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At least 1,225 records · Page 68Linked to original sources
USGS2013

User's guide and metadata for WestuRe: U.S. Pacific Coast estuary/watershed data and R tools

Overview There are about 350 estuaries along the U.S. Pacific Coast (U.S. Fish andWildlife 2011). Basic descriptive data for these estuaries, such as their size and watershed area, are important for coastal-scale research and conservation planning. However, this information is spread among many sources, making it difficult to find and standardize. The goal of the WestuRe Project is to provide a framework to: (1) make general descriptive data for estuaries and their watersheds more accessible, and (2) provide tools to make analyzing and visualizing these data easier. The WestuRe download includes data describing U.S. Pacific Coast estuaries and their corresponding watersheds from northern Washington (including the region located along the Strait of Juan de Fuca that goes from Port Townsend to Cape Flattery, 48.383°N) to southern California (Tijuana Estuary, 32.557°N), excluding Puget Sound proper and coastal islands (Fig. 1). The WestuRe data currently include shapefiles of estuary and watershed polygons as well as CSV files summarizing geomorphological and climate data (Fig. 2, Section 2). The WestuRe tools help users extract and view relevant data using the statistical program R and Google Earth (Fig. 3, Section 3). Potential applications of the data include: Describing and comparing estuaries and watersheds at the landscape scale Identifying relationships between estuary/watershed variables Incorporating estuary/watershed attributes in models to predict species and habitat distributions Classifying estuaries according to morphology, climate, and habitat (Lee and Brown 2009)

California, Oregon, Washington↗
USGS2013

Creating potentiometric surfaces from combined water well and oil well data in the midcontinent of the United States

For years, hydrologists have defined potentiometric surfaces using measured hydraulic-head values in water wells from aquifers. Down-dip, the oil and gas industry is also interested in the formation pressures of many of the same geologic formations for the purpose of hydrocarbon recovery. In oil and gas exploration, drillstem tests (DSTs) provide the formation pressure for a given depth interval in a well. These DST measurements can be used to calculate hydraulic-head values in deep hydrocarbon-bearing formations in areas where water wells do not exist. Unlike hydraulic-head measurements in water wells, which have a low number of problematic data points (outliers), only a small subset of the DST data measure true formation pressures. Using 3D imaging capabilities to view and clean the data, we have developed a process to estimate potentiometric surfaces from erratic DST data sets of hydrocarbon-bearing formations in the midcontinent of the U.S. The analysis indicates that the potentiometric surface is more readily defined through human interpretation of the chaotic DST data sets rather than through the application of filtering and geostatistical analysis. The data are viewed as a series of narrow, 400-mile-long swaths and a 2D viewer is used to select a subset of hydraulic-head values that represent the potentiometric surface. The user-selected subsets for each swath are then combined into one data set for each formation. These data are then joined with the hydraulic-head values from water wells to define the 3D potentiometric surfaces. The final product is an interactive, 3D digital display containing: (1) the subsurface structure of the formation, (2) the cluster of DST-derived hydraulic head values, (3) the user-selected subset of hydraulic-head values that define the potentiometric surface, (4) the hydraulic-head measurements from the corresponding shallow aquifer, (5) the resulting potentiometric surface encompassing both oil and gas and water wells, and (6) the land surface elevation of the region. Examples from the midcontinent of the United States, specifically Kansas, Oklahoma, and parts of adjacent states illustrate the process.

Book↗
USGS1998

The collection of clear-water contraction and abutment scour data at selected bridge sites in the coastal plain and piedmont of South Carolina

Clear-water contraction and abutment scour data were collected at 128 bridge sites in South Carolina. In the sandy soils of the Coastal Plain, clear-water-scour data were collected at 63 sites (scour depths ranged from 0.4 to 7.2 meters.) In the clayey soils of the Piedmont, clear-water-scour data were collected at 47 sites (scour depths ranged from 0 to 1.4 meters.) In the sandy, clayey soils of the Piedmont, clear-water-scour data were collected at 18 sites (scour depths ranged from 0.9 to 5.5 meters.) The field data are to be compiled into a data base that will include bridge age; basin, soil and hydraulic characteristics; and theoretical scour data. The data are planned to be statistically analyzed for significant relations that may help explain and (or) predict maximum scour depths at bridges in South Carolina.

South Carolina↗
USGS2016

Accuracy assessment/validation methodology and results of 2010–11 land-cover/land-use data for Pools 13, 26, La Grange, and Open River South, Upper Mississippi River System

Introduction/Background The U.S. Geological Survey (USGS)-Upper Midwest Environmental Sciences Center (UMESC) was responsible for development of several land cover/land use (LCU) systemic datasets of the Upper Mississippi River System (UMRS). These efforts (1989 and 2000) were funded by the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program (UMRR) Long Term Resource Monitoring (LTRM) element. Development of systemic datasets includes the acquisition, processing, and serving of high-resolution aerial photography and land cover/land use spatial datasets ( http://www.umesc.usgs.gov/data_library/land_cover_use/land_cover_use_data.html ). In 2008, the UMRR reached a collaborative agreement with the U.S. Fish and Wildlife Service-Region 3 to collect high-resolution digital imagery of the entire UMRS floodplain during 2010–11 for LTRM. The UMESC helped acquire, process, and serve this imagery, as well as produce and serve the 2010–11 LCU systemic dataset of the UMRS floodplain. Digital imagery for Pools 13, 26, La Grange, and Open River South was collected using an Applanix DSS 439 digital sensor system with a 40 millimeter lens and Color Infrared (CIR) filter. The imagery was collected at a resolution of 20 centimeters/pixel (8 inches/pixel) for Pool 13 and 40 centimeters/pixel (16 inches/pixel) for Pools 26, Open River South, and La Grange. All imagery was projected to Universal Transverse Mercator (UTM) Zone 15, North American Datum of 1983 (NAD 83). The General Wetland Vegetation Classification (GWVC) system used for mapping is hierarchical, and its 31 classes can be collapsed into broader categories using either a 15- or 7-class level. While the 1989 and 2000 LCU systemic datasets have not gone through a traditional thematic accuracy assessment (AA) in the past, nor have they undergone a validation analysis, the end products are of high quality. For each systemic dataset produced (1989, 2000, 2010–11), extensive field reconnaissance is performed before photointerpretation. The intent of this field reconnaissance is to learn, test, and verify image signatures as they relate to vegetation types. Questionable areas on the imagery are visited, and the plants or land features observed in the area are recorded for reference. This procedure verifies vegetation signatures on the imagery with those on the ground. In addition, once the photointerpretation is complete, the final LCU dataset undergoes extensive quality assurance/quality control to ensure the imagery is mapped correctly. Since the 2000 LCU systemic dataset was developed, there has been a growing interest in completing thematic AAs for the LTRM LCU spatial datasets. The objective of an AA is to measure the probability that a particular location has been assigned its correct vegetation class. An AA estimates thematic (map class) errors in the data, giving users information needed to determine data suitability for a particular application. At the same time, data producers are able to learn more about the nature of errors in the data. Thus, the two attributes of an AA are “producers’ accuracy,” which is the probability that an AA point has been mapped correctly (also referred to as an error of omission); and “users’ accuracy,” which is the probability that the map actually represents what was found on the ground (also referred to as error of commission). Producers’ and users’ accuracies can be obtained from the same set of data by using different analyses. Accuracy assessment is an extensive effort that requires seasonal field personnel and equipment, data entry, analyses, and post processing—tasks that are costly and time consuming. The geospatial team at the UMESC has suggested a validation process for understanding the accuracy of the spatial datasets, which will be tested on at least some areas of the UMRS. Validation is not a true verification of map-class type in the field; however, it can provide the user of the map with useful information that is similar to a field AA. Similar to an AA, validation involves generating random points based on the total area for each map class. However, instead of collecting field data, two or three individuals not involved with the photo-interpretative mapping separately review each of the points onscreen and record a best-fit vegetation type(s) for each site. Once the individual analyses are complete, results are joined together and a comparative analysis is performed. The objective of this initial analysis is to identify areas where the validation results were in agreement (matches) and areas where validation results were in disagreement (mismatches). The two or three individuals then perform an analysis, looking at each mismatched site, and agree upon a final validation class. (If two vegetation types at a specific site appear to be equally prevalent, the validation team is permitted to assign the site two best-fit vegetation types.) Following the validation team’s comparative analysis of vegetation assignments, the data are entered into a database and compared to the mappers’ vegetation assignments. Agreements and disagreements between the map and validation classes are identified, and a contingency table is produced. This document presents the AA processes/results for Pools 13 and La Grange, as well as the validation process/results for Pools 13 and 26 and Open River South.

Iowa, Illinois, Minnesota, Missouri, Wisconsin↗
USGS2003

Regional forest land cover characterisation using medium spatial resolution satellite data

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and Sturdevant 1993; Fuller et al. 1994b; Skole et al. 1997), and a circa 1990 Landsat image data set covering the entire land area of the globe has also been developed recently (Jones and Smith 2001). An acquisition strategy aimed at acquiring at least one cloud free image per year for the entire land area of the globe has been initiated for Landsat-7 (Arvidson et al. 2001). This will probably ensure the continued dominance of Landsat in the near future.

Book chapter↗
USGS2021

3-D Modeling of the Duluth Complex from geophysical data

The Mesoproterozoic Duluth Complex in northeastern Minnesota is one of the major plutonic components of the Midcontinent Rift System and hosts a variety of copper-nickel sulfide and platinum-group element deposits. The Duluth Complex is composed of a series of individual mafic and felsic intrusions emplaced 1110-1098 Ma within Paleoproterozoic sedimentary rocks of the Animikie basin and volcanic flows of the Midcontinent Rift. Prior work has included 2-D modeling and qualitative geologic interpretations of gravity and magnetic data (e.g., Chandler, 1990; Chandler and Ferderer, 1989), much of which is still preliminary (V. Chandler, written commun., 2020). Three-dimensional modeling has been limited, with only one 3-D model created using Bouguer gravity data constrained by seismic-reflection interpretations as part of a PhD thesis (Allen, 1994). Given the complex geology of the area, 3-D modeling is useful for providing a complete picture of the variable densities, susceptibilities, and electrical resistivities throughout the Duluth Complex and associated volcanic rocks as well as their depth extent beneath sedimentary cover. Models of these geophysical properties at depth enable more accurate geologic mapping in the subsurface which can lead to an improved understanding of the formation history of the Duluth Complex. In this study, we use aeromagnetic data acquired between 1979-1991 (Chandler, 2007), Bouguer gravity data collected since 1950 (Chandler and Lively, 2019), and magnetotelluric data collected in 2019 to create new 2-D and 3-D geophysical models of the Duluth Complex constrained by seismic reflection, geologic, and rock property data. An inversion of the Bouguer gravity data for thickness of the Duluth Complex using constant densities of 3110 kg/m3 and 2670 kg/m3 for the Duluth Complex and surrounding crustal rocks, respectively, results in thicknesses ranging from ~3-28 km for the Duluth Complex and related intrusions and volcanic rocks (Figure 1A). A 3-D model of the magnetotelluric data reveals low resistivity anomalies at ~5-10 km depth below the northern margin of the Duluth Complex and below the Greenwood Lake intrusion (Figure 1B). We expect to encounter low resistivities at depth associated with the Paleoproterozoic Animikie basin, which makes up the floor of the Duluth Complex, and therefore interpret these anomalies as either the base of the complex or as fragments of Animikie sediments interfingered with igneous intrusive rocks. Finally, 3-D voxel models of density and susceptibility illuminate the subsurface distribution of rock properties below the Duluth Complex which, in combination with resistivity and thickness models, can be used to create a 3-D geologic map of this area.

Minnesota↗
USGS2023

A comprehensive plan for in-water sea turtle data collection in the US Gulf of Mexico

The Deepwater Horizon Open Ocean Trustee Implementation Group (OO TIG) released a Final Open Ocean Restoration Plan 2 in 2019, which included a project titled Developing a Gulf-wide Comprehensive Plan for In-water Sea Turtle Data Collection. This document, A Comprehensive Plan for In-water Sea Turtle Data Collection in the US Gulf of Mexico (Plan), is the culmination of that OO TIG project. This Plan serves as the OO TIG project’s technical report as well as a framework for a biologically and statistically-sound plan to support coordinated in-water sea turtle data collection in the United States (US) Gulf of Mexico (GoM) to determine sea turtle abundance and population trends. The purpose of this Plan is to act as a guide for collecting biologically and statistically robust, in-water sea turtle data in a comprehensive, coordinated, and standardized fashion in the US GoM. Several sea turtle in-water monitoring efforts are underway in the GoM; however, additional coordination and standardization of these efforts will benefit current restoration and recovery objectives. These efforts will aid in restoration project design, assess long-term effectiveness of restoration activities, and create abundance and distribution baselines across the GoM. This Plan provides guidance for researchers investigating sea turtle abundance and demographic questions, as well as for management agencies and restoration planners. A Steering Committee (SC) was assembled to develop this Plan and to recommend a coordinated approach to the formulation of an improved understanding of sea turtle population baselines in the GoM, from which determination of large-scale population changes, effects of specific threats (e.g., oil spills, anthropogenic hazards), and effects of changes in ocean conditions (e.g., climate change) can later be evaluated. In crafting this guidance, the SC considered species distribution and life history characteristics, spatial and logistical considerations, level of effort required to detect trends, methods available and the pros and cons of each, associated assumptions and biases with suggested monitoring methods, and standardization of data collection. Given the current level of data available, the SC has recommended species monitoring in two main phases in neritic and oceanic waters, with additional recommended sampling for surface pelagic drift communities. The two phases in this Plan focus on 1) monitoring a limited number of sites in the first 5 to 8 years, followed by 2) a refined monitoring design. To support implementation of this Plan, the SC also considered broader programmatic needs, including supplemental data collection, program and data management, potential international partnerships, program expansion, and applications including future technology.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2024

Evaluation of data collected by Guam Division of Aquatic and Wildlife Resources during population establishment and monitoring of ko'ko' (Hypotaenidia owstoni) on Rota, Commonwealth of the Northern Mariana Islands, and wildlife monitoring datasets on Cocos Island and Guam

Efforts to recover the critically endangered ko’ko’ (Guam rail, Hypotaenidia owstoni) through establishing an experimental population on the island of Rota in the Commonwealth of the Northern Mariana Islands have been ongoing for three decades. The U.S. Geological Survey collaborated with the Guam Division of Aquatic and Wildlife Resources and the Government of Guam to evaluate whether objectives for three projects can be met with current protocols. The aim of this report was to evaluate existing data provided on (1) ko’ko’ population monitoring on Rota; (2) ko’ko’ population establishment on Rota; plus (3) evaluation of three wildlife monitoring datasets for ko’ko’ on Cocos Island, endangered pulattat (Mariana common moorhen, Gallinula chloropus guami) on Guam, and introduced ungulate species on Guam. Data sources included playback call surveys, point count surveys, release events and studbook information, telemetry of radio-marked birds, as well as landcover classes, storm events, and Oceanic Niño Index information to relate environmental factors to ko’ko’ persistence. Major findings were that reaching objectives was constrained by limited data availability and quality. Suggestions for future study include developing detailed protocols for surveys and data collection, standardizing training procedures for observers, improving data organization and archiving, using methods like distance sampling that account for imperfect detection, and collecting additional data on nests and prey resources to understand drivers of ko’ko’ density and survival. While the current data provide a preliminary assessment, improved sampling designs and consistent protocols are needed to fully address objectives related to the recovery of the ko’ko’. The report provides a roadmap for enhancing data collection and analysis to support management decisions and reach conservation translocation goals about this endangered species and related projects.

Guam, Mariana Islands↗
USGS2025

Methodology for compilation of previously published contour data showing the altitude of the base of Dakota Sandstone on the Colorado Plateau, Arizona, Colorado, New Mexico, and Utah

Structure contours and other geologic information from numerous published geologic maps were digitized and compiled into a digital dataset showing the configuration of a single stratigraphic datum, the base of the Dakota Sandstone and its equivalents across the Colorado Plateau. The principal maps compiled in digital form are a series of 1:250,000-scale 1 degree (°) × 2° quadrangle maps published by the U.S. Geological Survey, augmented by other geologic maps published at various map scales. The compiled digital dataset contains geologic map polygons of the Dakota Sandstone and regional stratigraphic equivalents, the location of faults and fold axes, structure contour lines that define the altitude of the base of the unit and bedding orientation data computed from the structure contour lines. This report provides the scientific rationale for compilation of these data and describes the compilation methodology for each of the data elements. This report provides an extended description of the data compilation in a companion U.S. Geological Survey digital data release of spatial data and attributes associated with the contoured surface and associated geologic data layers.

Arizona, Colorado, New Mexico, Utah↗
USGS2003

Comparison of 2002 Water Year and Historical Water-Quality Data, Upper Gunnison River Basin, Colorado

Introduction: Population growth and changes in land-use practices have the potential to affect water quality and quantity in the upper Gunnison River basin. In 1995, the U.S. Geological Survey (USGS), in cooperation with local sponsors, City of Gunnison, Colorado River Water Conservation District, Crested Butte South Metropolitan District, Gunnison County, Mount Crested Butte Water and Sanitation District, National Park Service, Town of Crested Butte, and Upper Gunnison River Water Conservancy District, established a water-quality monitoring program in the upper Gunnison River basin to characterize current water-quality conditions and to assess the effects of increased urban development and other land-use changes on water quality. The monitoring network has evolved into two groups of stations, stations that are considered as long term and stations that are rotational. The long-term stations are monitored to assist in defining temporal changes in water quality (how conditions have changed over time). The rotational stations are monitored to assist in the spatial definition of water-quality conditions (how conditions differ throughout the basin) and to address local and short term concerns. Another group of stations (rotational group 2) will be chosen and sampled beginning in water year 2004. Annual summaries of the water-quality data from the monitoring network provide a point of reference for discussions regarding water-quality sampling in the upper Gunnison River basin. This summary includes data collected during water year 2002. The introduction provides a map of the sampling locations, definitions of terms, and a one-page summary of selected water-quality conditions at the network stations. The remainder of the summary is organized around the data collected at individual stations. Data collected during water year 2002 are compared to historical data (data collected for this network since 1995), state water-quality standards, and federal water-quality guidelines. Data were collected during water year 2002 following USGS protocols (U.S. Geological Survey, variously dated).

Data Series↗
USGS2018

Chirp subbottom profile data collected in 2015 from the northern Chandeleur Islands, Louisiana

As part of the Barrier Island Evolution Research project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore geophysical survey around the northern Chandeleur Islands, Louisiana, in September 2015. The objective of the project is to improve the understanding of barrier island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual time scales (1–5 years). Collecting geophysical data can help researchers identify relations between the geologic history of the islands and their present day morphology and sediment distribution. High-resolution geophysical data collected along this rapidly changing barrier island system can provide a unique time-series dataset to further the analyses and geomorphological interpretations of this and other coastal systems, improving our understanding of coastal response and evolution over medium-term time scales (months to years). Subbottom profile data were collected in September 2015 offshore of the northern Chandeleur Islands, during USGS Field Activity Number 2015-331-FA. Data products, including raw digital chirp subbottom data, processed subbottom profile images, survey trackline map, navigation files, geographic information system data files and formal Federal Geographic Data Committee metadata, and Field Activity Collection System and operation logs are available for download.

Louisiana↗
USGS2005

Water-quality and biologic data for the Blue River basin, Kansas City metropolitan area, Missouri and Kansas, October 2000 to October 2004

This report presents water-quality and biologic data collected in the Blue River Basin, metropolitan Kansas City, Missouri and Kansas, from October 2000 to October 2004. Data were collected in cooperation with the city of Kansas City, Missouri, Water Services Department as part of an ongoing study designed to characterize long-term water-quality trends in the basin and to provide data to support a strategy for combined sewer overflow control. These data include values of physical properties, fecal indicator bacteria densities, suspended sediment, and concentrations of major ions, nutrients, trace elements, organic wastewater compounds, and pharmaceutical compounds in base-flow and stormflow stream samples and bottom sediments. Six surface-water sites in the basin were sampled 13 times during base-flow conditions and during a minimum of 7 storms. Benthic macroinvertebrate communities are described at 10 sites in the basin and 1 site outside the basin. Water-column and bottom-sediment data from impounded reaches of Brush Creek are provided. Continuous specific conductance, pH, water-quality temperature, turbidity, and dissolved oxygen data are provided for two streams-the Blue River and Brush Creek. Sampling, analytical, and quality assurance methods used in data collection during the study also are described in the report.

Kansas, Missouri↗
USGS2006

Ground-water-quality data in Pennsylvania: A compilation of computerized [electronic] databases, 1979-2004

This study, by the U.S. Geological Survey (USGS) in cooperation with the Pennsylvania Department of Environmental Protection (PADEP), provides a compilation of ground-water-quality data for a 25-year period (January 1, 1979, through August 11, 2004) based on water samples from wells. The data are from eight source agencies唯orough of Carroll Valley, Chester County Health Department, Pennsylvania Department of Environmental Protection-Ambient and Fixed Station Network, Montgomery County Health Department, Pennsylvania Drinking Water Information System, Pennsylvania Department of Agriculture, Susquehanna River Basin Commission, and the U.S. Geological Survey. The ground-water-quality data from the different source agencies varied in type and number of analyses; however, the analyses are represented by 12 major analyte groups:biological (bacteria and viruses), fungicides, herbicides, insecticides, major ions, minor ions (including trace elements), nutrients (dominantly nitrate and nitrite as nitrogen), pesticides, radiochemicals (dominantly radon or radium), volatile organic compounds, wastewater compounds, and water characteristics (dominantly field pH, field specific conductance, and hardness). A summary map shows the areal distribution of wells with ground-water-quality data statewide and by major watersheds and source agency. Maps of 35 watersheds within Pennsylvania are used to display the areal distribution of water-quality information. Additional maps emphasize the areal distribution with respect to 13 major geolithologic units in Pennsylvania and concentration ranges of nitrate (as nitrogen). Summary data tables by source agency provide information on the number of wells and samples collected for each of the 35 watersheds and analyte groups. The number of wells sampled for ground-water-quality data varies considerably across Pennsylvania. Of the 8,012 wells sampled, the greatest concentration of wells are in the southeast (Berks, Bucks, Chester, Delaware, Lancaster, Montgomery, and Philadelphia Counties), in the vicinity of Pittsburgh, and in the northwest (Erie County). The number of wells sampled is relatively sparse in south-central (Adams, Cambria, Cumberland, and Franklin Counties), central (Centre, Indiana, and Snyder Counties), and north-central (Bradford, Potter, and Tioga Counties) Pennsylvania. Little to no data are available for approximately one-third of the state. Water characteristics and nutrients were the most frequently sampled major analyte groups; approximately 21,000 samples were collected for each group. Major and minor ions were the next most-frequently sampled major analyte groups; approximately 17,000 and 12,000 samples were collected, respectively. For the remaining eight major analyte groups, the number of samples collected ranged from a low of 307 samples (wastewater compounds) to a high of approximately 3,000 samples (biological). The number of samples that exceeded a maximum contaminant level (MCL) or secondary maximum contaminant level (SMCL) by major analyte group also varied. Of the 2,988 samples in the biological analyte group, 53 percent had water that exceeded an MCL. Almost 2,500 samples were collected and analyzed for volatile organic compounds; 14 percent exceeded an MCL. Other major analyte groups that frequently exceeded MCLs or SMCLs included major ions (17,465 samples and a 33.9 percent exceedence), minor ions (11,905 samples and a 17.1 percent exceedence), and water characteristics (21,183 samples and a 20.3 percent exceedence). Samples collected and analyzed for fungicides, herbicides, insecticides, and pesticides (4,062 samples), radiochemicals (1,628 samples), wastewater compounds (307 samples), and nutrients (20,822 samples) had the lowest exceedences of 0.3, 8.4, 0.0, and 8.8 percent, respectively.

Pennsylvania↗
USGS2006

Hurricane Rita surge data, southwestern Louisiana and southeastern Texas, September to November 2005

Pressure transducers and high-water marks were used to document the inland water levels related to storm surge generated by Hurricane Rita in southwestern Louisiana and southeastern Texas. On September 22-23, 2005, an experimental monitoring network consisting of 47 pressure transducers (sensors) was deployed at 33 sites over an area of about 4,000 square miles to record the timing, extent, and magnitude of inland hurricane storm surge and coastal flooding. Sensors were programmed to record date and time, temperature, and barometric or water pressure. Water pressure was corrected for changes in barometric pressure and salinity. Elevation surveys using global-positioning systems and differential levels were used to relate all storm-surge water-level data, reference marks, benchmarks, sensor measuring points, and high-water marks to the North American Vertical Datum of 1988 (NAVD 88). The resulting data indicated that storm-surge water levels over 14 feet above NAVD 88 occurred at three locations and rates of water-level rise greater than 5 feet per hour occurred at three locations near the Louisiana coast. Quality-assurance measures were used to assess the variability and accuracy of the water-level data recorded by the sensors. Water-level data from sensors were similar to data from co-located sensors, permanent U.S. Geological Survey streamgages, and water-surface elevations performed by field staff. Water-level data from sensors at selected locations were compared to corresponding high-water mark elevations. In general, the water-level data from sensors were similar to elevations of high quality high-water marks, while reporting consistently higher than elevations of lesser quality high-water marks.

Data Series↗
USGS2006

Land-Cover and Imperviousness Data for Regional Areas near Denver, Colorado; Dallas-Fort Worth, Texas; and Milwaukee-Green Bay, Wisconsin - 2001

This report describes the processing and results of land-cover and impervious surface derivation for parts of three metropolitan areas being studied as part of the U.S. Geological Survey's (USGS) National Water-Quality Assessment (NAWQA) Program Effects of Urbanization on Stream Ecosystems (EUSE). The data were derived primarily from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery from the period 1999-2002, and are provided as 30-meter resolution raster datasets. Data were produced to a standard consistent with data being produced as part of the USGS National Land Cover Database 2001 (NLCD01) Program, and were derived in cooperation with, and assistance from, NLCD01 personnel. The data were intended as surrogates for NLCD01 data because of the EUSE Program's time-critical need for updated land-cover for parts of the United States that would not be available in time from the NLCD01 Program. Six datasets are described in this report: separate land-cover (15-class categorical data) and imperviousness (0-100 percent continuous data) raster datasets for parts of the general Denver, Colorado area (South Platte River Basin), Dallas-Fort Worth, Texas area (Trinity River Basin), and Milwaukee-Green Bay, Wisconsin area (Western Lake Michigan Drainages).

Data Series↗
USGS2006

Compilation of historical water-quality data for selected springs in Texas, by ecoregion

Springs are important hydrologic features in Texas. A database of about 2,000 historically documented springs and available spring-flow measurements previously has been compiled and published, but water-quality data remain scattered in published sources. This report by the U.S. Geological Survey, in cooperation with the Texas Parks and Wildlife Department, documents the compilation of data for 232 springs in Texas on the basis of a set of criteria and the development of a water-quality database for the selected springs. The selection of springs for compilation of historical water-quality data in Texas was made using existing digital and hard-copy data, responses to mailed surveys, selection criteria established by various stakeholders, geographic information systems, and digital database queries. Most springs were selected by computing the highest mean spring flows for each Texas level III ecoregion. A brief assessment of the water-quality data for springs in Texas shows that few data are available in the Arizona/New Mexico Mountains, High Plains, East Central Texas Plains, Western Gulf Coastal Plain, and South Central Plains ecoregions. Water-quality data are more abundant for the Chihuahuan Deserts, Edwards Plateau, and Texas Blackland Prairies ecoregions. Selected constituent concentrations in Texas springs, including silica, calcium, magnesium, sodium, potassium, strontium, sulfate, chloride, fluoride, nitrate (nitrogen), dissolved solids, and hardness (as calcium carbonate) are comparatively high in the Chihuahuan Deserts, Southwestern Tablelands, Central Great Plains, and Cross Timbers ecoregions, mostly as a result of subsurface geology. Comparatively low concentrations of selected constituents in Texas springs are associated with the Arizona/New Mexico Mountains, Southern Texas Plains, East Central Texas Plains, and South Central Plains ecoregions.

Texas↗
USGS2009

Selected ground-water-quality data in Pennsylvania - 1979-2006

This study, by the U.S. Geological Survey (USGS) in cooperation with the Pennsylvania Department of Environmental Protection (PADEP), provides a compilation of ground-water-quality data for a 28-year period (January 1, 1979, through December 31, 2006) based on water samples from wells and springs. The data are from 14 source agencies or programs—Borough of Carroll Valley, Chester County Health Department, Montgomery County Health Department, Pennsylvania Department of Agriculture, Pennsylvania Department of Environmental Protection 2002 Pennsylvania Water-Quality Assessment, Pennsylvania Department of Environmental Protection Agency Act 537 Sewage Facilities Program, Pennsylvania Department of Environmental Protection-Ambient and Fixed Station Network, Pennsylvania Department of Environmental Protection–North-Central Region, Pennsylvania Department of Environmental Protection–South-Central Region, Pennsylvania Drinking Water Information System, Pennsylvania Topographic and Geologic Survey, Susquehanna River Basin Commission, U.S. Environmental Protection Agency, and the U.S. Geological Survey. The ground-water-quality data from the different source agencies or programs varied in type and number of analyses; however, the analyses are represented by 11 major analyte groups: antibiotics, major ions, microorganisms (bacteria, viruses, and other microorganisms), minor ions (including trace elements), nutrients (predominantly nitrate and nitrite as nitrogen), pesticides, pharmaceuticals, radiochemicals (predominantly radon or radium), volatiles (volatile organic compounds), wastewater compounds, and water characteristics (field measurements, predominantly field pH, field specific conductance, and hardness). For the USGS and the PADEP–North-Central Region, the pesticide analyte group was broken down into fungicides, herbicides, and insecticides. Summary maps show the areal distribution of wells and springs with ground-water-quality data statewide by source agency or program. Summary data tables by source agency or program provide information on the number of wells and springs and samples collected for each of the 35 watersheds and analyte groups. The number of wells and springs sampled for ground-water-quality data varies considerably across Pennsylvania. Of the 24,772 wells and springs sampled, the greatest concentration of wells and springs is in the southeast (Berks, Bucks, Chester, Delaware, Lancaster, Montgomery, and Philadelphia Counties) and in the northwest (Erie County). The number of wells and springs sampled is relatively sparse in north-central (Cameron, Elk, Forest, McKean, Potter, and Warren Counties) Pennsylvania. Little to no data are available for approximately one-fourth of the state. Nutrients and water characteristics were the most frequently sampled major analyte groups—43,025 and 30,583 samples, respectively. Minor ions and major ions were the next most frequently sampled major analyte groups–26,972 and 13,115 samples, respectively. For the remaining 10 major analyte groups, the number of samples collected ranged from a low of 24 samples (antibiotic compounds) to a high of approximately 4,674 samples (microorganisms). The number of samples that exceeded a maximum contaminant level (MCL) or secondary maximum contaminant level (SMCL) by major analyte group also varied. Of the 4,674 samples in the microorganism analyte group, 50.2 percent had water that exceeded an MCL. Of the 4,528 samples collected and analyzed for volatile organic compounds, 23.5 percent exceeded an MCL. Other major analyte groups that frequently exceeded MCLs or SMCLs included major ions (18,343 samples and a 27.7 percent exceedence), minor ions (26,972 samples, 44.7 percent exceedence), pesticides (4,868 samples, 0.7 percent exceedence), water characteristics (30,583 samples, 19.3 percent exceedence), and radiochemicals (1,866 samples, 9.6 percent exceedence). Samples collected and analyzed for antibiotics (24 samples), fungicides (1,273 samples), herbicides (1,470 samples), insecticides (1,424 samples), nutrients (43,025 samples), pharmaceuticals (28 samples), and wastewater compounds (328 samples) had the lowest exceedences of 0.0, 2.4, 1.2, <1.0, 8.3, 0.0, and <1.0 percent, respectively.

Pennsylvania↗
USGS2008

Archive of digitized analog boomer seismic reflection data collected from Lake Pontchartrain, Louisiana, to Mobile Bay, Alabama, during cruises onboard the R/V ERDA-1, June and August 1992

In June and August of 1992, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the shallow geologic framework from Lake Pontchartrain, Louisiana, to Mobile Bay, Alabama. This work was conducted onboard the Argonne National Laboratory's R/V ERDA-1 as part of the Mississippi/Alabama Pollution Project. This report is part of a series to digitally archive the legacy analog data collected from the Mississippi-Alabama SHelf (MASH). The MASH data rescue project is a cooperative effort by the USGS and the Minerals Management Service (MMS). A standardized naming convention was established to allow for better management of scanned trackline images within the MASH data rescue project. Each cruise received a unique field activity ID based on the year the data were collected, the first two digits of the survey vessel name, and the number of cruises made (to date) by that vessel that year (i.e. 92ER2 represents the second cruise made by the R/V ERDA-1 in 1992.) The new field activity IDs 92ER2 and 92ER4 presented in this report were originally referred to as ERDA 92-2 and ERDA 92-4 at the USGS in St. Petersburg, FL, and 92010 and 92037 at the USGS in Woods Hole, MA. A table showing the naming convention lineage for cruise IDs in the MASH data rescue series is included as a PDF. This report serves as an archive of high resolution scanned Tagged Image File Format (TIFF) and Graphics Interchange Format (GIF) images of the original boomer paper records, navigation files, trackline maps, Geographic Information System (GIS) files, cruise logs, and formal Federal Geographic Data Committee (FGDC) metadata for cruises 92ER2 and 92ER4. The boomer system uses an acoustic energy source called a plate, which consists of capacitors charged to a high voltage and discharged through a transducer in the water. The source is towed on a sled, at sea level, and when discharged emits a short acoustic pulse, or shot, which 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 hydrophone receiver, and the amplitude of the reflected energy is recorded by an Edward P. Curley Lab (EPC) thermal plotter. This process is repeated at timed intervals (for example, 0.5 s) and recorded for specific intervals of time (for example, 100 ms). The timed intervals are also referred to as the shot interval or fire rate. On analog records, the recorded interval is referred to as the sweep, which is the amount of time the recorder stylus takes to sweep from the top of the record to the bottom of the record, thereby recording the amplitude of the reflected energy of one shot. In this way, consecutive recorded shots produce a two-dimensional (2-D) vertical image of the shallow geologic structure beneath the ship track. Many of the geophysical data collected by the USGS prior to the late 1990s were recorded in analog format and stored as paper copies. Scientists onboard made hand-written annotations onto these records to note latitude and longitude, time, line number, course heading, and geographic points of reference. Each paper roll typically contained numerous survey lines and could reach more than 90 ft in length. All rolls are stored at the USGS FISC-St. Petersburg, FL. To preserve the integrity of these records and improve accessibility, analog holdings were converted to digital files.

Alabama, Louisiana, Mississippi↗