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USGS2012

Tabulated Transmissivity and Storage Properties of the Floridan Aquifer System in Florida and Parts of Georgia, South Carolina, and Alabama

A goal of the U.S. Geological Survey Groundwater Resources Program is to assess the availability of fresh water within each of the principal aquifers in the United States with the greatest groundwater withdrawals. The Floridan aquifer system (FAS), which covers an area of approximately 100,000 square miles in Florida and parts of Georgia, Alabama, Mississippi, and South Carolina, is one such principal aquifer, having the fifth largest groundwater withdrawals in the Nation, totaling 3.64 billion gallons per day in 2000. Compilation of FAS hydraulic properties is critical to the development and calibration of groundwater flow models that can be used to develop water budgets spatially and temporally, as well as to evaluate resource changes over time. Wells with aquifer test data were identified as Upper Floridan aquifer (UFA), Lower Floridan aquifer (LFA), Floridan aquifer system (FAS, Upper Floridan with some middle and/or Lower Floridan), or middle Floridan confining unit (MCU), based on the identification from the original database or report description, or comparison of the open interval of the well with previously published maps. This report consolidates aquifer hydraulic property data obtained from multiple databases and reports of the U.S. Geological Survey, various State agencies, and the Water Management Districts of Florida, that are compiled into tables to provide a single information source for transmissivity and storage properties of the FAS as of October 2011. Transmissivity calculated from aquifer pumping tests and specific-capacity data are included. Values for transmissivity and storage coefficients are intended for use in regional or sub regional groundwater flow models; thus, any tests (aquifer pumping tests and specific capacity data) that were conducted with packers or for open intervals less than 30 feet in length are excluded from the summary statistics and tables of this report, but are included in the database. The transmissivity distribution from the aquifer pumping tests is highly variable. The transmissivity based on aquifer pumping tests (from 1,045 values for the UFA and FAS) ranges from 8 to about 9,300,000 square feet per day (ft 2 /d) and values of storage coefficient (646 reported) range from 3x10 -9 to 0.41. The 64 transmissivity values for the LFA range from about 130 to 4,500,000 ft 2 /d, and the 17 storage coefficient values range from 7x10 -8 to 0.03. The 14 transmissivity values for the MCU range from 1 to about 600,000 ft 2 /d and the 10 storage coefficient values range from 8x10 -8 to 0.03. Transmissivity estimates for the UFA and FAS for 442 specific capacity tests range from approximately 200 to 1,000,000 ft 2 /d.

Alabama, Florida, Georgia, South Carolina↗

USGS2010

EAARL Coastal Topography and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Assateague Island National Seashore in Maryland and Virginia, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar(EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2010

EAARL Coastal Topography-Eastern Louisiana Barrier Islands, Post-Hurricane Gustav, 2008: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Louisiana barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 6 and 7, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2013

EAARL coastal topography and imagery–Western Louisiana, post-Hurricane Rita, 2005: First surface

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, Virginia. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beachface, acquired post-Hurricane Rita on September 27-28 and October 2, 2005. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the National Aeronautics and Space Administration (NASA) Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Website.

Louisiana↗

USGS2010

EAARL Coastal Topography-Eastern Florida, Post-Hurricane Jeanne, 2004: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Florida coastline beachface, acquired post-Hurricane Jeanne (September 2004 hurricane) on October 1, 2004. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2011

The Alaska Geochemical Database: v. 1.0 - Geologic Materials

What is the AGDB?: The Alaska Geochemical Database (AGDB) is a new, comprehensive compilation of geologic, spatial, descriptive, mineralogical, and analytical geochemical data for samples collected in Alaska and surrounding waters by the U.S. Geological Survey (USGS) from 1962 to 2009. Data for geologic materials (rocks, minerals and mineral separates, soils, lake sediments, bulk stream sediments, and a variety of heavy-mineral concentrates) will be released as a two-sided DVD (USGS Digital Data Series DS 637 v. 1.0) in October of 2011. Future data releases will include water, organic and leachate samples. The AGDB contains all Alaskan data from USGS legacy databases (for example, the RASS and PLUTO systems), and all results produced by USGS in-house and contract chemistry laboratories through December 2009. The database includes geochemical data resulting from the reanalysis of archived materials, such as those from the Alaska Mineral Resource Assessment (AMRAP) and National Uranium Resource Evaluation (NURE) programs, for additional elements and by newer methods. Reanalyses include samples collected statewide as part of the National Geochemical Survey, and samples from a project across the Alaska Range (data released in 2010). The AGDB also contains data for geologic materials from Alaska submitted by USGS researchers to non-USGS and non-contract labs, and a variety of other Alaskan geologic materials samples. Quality Control: Data in the AGDB have undergone extensive quality control screening including searching field notes and maps for accurate location information, verifying media and sample type, linking analytical data to geologic parameters recorded by the submitter, and documenting sample preparation and analytical methods. Data Files The AGDB v. 1.0 two-sided DVD includes: * a 4.3 GB Microsoft Access® 2007 relational database (as two linked .mdb files); * the same database in Microsoft Access® 2003; * Microsoft Excel® spreadsheet tables (.xls files) and ASCII text files that display the results of common queries to the database (for example, Ag-Cr values for concentrate samples; rock samples by quadrangle); * references for analytical methods; * references to published data; and * metadata in three file formats. Data Availability: * The Alaska Geochemical Database will be available in a searchable, spatially referenced, online format at http://mrdata.usgs.gov/; estimated availability early 2012. * A 2012 update (AGDB v. 2.0) will include water, organic, leachate, and miscellaneous sample media. For More Information: On sample media or analytical methods: http://minerals.cr.usgs.gov/projects/analytical_chem/references.html Text prepared by Jeanine M. Schmidt and Matt Granitto Figure prepared by Nora Shew; Layout by Jeanine Schmidt Artwork on page 1 by Daniel Granitto (used by permission) The USGS Mineral Resources Program is the sole Federal provider of research and information on nonfuel mineral resources.

Fact Sheet↗

USGS1998

Depth-duration frequency of precipitation for Texas

The U.S. Geological Survey, in cooperation with the Texas Department of Transportation, conducted a study of the depth-duration frequency of precipitation for Texas. Depth-duration frequency is an estimate of the depth of precipitation for a specified duration and frequency or recurrence interval. For this report, precipitation durations of 15, 30, and 60 minutes; 1, 2, 3, 6, 12, and 24 hours; and 1, 2, 3, 5, and 7 days were investigated. The recurrence intervals for the frequencies range from 2 to 500 years. The time series of precipitation annual maxima for 173 fifteen-minute, 274 hourly, and 865 daily National Weather Service precipitation stations with at least 10 years of record in Texas provide the basis of depth-duration frequency for each identified duration. In total, about 3,030; 10,160; and 38,120 cumulative years of record are available for the 15-minute, hourly, and daily stations, respectively. L-moment statistics of the precipitation annual maxima were calculated for each duration and for each station using unbiased L-moment estimators. The statistics calculated were the mean, L-scale, L-coefficient of variation, L-skew, and L-kurtosis. The mean for each station and duration was corrected for the bias associated with fixed-interval recording of precipitation. The generalized logistic distribution was determined, using L-moment ratio diagrams, as an appropriate probability distribution for modeling the frequency of annual maxima for durations of 15 minutes to 24 hours; whereas, the generalized extreme-value distribution was determined as appropriate for durations of 1 to 7 days. The location, scale, and shape parameters of the distributions for each duration and each station were calculated from the L-moments. These parameters were contoured using spatial interpolation, based on the geostatistical method of kriging, to produce 37 maps that depict the spatial variation and magnitude of each parameter. Contour maps of the shape parameter for the generalized extreme-value distribution for durations of 1 to 7 days are not presented; the root mean square errors of preliminary maps for 1- to 7-day shape parameters were not appreciably smaller than the statewide standard deviation. Therefore, a single statewide mean shape parameter was used for 1- to 7-day durations. The depth-duration frequency for any location in Texas can be estimated using the contour maps and the equation of the corresponding distribution.

Texas↗

USGS2010

EAARL Coastal Topography-Mississippi and Alabama Barrier Islands, Post-Hurricane Gustav, 2008

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Mississippi and Alabama barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 8, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2010

EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and submerged topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Chandeleur Islands, acquired March 3, 2010. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2002

Color-coded contour map of Mars M 25M RKN

NOTES ON BASE This map is based on data from the Mars Orbiter Laser Altimeter (MOLA) (Smith and others, 2001), an instrument on NASA's Mars Global Surveyor (MGS) spacecraft (Albee and others, 2001). The image used for the base of this map represents more than 600 million measurements gathered between 1999 and 2001, adjusted for consistency (Neumann and others, 2001, 2002) and converted to planetary radii. These have been converted to elevations above the areoid as determined from a martian gravity field solution GMM2 (Lemoine and others, 2001), truncated to degree and order 50, and oriented according to current standards (see below). The average accuracy of each point is originally ~100 meters in horizontal position, and ~1 meter in radius (Neumann, 2001). However, the total elevation uncertainty is at least +3 m due to the global error in the areoid (+1.8 meters according to Lemoine and others, 2001) and regional uncertainties in its shape (communication from Neumann, 2002). The measurements were converted into a digital elevation model (DEM) (communication from Neumann, 2002; Neumann and others, 2001; Smith and others, 2001) using Generic Mapping Tools software (Wessel and Smith, 1998), with a resolution of 0.015625 degrees per pixel or 64 pixels per degree. In projection, the pixels are 926.17 meters in size at the equator. PROJECTION The Mercator projection is used between latitudes +57°, with a central meridian at 0° and latitude equal to the nominal scale at 0°. The Polar Stereographic projection is used for the polar regions north of the +55° parallel and south of the –55° parallel with a central meridian set for both at 0°. The adopted equatorial radius is 3,396.19 km (Duxbury and others 2002; Seidelmann and others 2002). COORDINATE SYSTEM The MOLA data were initially referenced to an internally consistent inertial coordinate system, derived from tracking of the MGS spacecraft. By adopting appropriate values for the orientation of Mars as defined by the International Astronomical Union (IAU) and the International Association of Geodesy (IAG) (Seidelmann and others, 2002), these inertial coordinates were converted into the planet-fixed coordinates (longitude and latitude) used on this map. These values include the orientation of the north pole of Mars (including the effects of precession), the rotation rate of Mars, and a value for W0 of 176.630°, where W0 is the angle along the equator to the east, between the 0° meridian and the equator's intersection with the celestial equator at the standard epoch J2000.0 (Seidelmann and others, 2002). This value of W0 was chosen (Duxbury and others, 2002) in order to place the 0° meridian through the center of the small (~500 m) crater Airy-0, located in the crater Airy (de Vaucouleurs and others, 1973; Seidelmann and others, 2002). Longitude increases to the east, and latitude is planetocentric as allowed by IAU/IAG standards (Seidelmann and others, 2002) and in accordance with current NASA and USGS standards (Duxbury and others, 2002). A secondary grid (printed in red) has been added to the map as a reference to the west longitude/planetographic latitude system that is also allowed by IAU/IAG standards (Seidelmann and others, 2002) and has also been used for Mars. The figure adopted to compute this secondary grid is an oblate spheroid with an equatorial radius of 3,396.19 km and a polar radius of 3,376.2 km (Duxbury and others, 2002; Seidelmann and others, 2002). MAPPING TECHNIQUES To create the topographic base image, the original DEM produced by the MOLA team in Simple Cylindrical projection with a resolution of 64 pixels per degree was projected into the Mercator and Polar Stereographic pieces. A shaded relief was generated from each DEM with a sun angle of 30° from horizontal and a sun azimuth of 270°, as measured clockwise from north, and a vertical exaggeration of 100%. Illumination is from the west, which follows a long-standing USGS tradition for planetary maps. This allows for continuity in the shading between maps and quadrangles, and most closely resembles lighting conditions found on imagery. The DEM values were then mapped to a smooth global color look-up table. Note that the chosen color scheme simply represents elevation changes and is not intended to imply anything about surface characteristics (e.g., past or current presence of water or ice). These two files were then merged and scaled to 1:25 million for the Mercator portion and 1:15,196,708 for the two Polar Stereographic portions, with a resolution of 300 dots per inch. The projections have a common scale of 1:13,923,113 at +56° latitude. Contours were created from the DEM at a 1-kilometer interval. Contours for features with a diameter of 3 km or less (features too small for this map scale) were removed. The contours were then simplified by removing points along the contours spaced less than 1 km apart. NOMENCLATURE Names on this sheet are approved by the IAU and have been applied for features clearly visible at the scale of this map. For a complete list of the IAU-approved nomenclature for Mars, see the Gazetteer of Planetary Nomenclature at http://planetarynames.wr.usgs.gov/. Font color was chosen for readability. Names followed by an asterisk are provisionally approved. M 25M RKN: Abbreviation for Mars, 1:25,000,000 series, shaded relief (R), with color (K) and nomenclature (N) (Greeley and Batson, 1990).

Open-File Report↗

USGS1980

Storm runoff as related to urbanization in the Portland, Oregon-Vancouver, Washington Area

A series of equations was developed to provide a better method of determining flood frequencies in the Portland-Vancouver urban area than is now available. The resulting regression equations can be used to compute peak discharge and storm runoff with a standard error of estimate of approximately 30 percent. Basins used to define the regression equations ranged in size from 0.2 to 26 square miles. Those physical basin parameters that proved to be significant are: drainage area, effective impervious area, storage, rainfall intensity, basin slope, and soil infiltration. The equations indicate that total urbanization of an undeveloped basin can increase peak discharge as much as 3? times and almost double the volume of storm runoff. Impervious area, as delineated by mapping techniques, proved to be an inadequate physical parameter for use in the regression equations because builders and planners have devised many methods of routing storm runoff from impervious areas to the main channel (in effect, speeding up or slowing down the response to the storm). In some parts of the study area, storm runoff was diverted into dry wells and never entered the main channel. To define the effect of this rerouting, the digital model was used to find an effective impervious area that would 'best fit' the rainfall-runoff data. Field estimates to verify the effectiveness of the impervious area for two of the basins showed that optimizations were within 20 percent of those shown by the digital model. Users of these data who may find the effective impervious area a difficult, expensive, and time-consuming parameter to obtain have an alternative. The combination of land-use type I (parks, forests, and vacant lots) and Type II (agriculture) proved to be an excellent inverse indicator of impervious area. Land-use types I and II, coupled with the street-gutter density, an indication of effective routing, provide the user with alternative indices of urbanization.

Oregon, Washington↗

USGS1979

Suspended- and bedload-sediment transport in the Snake and Clearwater rivers in the vicinity of Lewiston, Idaho, August 1976 through July 1978

Impoundment of water in the Snake River and Clearwater River arms behind Lower Granite Dam (see cover map) began in June 1975. At this time, Lower Granite Reservoir and Lock facilities, constructed by the USACE (U.S. Army Corps of Engineers), Walla Walla District, became operational. Construction and operation of this facility necessitated collection of hydrologic data that did not exist prior to construction. The USACE requested the USGS (U.S. Geological Survey) to collect hydraulic- and channel-geometry data and describe sediment-transport characteristics, beginning in the spring of 1972. This report summarizes information collected during August 1976 through July 1978 and is the fifth in a series of reports designed to release hydrologic data on a timely basis. Although some of the data were collected during the late summer and fall periods (August through December) of 1976 and 1977, most were collected during the spring runoff periods of 1977 and 1978. Therefore, for convenience, data contained in this report will be referred to as the 1977-78 data. Because this is primarily a basic-data report, no interpretation of the data is provided. This report presents tables of selected data collected and computations compiled since the 1976 report (Seitz, 1976). Most of the tabular data are also presented on graphs. Some of the graphs show plots of data since 1972~ others show plots of only the 1977-78 data. Relatively minor amounts of bedload were transported during the 1977 drought period. Therefore, regular scheduled sampling of the bedload was impractical. Only two bedload samples were collected from the Clearwater River in 1977. The resultant data are included in tables 10, 12, and 14, and figure 6. All bedload data in this report should be considered tentative, pending completion of sampler-calibration studies and possible adjustment of the data to correct for sampler efficiency. An analysis of the middle Snake River streamflow record was made during 1977. The streamflow rating for the Snake River near Anatone, Washington, gage was found to be in error at high stages. The streamflow record for water years 1974 and 1975 was revised and published with 1976 water-year data (Water Resources Data for Idaho, Water Year 1976). The revised Snake River near Anatone streamflow rating was used to recompute the sediment-discharge rating curve (fig. 3). This study program is funded by the USACE through a cooperative agreement with the USGS. All field work, laboratory analysis, and compilation of data are being conducted by the USGS. Data collection is scheduled to terminate at the end of the 1979 runoff season. A reanalysis of all data collected since the start of the program will correct all provisional records since 1972, including the 1974, 1975, and 1976 years for the Snake River near Anatone station.

Idaho↗

USGS2021

Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013

Bulletin 17C (B17C) recommends fitting the log-Pearson Type III (LP−III) distribution to a series of annual peak flows at a streamgage by using the method of moments. The third moment, the skewness coefficient (or skew), is important because the magnitudes of annual exceedance probability (AEP) flows estimated by using the LP–III distribution are affected by the skew; interest is focused on the right-hand tail of the distribution, which represents the larger annual peak flows that correspond to small AEPs. For streamgages having modest record lengths, the skew is sensitive to extreme events like large floods, which cause a sample to be highly asymmetrical or “skewed.” For this reason, B17C recommends using a weighted-average skew computed from the skew of the annual peak flows for a given streamgage and a regional skew. This report presents an estimate of regional skew for a study area encompassing parts of eastern New York and Pennsylvania. A total of 232 candidate U.S. Geological Survey streamgages that were unaffected by extensive regulation, diversion, urbanization, or channelization were considered for use in the skew analysis; after screening for redundancy and pseudo record length ( P RL ) of at least 36 years, 183 streamgages were selected for use in the study. Flood frequencies for candidate streamgages were analyzed by employing the expected moments algorithm, which extends the method of moments so that it can accommodate interval, censored, and historical/paleo flow data, as well as the multiple Grubbs-Beck test to identify potentially influential low floods in the data series. Bayesian weighted least squares/Bayesian generalized least squares regression was used to develop a regional skew model for the study area that would incorporate possible variables (basin characteristics) to explain the variation in skew in the study area. Ten basin characteristics were considered as possible explanatory variables; however, none produced a pseudo coefficient of determination greater than 1 percent; as a result, these characteristics did not help to explain the variation in skew in the study area. Therefore, a constant model that had a regional skew coefficient of 0.32 and an average variance of prediction at a new streamgage ( AVP new , which corresponds to the mean square error [MSE] of 0.11) was selected. The AVP new corresponds to an effective record length of 68 years, a marked improvement over the Bulletin 17B national skew map, whose reported MSE of 0.302 indicated a corresponding effective record length of only 17 years.

New York, Pennsylvania↗

USGS2020

Methods for estimating regional skewness of annual peak flows in parts of the Great Lakes and Ohio River Basins, based on data through water year 2013

Bulletin 17C (B17C) recommends fitting the log-Pearson Type III (LP−III) distribution to a series of annual peak flows at a streamgage by using the method of moments. The third moment, the skewness coefficient (or skew), is important because the magnitudes of annual exceedance probability (AEP) flows estimated by using the LP−III distribution are affected by the skew; interest is focused on the right-hand tail of the distribution, which represents the larger annual peak flows that correspond to small AEPs. For streamgages having modest record lengths, the skew is sensitive to extreme events like large floods, which cause a sample to be highly asymmetrical or “skewed.” For this reason, B17C recommends using a weighted-average skew computed from the station skew for a given streamgage and a regional skew. This report generates an estimate of regional skew for a study area encompassing most of the Great Lakes Basin (hydrologic unit 04) and part of the Ohio River Basin (hydrologic unit 05). A total of 551 candidate streamgages that were unaffected by extensive regulation, diversion, urbanization, or channelization were considered for use in the skew analysis; after screening for redundancy and pseudo record length greater than 36 years, 368 streamgages were selected for use in the study. Flood frequencies for candidate streamgages were analyzed by employing the Expected Moments Algorithm, which extends the method of moments so that it can accommodate interval, censored, and historic/paleo flow data, as well as the Multiple Grubbs-Beck test to identify potentially influential low floods in the data series. Bayesian weighted least squares/Bayesian generalized least squares regression was used to develop a regional skew model for the study area that would incorporate possible variables (basin characteristics) to explain the variation in skew in the study area. Twelve basin characteristics were considered as possible explanatory variables; however, none produced a pseudo coefficient of determination greater than 5 percent; as a result, these characteristics did not help to explain the variation in skew in the study area. Therefore, a constant model having a regional skew coefficient of 0.086 and an average variance of prediction ( AVP new ) (which corresponds to the mean square error [MSE]) of 0.13 at a new streamgage was selected. The AVP new corresponds to an effective record length of 54 years, a marked improvement over the Bulletin 17B national skew map, whose reported MSE of 0.302 indicated a corresponding effective record length of only 17 years.

Great Lakes and Ohio River Basins↗

USGS2006

Proceedings of the U.S. Geological Survey Sixth Biennial Geographic Information Science Workshop, Denver, Colorado, April 24-28, 2006

The U.S. Geological Survey's (USGS) Sixth Biennial Geographic Information Science Workshop April 24 - 28, 2006, at the Denver Federal Center in Denver, Colorado, provides a unique opportunity for multi-disciplinary Geographic Information Systems (GIS) and associated scientific professionals to share, learn, present, and discuss a wide variety of geospatial-related topics. Information is exchanged through a series of plenary sessions, hands-on technical workshops, user and commercial vendor demonstrations, lecture and poster sessions, and specialty meetings. Workshop attendance is limited to Department of Interior (DOI) and USGS employees and contractors; however, plenary, hands-on, and lecture sessions have presenters from other Federal agencies, numerous commercial vendors, universities, and several consortia. Over 175 participants are expected to attend the Workshop. Several prominent speakers are featured at this Workshop. Monday evening Star Guest Speaker and National Aeronautics and Space Administration (NASA) Astronaut Captain Dominic Gorie will talk about his experiences as a veteran of three space flights and over 32 days in space, including the NASA Space Shuttle Radar Topography Mission that mapped more than 47 million miles of the Earth's land surface. Selected as an astronaut candidate by NASA in December 1994, Captain Gorie is currently Chief of the Astronaut Shuttle Branch. Monday evening also features a town hall meeting with Geographic Information Office (GIO) leaders Karen Siderelis, Kevin Gallagher, Bob Pierce, Steve Guptill, Mark DeMulder, John Mahoney, and Mark Negri, who will discuss changes and activities within the GIO in an open discussion format. Tuesday plenary sessions feature keynote speaker Dr. P. Patrick Leahy, Acting USGS Director. Dr. Leahy holds undergraduate and graduate degrees in geology (1968) and geophysics (1970) from Boston College. In 1979, he received his doctorate in geology from Rensselaer Polytechnic Institute, where he specialized in regional ground-water studies and hydraulics. Dr. Leahy has been with the USGS since 1974, and has held various technical and managerial positions, including Associate Director for Geology and Chief of the National Water-Quality Assessment (NAWQA) Program. Dr. Leahy will be discussing a broad range of topics including Bureau accomplishments, initiatives, and budgets. The purpose of this proceedings volume is to serve as an activity reference for Workshop attendees as well as an archive of technical abstracts submitted, presented, and discussed at the Workshop. Author, co-author, and presenter names, affiliations, and contact information are listed with presentation titles along with submitted abstracts. Some hands-on sessions are offered twice. In these instances, abstracts submitted for publication are presented in the proceedings on both days they are offered. All acronyms used in these proceedings are explained in the text of each abstract. The term 'ArcGIS' refers to an integrated collection of GIS software products produced by Environmental Systems Research Institute, Inc. (ESRI).

Scientific Investigations Report↗

USGS2013

Geologic framework, structure, and hydrogeologic characteristics of the Knippa Gap area in eastern Uvalde and western Medina Counties, Texas

The Edwards aquifer is the primary source of potable water for the San Antonio area in south-central Texas. The Knippa Gap was postulated to channel or restrict flow in the Edwards aquifer in eastern Uvalde County, and its existence was based on a series of numerical simulations of groundwater flow in the aquifer. To better understand the function of the area known as the Knippa Gap as it pertains to its geology and structure, the geologic framework, structure, and hydrogeologic characteristics of the area were evaluated by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers-Fort Worth District. The principal structural feature in the San Antonio area is the Balcones Fault Zone, which is the result of Miocene age faulting. In Medina County, the faulting of the Balcones Fault Zone has produced a relay-ramp structure that dips to the southwest from the Edwards aquifer recharge zone and extends westward and below land surface from Seco Creek. Groundwater flow paths in the Edwards aquifer are influenced by faulting and geologic structure. Some faults act as barriers to groundwater flow paths where the aquifer is offset by 50 percent or more and result in flow moving parallel to the fault. The effectiveness of a fault as a barrier to flow changes as the amount of fault displacement changes. The structurally complex area of the Balcones Fault Zone contains relay ramps, which form in extensional fault systems to allow for deformation changes along the fault block. In Medina County, the faulting of the Balcones Fault Zone has produced a relay-ramp structure that dips to the southwest from the Edwards aquifer recharge zone. Groundwater moving down the relay ramp in northern Medina County flows downgradient (downdip) to the structural low (trough) from the northeast to the southwest. In Uvalde County, the beds dip from a structural high known as the Uvalde Salient. This results in groundwater moving from the structural high and downgradient (dip) towards a structural low (trough) to the northeast. These two opposing structural dips result in a subsurface structural low (trough) locally referred to as the Knippa Gap. This trough is located in eastern Uvalde County beneath the towns of Knippa and Sabinal. By using data that were compiled and collected for this study and previous studies, a revised map was constructed depicting the geologic framework, structure, and hydrogeologic characteristics of the Knippa Gap area in eastern Uvalde and western Medina Counties, Tex. The map also shows the interpreted structural dip directions and interpreted location of a structural low (trough) in the area known as the Knippa Gap.

Texas↗

USGS2004

Archive of Digital Boomer Seismic Reflection Data Collected During USGS Field Activities 93LCA01 and 94LCA01 in Kingsley, Orange, and Lowry Lakes, Northeast Florida, 1993 and 1994

In August and September of 1993 and January of 1994, the U.S. Geological Survey, under a cooperative agreement with the St. Johns River Water Management District (SJRWMD), conducted geophysical surveys of Kingsley Lake, Orange Lake, and Lowry Lake in northeast Florida. This report serves as an archive of unprocessed digital boomer seismic reflection data, trackline maps, navigation files, GIS information, observer's logbook, Field Activity Collection System (FACS) logs, and formal FGDC metadata. A filtered and gained GIF image of each seismic profile is also provided. Refer to the Acronyms page for expansion of acronyms and abbreviations used in this report. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU). Examples of SU processing scripts and in-house (USGS) software for viewing SEG-Y files (Zihlman, 1992) are also provided. The data archived here were collected under a cooperative agreement with the St. Johns River Water Management District as part of the USGS Lakes and Coastal Aquifers (LCA) Project. For further information about this study, refer to http://coastal.er.usgs.gov/stjohns, Kindinger and others (1994), and Kindinger and others (2000). The USGS Florida Integrated Science Center (FISC) - Coastal and Watershed Studies in St. Petersburg, Florida, assigns a unique identifier to each cruise or field activity. For example, 93LCA01 tells us the data were collected in 1993 for the Lakes and Coastal Aquifers (LCA) Project and the data were collected during the first field activity for that project in that calendar year. For a detailed description of the method used to assign the field activity ID, see http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html. The boomer is an acoustic energy source that consists of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled at the sea surface and when discharged emits a short acoustic pulse, or shot, that propagates through the water and sediment column. The acoustic energy is reflected at density boundaries (such as the seafloor or sediment layers beneath the seafloor), detected by the receiver, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (e.g., 0.5 s) and recorded for specific intervals of time (e.g., 100 ms). In this way, a two-dimensional vertical image of the shallow geologic structure beneath the ship track is produced. Acquisition geometery for 94LCA01 is recorded in the operations logbook. No logbook exists for 93LCA01. Table 1 displays acquisition parameters for both field activities. For more information about the acquisition equipment used, refer to the FACS equipment logs. The unprocessed seismic data are stored in SEG-Y format (Barry and others, 1975). For a detailed description of the data format, refer to the SEG-Y Format page. See the How To Download SEG-Y Data page for more information about these files. Processed profiles can be viewed as GIF images from the Profiles page. Refer to the Software page for details about the processing and examples of the processing scripts. Detailed information about the navigation systems used for each field activity can be found in Table 1 and the FACS equipment logs. To view the trackline maps and navigation files, and for more information about these items, see the Navigation page. The original trace files were recorded in nonstandard ELICS format and later converted to standard SEG-Y format. The original trace files for 94LCA01 lines ORJ127_1, ORJ127_3, and ORJ131_1 were divided into two or more trace files (e.g., ORJ127_1 became ORJ127_1a and ORJ127_1b) because the original total number of traces exceeded the maximum allowed by the processing system. Digital data were not recoverable for 93LCA

Data Series↗

USGS2018

Geomorphology and vegetation change at Colorado River campsites, Marble and Grand Canyons, Arizona

Sandbars along the Colorado River are used as campsites by river runners and hikers and are an important recreational resource within Grand Canyon National Park, Arizona. Regulation of the flow of river water through Glen Canyon Dam has reduced the amount of sediment available to be deposited as sandbars, has reduced the magnitude and frequency of flooding events, and has increased the magnitude of baseflows. This has caused widespread erosion of sandbars and has allowed native and non-native vegetation to expand on open sand. Previous studies show an overall decline in campsite area despite the use of controlled floods to rebuild sandbars. Monitoring of campsites since 1998 has shown changes in campsite area, but the factors that cause gains and losses in campsite area have not been quantified. These factors include, among others, changes in sandbar volume and slope under different dam flow regimes that include controlled floods, gullying caused by monsoonal rains, vegetation expansion, and reworking of sediment by aeolian processes. Using 4-band aerial imagery and digital elevation models (DEMs) derived from total-station survey data, we analyzed topographic and vegetation change at 35 of 37 long-term monitoring sites (2 sites were excluded because topographic measurements do not overlap with measurements of campsite area) using data collected between 2002 and 2009 to quantify the factors affecting the size of campsite area. Over the course of the study period, there was a net loss in campsite area of 2,431 square meters (m 2 ). We find that (1) 53 percent of the net loss was caused by topographic change associated with controlled floods and erosion of those flood deposits, (2) 47 percent of the net loss was caused by increases in vegetation cover, the majority of which occurred in high-elevation campsite area, and (3) gullying was significant at certain sites but overall was a minor factor. Sites in critical reaches—sections of river where campsites are infrequent or where there is high demand by river runners—were subjected to more erosion and changes in sandbar slope than sites in noncritical reaches, suggesting that campsite area is less stable in those reaches. There was also a greater increase in vegetation cover at sites in noncritical reaches than at sites in critical reaches. Our results show a continuation of sandbar erosion and vegetation encroachment that has been occurring at campsites since construction of the dam. A new campsite survey methodology using a tablet-based geographic information system (GIS) approach was also developed in an effort to map campsite area on digital orthophotographs. Using a series of repeat measurements, we evaluated the inherent uncertainty in mapping campsite area, the accuracy of the new tablet-based method, and if there is any bias between the tablet method and the total-station method that is currently used. We find that uncertainty associated with surveyor judgment while using the total-station method is about 15 percent, which is higher than a previously reported uncertainty of 10 percent. Use of the tablet method adds additional uncertainty; however, the benefits of being able to quantify factors that lead to campsite-area change in the field may outweigh the additional error. Future campsite monitoring may need to consist of a combination of total-station and orthophotograph techniques.

Arizona↗