface, the stratigraphic relationships of those geological units and structures, and the geological history inferred from those relationships. For instance, the characteristics and stratigraphic relationships of dark lineated material and reticulate material suggest they represent an intermediate stage between dark cratered material and light material units.

Icarus↗

USGS2019

The Value of Data – The Qatar Geologic Mapping Project

The State of Qatar is in a period of rapid development, modernization, and population growth. One of the most important factors influencing the long-term success and sustainability of future development is a comprehensive understanding of the region’s geologic regime, geotechnical conditions, natural resources, and environmental constraints. To obtain this understanding, the Ministry of Municipality and Environment (MME) of the State of Qatar has undertaken the Qatar Geological Mapping Project (QGMP). The project was envisioned with the strategic foresight to compile and utilize existing and legacy subsurface data collected as part of its massive infrastructure and development projects as the foundation for developing modern scientific resources including geologic maps, digital thematic maps, and a 3-dimensional geological model of the Doha metropolitan area. Recently, the MME, in consultation with Gannett Fleming, Inc. (GF) and the United States Geological Survey (USGS) concluded the data collection and analysis phase (Phase I) of the two-phase QGMP. Phase I included: the development of a comprehensive geotechnical relational database populated with data digitized from more than 13,000 subsurface data logs; a detailed data quality analysis and distribution assessment; an extensive gap analysis and needs assessment; and careful design of the geologic mapping and subsurface investigation programs for the next phase of the project.

Conference Paper↗

USGS2006

Geology of Delaware Water Gap National Recreation Area, New Jersey-Pennsylvania

Many of the parks within the National Park System owe their uniqueness to their geologic framework. Their scenery is the result of diverse natural processes acting upon a variety of rocks that were deposited in varied environments in the geologic past. The Delaware Water Gap National Recreation Area (DEWA) contains a rich geologic and cultural history within its 68,714 acre boundary. Following the border between New Jersey and Pennsylvania, the Delaware River has cut a magnificent gorge through Kit-tantinny Mountain, the Delaware Water Gap, to which all other gaps in the Appalachian Mountains have been compared. Proximity to many institutions of learning in this densely populated area of the northeastern United States (Fig. 1 ) makes DEWA an ideal locality to study the geology of this part of the Appalachian Mountains. This one-day field trip comprises two stops within the gap itself and will include discussion on stratigraphy, structure, geomorphology, and glacial geology. The first stop will be at the bottom of the gap in Pennsylvania to look at the magnificent exposures in the cleft on the New Jersey side. This will be followed by a traverse to the top of Mount Tammany along a popular trail, where we will compare the geology across the river in Pennsylvania. Much of the information presented in this guidebook is summarized from Epstein (2001a , 2001b , 2001c ) and Epstein and Lyttle (2001) .

New Jersey, Pennsylvania↗

USGS2014

Subsurface geologic features of the 2011 central Virginia earthquakes revealed by airborne geophysics

Characterizing geologic features associated with major earthquakes provides insights into mechanisms contributing to fault slip and assists evaluation of seismic hazard. We use high-resolution airborne geophysical data combined with ground sample measurements to image subsurface geologic features associated with the 2011 moment magnitude (M w ) 5.8 central Virginia (USA) intraplate earthquake and its aftershocks. Geologic mapping and magnetic data analyses suggest that the earthquake occurred near a complex juncture of geologic contacts. These contacts also intersect a >60-km-long linear gravity gradient. Distal aftershocks occurred in tight, ~1-km-wide clusters near other obliquely oriented contacts that intersect gravity gradients, in contrast to more linearly distributed seismicity observed at other seismic zones. These data and corresponding models suggest that local density contrasts (manifested as gravity gradients) modified the nearby stress regime in a manner favoring failure. However, along those gradients seismic activity is localized near structural complexities, suggesting a significant contribution from variations in associated rock characteristics such as rheological weakness and/or rock permeability, which may be enhanced in those areas. Regional magnetic data show a broader bend in geologic structures within the Central Virginia seismic zone, suggesting that seismic activity may also be enhanced in other nearby areas with locally increased rheological weaknesses and/or rock permeability. In contrast, away from the M w 5.8 epicenter, geophysical lineaments are nearly continuous for tens of kilometers, especially toward the northeast. Continuity of associated geologic structures probably contributed to efficient propagation of seismic energy in that direction, consistent with moderate to high levels of damage from Louisa County to Washington, D.C., and neighboring communities.

Virginia↗

USGS2020

Foreward: Geology Field Trips in and around the U.S. Capital

The first annual meeting of the Geological Society of America (GSA) was held in 1888 in Ithaca, New York (Fairchild, 1932), but official Sections of GSA formed much later. During the spring of 1949, a symposium in Knoxville, Tennessee, on mineral resources of the southeastern United States became the catalyst for the creation of the Southeastern Section of the Geological Society of America (King, 1964), and the first annual meeting of the Southeastern Section was held in 1952 in Roanoke, Virginia (Wilson, 1954). The Northeastern Section formed much later, and its first annual meeting was held in 1966 in Philadelphia, Pennsylvania (Socolow, 1968). At all of these section meetings, field trips have been important venues for geologists and especially students to gather together, examine rocks in the field, and discuss ideas. These field trips have been especially important at combined section meetings because they provide settings for geologists who are experienced in one geographic region to examine and compare the geology of other regions. The first combined meeting of the Southeastern and Northeastern sections occurred in 1976 in Arlington, Virginia. Since then, the Southeastern and Northeastern sections have met together on numerous occasions, including 1982 in Washington, DC; 1991 in Baltimore, Maryland; 2004 in Tysons Corner, Virginia; and 2010 in Baltimore, Maryland. Since the first combined section meeting in 1976, there has been a gradual increase in the role of technology in geology field studies. In fact, during the past several decades there has been an increase in emphasis in our society on the instrumental component of science, the goal of which is operational techniques to do or control things, and a corresponding decrease in emphasis on the natural philosophy component of science, the goal of which is a greater understanding of the natural world (Dear, 2006). The modern education acronym STEM (Science, Technology, Engineering, and Mathematics), for example, is often used as a catch-all term that implies that science and technology are relatively synonymous, and implies that greater technology leads automatically to greater understanding of the natural world. This assumption, however, is not always valid (Dear, 2006), and technology should not be promoted as a substitute for field experiences. Technology can be a tool that leads to greater understanding of the natural world, but not all Science uses technology as a means of providing greater understanding. The benefits of new technologies include: (1) data of greater resolution; and (2) greater efficiency of capturing, storing, and visualizing data. The risks of new technologies include: (1) an overabundance of data, some of which may be of little value; (2) less time available for analysis of data, if geologists become occupied primarily with capturing and storing data; and (3) errors that arise from complacency and the perception that field-checking may not be necessary. In other words, there is a risk that a glut of data and vast amounts of time devoted to the capturing and storing of data may result in a reduced interest and (or) willingness to field-check data. In the spirit of the early GSA section meetings, we feel that there are still enormous advantages to conducting geology field trips in conjunction with traditional meeting presentations and posters. In 2020, with this current combined Southeastern and Northeastern section meeting in Reston, Virginia, we have assembled eight different field trips that cover a wide range of territory in and around the Nation’s capital. These field trip localities include the immediate vicinity of Washington, DC, as well as various locations in nearby areas of Virginia, Maryland, and West Virginia. The physiographic provinces include Mesozoic Rift Basins, the Piedmont, the Blue Ridge, the Valley and Ridge, and the Allegheny Plateau of the Appalachian Basin. The field trip sites exhibit a wide range of igneous, metamorphic, and sedimentary rocks, as well as rocks with a wide range of geologic ages from the Mesoproterozoic to the Holocene. We hope that this guidebook provides new motivation for geologists to examine rocks in the field, to discuss ideas with colleagues in the field, and to avoid becoming complacent. The editors of this volume would like to thank the authors of the different field trip guides, the field trip leaders, and all of the reviewers who made suggestions for improving the field trip manuscripts. The editors would also like to thank Elle Derwent of GSA for her logistical help and guidance regarding the field trips, and April Leo and the staff of the GSA Publications Department for seeing this book through to publication.

Maryland, Virginia, West Virginia↗

USGS2018

Exploring viable geologic interpretations of gravity models using distance-based global sensitivity analysis and kernel methods

We have explored ways to integrate alternative geologic interpretations into the modeling of gravity data. These methods are applied to the Vaca Fault east of Fairfield, California, USA, where the structure across the fault is in question, and the Vaca Fault is used as a case study to demonstrate the method. The Vaca Fault is modeled using gravity data collected along a 10 km line perpendicular to the strike of the fault. Of particular interest is how the gravity data might inform on the dip of the Vaca Fault and thickness of the nonmarine section and whether spatial autocorrelation of density internal to the geologic units significantly influences the resulting gravity anomaly. We approach these questions by creating a suite of structural geologic models, which we then populate with geostatistically generated densities and from which the respective synthetic gravity anomalies are calculated. We perform distance-based generalized sensitivity analysis to identify which model inputs most leverage the calculated gravity anomaly. We then use multidimensional scaling to transform the gravity anomalies into a metric space and estimate the posterior probabilities of each structural geologic model using a Bayesian approach. We find that the gravity anomalies are particularly sensitive to zones of autocorrelated density values generated from geostatistical modeling. The structural geologic models most likely to produce gravity anomalies that match the observed data are the moderately dipping normal faults, 45° and 60°, although the probability that the fault dips more steeply, including in a strike slip or reverse fault orientation, is approximately 30%. The probability of a thicker nonmarine unit is 67%, more probable than a thinner nonmarine unit. This suggests that the Vaca Fault dips moderately to the east and truncates a thicker nonmarine unit, but that any further process modeling should include alternatives of the geologic structures.

California↗

USGS2005

Shear-wave velocity of surficial geologic sediments in Northern California: Statistical distributions and depth dependence

Shear-wave velocities of shallow surficial geologic units were measured at 210 sites in a 140-km2 area in the greater Oakland, California, area near the margin of San Francisco Bay. Differences between average values of shear-wave velocity for each geologic unit computed by alternative approaches were in general smaller than the observed variability. Averages estimated by arithmetic mean, geometric mean, and slowness differed by 1 to 8%, while coefficients of variation ranged from 14 to 25%. With the exception of the younger Bay mud that underlies San Francisco Bay, velocities of the geologic units are approximately constant with depth. This suggests that shear-wave velocities measured at different depths in these surficial geologic units do not need to be normalized to account for overburden stress in order to compute average values. The depth dependence of the velocity of the younger Bay mud most likely is caused by consolidation. Velocities of each geologic unit are consistent with a normal statistical distribution. Average values increase with geologic age, as has been previously reported. Velocities below the water table are about 7% less than those above it. ?? 2005, Earthquake Engineering Research Institute.

Earthquake Spectra↗

USGS2015

Geologic maps of the eastern Alaska Range, Alaska (1:63,360 scale)

This report provides a description of map units for a suite of 44 inch-to-mile (1:63,360-scale) geologic quadrangle maps of the eastern Alaska Range. This report also contains a geologic and tectonic summary and a comprehensive list of references pertaining to geologic mapping and specialized studies of the region. In addition to the geologic maps of the eastern Alaska Range, this package includes a list of map units and an explanation of map symbols and abbreviations. The geologic maps display detailed surficial and bedrock geology, structural and stratigraphic data, portrayal of the active Denali fault that bisects the core of the east–west-trending range, and portrayal of other young faults along the north and south flanks of the range.

Alaska↗

USGS2006

Developing a map of geologically defined site-condition categories for California

Consideration of site conditions is a vital step in analyzing and predicting earthquake ground motion. The importance of amplification by soil conditions has long been recognized, but though many seismic-instrument sites have been characterized by their geologic conditions, there has been no consistent, simple classification applied to all sites. As classification of sites by shear-wave velocity has become more common, the need to go back and provide a simple uniform classification for all stations has become apparent. Within the Pacific Earthquake Engineering Research Center's Next Generation Attenuation equation project, developers of attenuation equations recognized the need to consider site conditions and asked that the California Geological Survey provide site conditions information for all stations that have recorded earthquake ground motion in California. To provide these estimates, we sorted the available shear-wave velocity data by geologic unit, generalized the geologic units, and prepared a map so that we could use the extent of the map units to transfer the velocity characteristics from the sites where they were measured to sites on the same or similar materials. This new map is different from the California Geological Survey "preliminary site-conditions map of California" in that 19 geologically defined categories are used, rather than National Earthquake Hazards Reduction Program categories. Although this map does not yet cover all of California, when completed it may provide a basis for more precise consideration of site conditions in ground-motion calculations.

Bulletin of the Seismological Society of America↗

USGS2017

A fault‐based model for crustal deformation in the western United States based on a combined inversion of GPS and geologic inputs

We develop a crustal deformation model to determine fault‐slip rates for the western United States (WUS) using the Zeng and Shen (2014) method that is based on a combined inversion of Global Positioning System (GPS) velocities and geological slip‐rate constraints. The model consists of six blocks with boundaries aligned along major faults in California and the Cascadia subduction zone, which are represented as buried dislocations in the Earth. Faults distributed within blocks have their geometrical structure and locking depths specified by the Uniform California Earthquake Rupture Forecast, version 3 (UCERF3) and the 2008 U.S. Geological Survey National Seismic Hazard Map Project model. Faults slip beneath a predefined locking depth, except for a few segments where shallow creep is allowed. The slip rates are estimated using a least‐squares inversion. The model resolution analysis shows that the resulting model is influenced heavily by geologic input, which fits the UCERF3 geologic bounds on California B faults and ±one‐half of the geologic slip rates for most other WUS faults. The modeled slip rates for the WUS faults are consistent with the observed GPS velocity field. Our fit to these velocities is measured in terms of a normalized chi‐square, which is 6.5. This updated model fits the data better than most other geodetic‐based inversion models. Major discrepancies between well‐resolved GPS inversion rates and geologic‐consensus rates occur along some of the northern California A faults, the Mojave to San Bernardino segments of the San Andreas fault, the western Garlock fault, the southern segment of the Wasatch fault, and other faults. Off‐fault strain‐rate distributions are consistent with regional tectonics, with a total off‐fault moment rate of 7.2 × 10 18 "> 7.2 × 10 18 and 8.5 × 10 18    N · m / year "> 8.5 × 10 18 N ⋅ m / year for California and the WUS outside California, respectively.

Bulletin of the Seismological Society of America↗