SEARCH · USGS Science

Results for “Information Systems”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49Linked to original sources

USGS2006

High-resolution geologic mapping of the inner continental shelf: Boston Harbor and approaches, Massachusetts

This report presents the surficial geologic framework data and information for the sea floor of Boston Harbor and Approaches, Massachusetts (fig. 1.1). This mapping was conducted as part of a cooperative program between the U.S. Geological Survey (USGS), the Massachusetts Office of Coastal Zone Management (CZM), and the National Oceanic and Atmospheric Administration (NOAA). The primary objective of this project was to provide sea floor geologic information and maps of Boston Harbor to aid resource management, scientific research, industry and the public. A secondary objective was to test the feasibility of using NOAA hydrographic survey data, normally collected to update navigation charts, to create maps of the sea floor suitable for geologic and habitat interpretations. Defining sea-floor geology is the first steps toward managing ocean resources and assessing environmental changes due to natural or human activity. The geophysical data for these maps were collected as part of hydrographic surveys carried out by NOAA in 2000 and 2001 (fig. 1.2). Bottom photographs, video, and samples of the sediments were collected in September 2004 to help in the interpretation of the geophysical data. Included in this report are high-resolution maps of the sea floor, at a scale of 1:25,000; the data used to create these maps in Geographic Information Systems (GIS) format; a GIS project; and a gallery of photographs of the sea floor. Companion maps of sea floor to the north Boston Harbor and Approaches are presented by Barnhardt and others (2006) and to the east by Butman and others (2003a,b,c). See Butman and others (2004) for a map of Massachusetts Bay at a scale of 1:125,000. The sections of this report are listed in the navigation bar along the left-hand margin of this page. Section 1 (this section) introduces the report. Section 2 presents the large-format map sheets. Section 3 describes data collection, processing, and analysis. Section 4 summarizes the geologic history of the region and discusses geomorphic and anthropogenic features within the study area. Section 4 also provides references that contain additional information about the region. Appendix 1 provides GIS layers of all the data collected in this study, Appendix 2 contains the grain size textural analyses of sediment samples, and Appendix 3 contains bottom photographs of the sea floor in JPG format.

Massaachusetts↗

USGS2008

Monitoring fine-grained sediment in the Colorado River ecosystem, Arizona — Control network and conventional survey techniques

In 2002, fine-grained sediment (sand, silt, and clay) monitoring in the Colorado River downstream from Glen Canyon Dam was initiated to survey channel topography at scales previously unobtainable in this canyon setting. This report presents the methods used to establish the high-resolution global positioning system (GPS) control network required for this effort as well as the conventional surveying techniques used in the study. Using simultaneous, dual-frequency GPS vector-based methods, the network points were determined to have positioning accuracies of less than 0.03 meters (m) and ellipsoidal height accuracies of between 0.01 and 0.10 m at a 95-percent degree of confidence. We also assessed network point quality with repeated, electronic (optical) total-station observations at 39 points for a total of 362 measurements; the mean range was 0.022 m in horizontal and 0.13 in vertical at a 95-percent confidence interval. These results indicate that the control network is of sufficient spatial and vertical accuracy for collection of airborne and subaerial remote-sensing technologies and integration of these data in a geographic information system on a repeatable basis without anomalies. The monitoring methods were employed in up to 11 discrete reaches over various time intervals. The reaches varied from 1.3 to 6.4 kilometers in length. Field results from surveys in 2000, 2002, and 2004 are described, during which conventional surveying was used to collect more than 3000 points per day. Ground points were used as checkpoints and to supplement areas just below or above the water surface, where remote-sensing data are not collected or are subject to greater error. An accuracy of +or- 0.05 m was identified as the minimum precision of individual ground points. These results are important for assessing digital elevation model (DEM) quality and identifying detection limits of significant change among surfaces generated from remote-sensing technologies.

Arizona↗

USGS2016

Geologic map of the Murray Quadrangle, Newton County, Arkansas

This map summarizes the geology of the Murray quadrangle in the Ozark Plateaus region of northern Arkansas. Geologically, the area is on the southern flank of the Ozark dome, an uplift that has the oldest rocks exposed at its center, in Missouri. Physiographically, the Murray quadrangle is within the Boston Mountains, a high plateau region underlain by Pennsylvanian sandstones and shales. Valleys of the Buffalo River and Little Buffalo River and their tributaries expose an approximately 1,600-ft-thick (488-meter-thick) sequence of Ordovician, Mississippian, and Pennsylvanian carbonate and clastic sedimentary rocks that have been mildly deformed by a series of faults and folds. The Buffalo National River, a park that encompasses the Buffalo River and adjacent land that is administered by the National Park Service is present at the northwestern edge of the quadrangle. Mapping for this study was carried out by field inspection of numerous sites and was compiled as a 1:24,000 geographic information system (GIS) database. Locations and elevation of sites were determined with the aid of a global positioning satellite receiver and a hand-held barometric altimeter that was frequently recalibrated at points of known elevation. Hill-shade relief and slope maps derived from a U.S. Geological Survey 10-meter digital elevation model as well as orthophotographs were used to help trace ledge-forming units between field traverses within the Upper Mississippian and Pennsylvanian part of the stratigraphic sequence. Strike and dip of beds were typically measured along stream drainages or at well-exposed ledges. Structure contours, constructed on the top of the Boone Formation and the base of a prominent sandstone unit within the Bloyd Formation, were drawn based on the elevations of field sites on these contacts well as other limiting information for their minimum elevations above hilltops or their maximum elevations below valley bottoms.

Arkansas↗

USGS2017

Water-quality data from an earthen dam site in southern Westchester County, New York, 2015

The U.S. Geological Survey, in cooperation with the New York City Department of Environmental Protection, sampled 37 sites in the reservoir area for nutrients, major ions, metals, pesticides and their degradates, volatile organic compounds, temperature, pH, and specific conductance during fall 2015. Data collection was done to characterize the local groundwater-flow system and identify potential sources of seeps from the southern embankment at the Hillview Reservoir. Water-quality samples were collected in accordance with standard U.S. Geological Survey methods at 37 sites in and adjacent to Hillview Reservoir. These 37 sites were sampled to determine (1) baseline water-quality conditions of the saturated, low-permeability sediments that compose the earthen embankment that surrounds the reservoir, (2) water-quality conditions in the southwestern part of the study area in relation to the seeps on the embankment, and (3) temporal variation of water-quality conditions between 2006 and 2015 (not included in this report). The physical parameters and the results of the water-quality analysis from the 37 sites are included in this report and can be downloaded from the U.S. Geological Survey National Water Information System website.

New York↗

USGS1997

National Geochemical Database: Reformatted data from the National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) program

The National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) program produced a large amount of geochemical data. To fully understand how these data were generated, it is recommended that you read the History of NURE HSSR Program for a summary of the entire program. By the time the NURE program had ended, the HSSR data consisted of 894 separate data files stored with 47 different formats. Many files contained duplication of data found in other files. The University of Oklahoma's Information Systems Programs of the Energy Resources Institute (ISP) was contracted by the Department of Energy to enhance the accessibility and usefulness of the NURE HSSR data. ISP created a single standard-format master file to replace the 894 original files. ISP converted 817 of the 894 original files before its funding apparently ran out. The ISP-reformatted NURE data files have been released by the USGS on CD-ROM (Lower 48 States, Hoffman and Buttleman, 1994; Alaska, Hoffman and Buttleman, 1996). A description of each NURE database field, derived from a draft NURE HSSR data format manual (unpubl. commun., Stan Moll, ISP, Oct 7, 1988), was included in a readme file on each CD-ROM. That original manual was incomplete and assumed that the reformatting process had gone to completion. A lot of vital information was not included. Efforts to correct that manual and the NURE data revealed a large number of problems and missing data. As a result of the frustrating process of cleaning and re-cleaning data from the ISP-reformatted NURE files, a new NURE HSSR data format was developed. This work represents a totally new attempt to reformat the original NURE files into 2 consistent database structures; one for water samples and a second for sediment samples, on a quadrangle by quadrangle basis, from the original NURE files. Although this USGS-reformatted NURE HSSR data format is different than that created by the ISP, many of their ideas were incorporated and expanded in this effort. All of the data from each quadrangle are being examined thoroughly in an attempt to eliminate problems, to combine partial or duplicate records, to convert all coding to a common scheme, and to identify problems even if they can not be solved at this time.

Open-File Report↗

USGS2010

Simulation of Runoff and Reservoir Inflow for Use in a Flood-Analysis Model for the Delaware River, Pennsylvania, New Jersey, and New York, 2004-2006

A model was developed to simulate inflow to reservoirs and watershed runoff to streams during three high-flow events between September 2004 and June 2006 for the main-stem subbasin of the Delaware River draining to Trenton, N.J. The model software is a modified version of the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The PRMS model simulates time periods associated with main-stem flooding that occurred in September 2004, April 2005, and June 2006 and uses both daily and hourly time steps. Output from the PRMS model was formatted for use as inflows to a separately documented reservoir and riverrouting model, the HEC-ResSim model, developed by the U.S. Army Corps of Engineers Hydrologic Engineering Center to evaluate flooding. The models were integrated through a graphical user interface. The study area is the 6,780 square-mile watershed of the Delaware River in the states of Pennsylvania, New Jersey, and New York that drains to Trenton, N.J. A geospatial database was created for use with a geographic information system to assist model discretization, determine land-surface characterization, and estimate model parameters. The USGS National Elevation Dataset at 100-meter resolution, a Digital Elevation Model (DEM), was used for model discretization into streams and hydrologic response units. In addition, geospatial processing was used to estimate initial model parameters from the DEM and other data layers, including land use. The model discretization represents the study area using 869 hydrologic response units and 452 stream segments. The model climate data for point stations were obtained from multiple sources. These sources included daily data for 22 National Weather Service (NWS) Cooperative Climate Station network stations, hourly data for 15 stations from the National Climatic Data Center, hourly data for 1 station from the NWS Middle Atlantic River Forecast Center records, and daily and hourly data for 7 stations operated by the New York City Department of Environmental Protection. The NWS Multisensor Precipitation Estimate data set for 2001-2007 was used for computing daily precipitation for the model and for computing hourly precipitation for storm simulation periods. Calibration of the PRMS model included regression and optimization algorithms, as well as manual adjustments of model parameters. The general goal of the calibration procedure was to minimize the difference between discharge measured at USGS streamgages and the corresponding discharge simulated by the model. Daily streamflow data from 35 USGS streamgages were used in model calibration. The streamflow data represent areas draining from 20.2 to 6,780 square miles. The PRMS model simulates reservoir inflow and watershed runoff for use as input into HECResSim for the purpose of evaluating and comparing the effects of different watershed conditions on main-stem flooding in the Delaware River watershed draining to Trenton, N.J. The PRMS model is useful as a planning tool to simulate the effects of land-use changes and different antecedent conditions on local runoff and reservoir inflow and, as input to the HEC-ResSim model, on flood flows in the main stem of the Delaware River.

Open-File Report↗

USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗

USGS2017

Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015

Introduction The Floridan aquifer system (FAS) consists of the Upper Floridan aquifer (UFA), an intervening confining unit of highly variable properties, and the Lower Floridan aquifer (LFA). The UFA and LFA are primarily composed of Paleocene- to Oligocene-age carbonate rocks that include, locally, Upper Cretaceous rocks. The FAS extends from coastal areas in southeastern South Carolina and continues southward and westward across the coastal plain of Georgia and Alabama, and underlies all of Florida. The thickness of the FAS varies from less than 100 feet (ft) in aquifer outcrop areas of South Carolina to about 1,700 ft near the city of Brunswick, Georgia. Locally, in southeastern Georgia and the Brunswick– Glynn County area, the UFA consists of an upper water-bearing zone (UWBZ) and a lower water-bearing zone (LWBZ), as identified by Wait and Gregg (1973), with aquifer test data indicating the upper zone has higher productivity than the lower zone. Near the city of Brunswick, the LFA is composed of two permeable zones: an early middle Eocene-age upper permeable zone (UPZ) and a highly permeable lower zone of limestone (LPZ) of Paleocene and Late Cretaceous age that includes a deeply buried, cavernous, saline water-bearing unit known as the Fernandina permeable zone. Maslia and Prowell (1990) inferred the presence of major northeast–southwest trending faults through the downtown Brunswick area based on structural analysis of geophysical data, northeastward elongation of the potentiometric surface of the UFA, and breaches in the local confining unit that influence the area of chloride contamination. Pronounced horizontal and vertical hydraulic head gradients, caused by pumping in the UFA, allow saline water from the FPZ to migrate upward into the UFA through this system of faults and conduits. Saltwater was first detected in the FAS in wells completed in the UFA near the southern part of the city of Brunswick in late 1957. By the 1970s, a plume of groundwater with high chloride concentrations had migrated northward toward two major industrial pumping centers, and since 1965, chloride concentrations have steadily increased in the northern part of the city. In 1978, data obtained from a 2,720-ft-deep test well (33H188) drilled south of the city showed water with a chloride concentration of 33,000 milligrams per liter (mg/L), suggesting the saltwater source was located below the UFA in the Fernandina permeable zone (FPZ) of the LFA. All U.S. Geological Survey (USGS) data collected for this study, including groundwater levels in wells and water-chemistry data, are available in the USGS National Water Information System.

Georgia↗

USGS2010

Vegetation classification and distribution mapping report: Canyon de Chelly National Monument

Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.

Report↗

USGS1994

Ecological perspective: Linking ecology, GIS, and remote sensing to ecosystem management

Awareness of significant human impacts on the ecology of Earth's landscapes is not new (Thomas 1956). Over the past decade (Forman and Godron 1986, Urban et a1. 1987) applications of geographic information systems (GIS) and remote sensing technologies have supported a rapid rise in landscape.stale research. The heightened recognition within the research community of the ecological linkages between local sites and larger spatial scales has spawned increasing calls for more holistic management of landscapes (Noss 1983, Harris 1984, Risser 1985, Norse et al. 1986, Agee and Johnson 1988, Franklin 1989, Brooks and Grant 1992, Endangered Species Update-Special Issue 1993, Crow 1994, Grumbine 1994). As a result agencies such as the U.S. Forest Service, U.S. Fish and Wildlife Service, and National Park Service are now converging on "ecosystem management" as a new paradigm to sustainably manage wildlands and maintain biodiversity. However, as this transition occurs, several impediments to implementation of this new paradigm persist, including (1) significant uncenainty among many land managers about the definition and goals of ecosystem management, (2) inadequate ecological information on the past and present processes and structural conditions of target ecosystems, (3) insufficient experience on the part of land managers with the rapidly diversifying array of GIS and remote sensing tools to effectively use them to support ecology-based land management, and (4) a paucity of intimate, long-term relationships between people (including land managers) and the particular landscape communities to which they belong. This chapter provides an ecological perspective on these issues as applied to ecosystem management in a southwestern U.S. landscape.

Book chapter↗

USGS2006

Hydrogeologic framework refinement, ground-water flow and storage, water-chemistry analyses, and water-budget components of the Yuma area, southwestern Arizona and southeastern California

The ground-water and surface-water system in the Yuma area in southwestern Arizona and southeastern California is managed intensely to meet water-delivery requirements of customers in the United States, to manage high ground-water levels in the valleys, and to maintain treaty-mandated water-quality and quantity requirements of Mexico. The following components in this report, which were identified to be useful in the development of a ground-water management model, are: (1) refinement of the hydrogeologic framework; (2) updated water-level maps, general ground-water flow patterns, and an estimate of the amount of ground water stored in the mound under Yuma Mesa; (3) review and documentation of the ground-water budget calculated by the Bureau of Reclamation, U.S. Department of the Interior (Reclamation); and (4) water-chemistry characterization to identify the spatial distribution of water quality, information on sources and ages of ground water, and information about the productive-interval depths of the aquifer. A refined three-dimensional digital hydrogeologic framework model includes the following hydrogeologic units from bottom to top: (1) the effective hydrologic basement of the basin aquifer, which includes the Pliocene Bouse Formation, Tertiary volcanic and sedimentary rocks, and pre-Tertiary metamorphic and plutonic rocks; (2) undifferentiated lower units to represent the Pliocene transition zone and wedge zone; (3) coarse-gravel unit; (4) lower, middle, and upper basin fill to represent the upper, fine-grained zone between the top of the coarse-gravel unit and the land surface; and (5) clay A and clay B. Data for the refined model includes digital elevation models, borehole lithology data, geophysical data, and structural data to represent the geometry of the hydrogeologic units. The top surface of the coarse-gravel unit, defined by using borehole and geophysical data, varies similarly to terraces resulting from the down cutting of the Colorado River. Clay A is nearly the same as the previous conceptual hydrogeologic model definition (Olmsted and others, 1973), except for a minor westward extension from the city of Yuma. Clay B is extended to the southerly international boundary and increased in areal extent by about two-thirds of the original extent (Olmsted and others, 1973). The other hydrogeologic units generally are the same as in the previous conceptual hydrogeologic model. Before development, the Colorado and Gila Rivers were the sources of nearly all the ground water in the Yuma area through direct infiltration of water from river channels and annual overbank flooding. After construction of upstream reservoirs and clearing and irrigation of the floodplains, the rivers now act as drains for the ground water. Ground-water levels in most of the Yuma area are higher now than they were in predevelopment time. A general gradient of ground-water flow toward the natural discharge area south of the Yuma area still exists, but many other changes in flow are evident. Ground water in Yuma Valley once flowed away from the Colorado River, but now has a component of flow towards the river and Mexicali Valley. A ground-water mound has formed under Yuma Mesa from long-term surface-water irrigation; about 600,000 to 800,000 acre-ft of water are stored in the mound. Ground-water withdrawals adjacent to the southerly international boundary have resulted in water-level declines in that area. The reviewed and documented water budget includes the following components: (1) recharge in irrigated areas, (2) evapotranspiration by irrigated crops and phreatophytes, (3) ground-water return flow to the Colorado River, and (4) ground-water withdrawals (including those in Mexicali Valley). Recharge components were calculated by subtracting the amount of water used by crops from the amount of water delivered. Evapotranspiration rates were calculated on the basis of established methods, thus were appropriate for input to the ground-water flow model developed by the Bureau of Reclamation (William Greer, hydrologist, Bureau of Reclamation, written commun., 2005). Evapotranspiration by crops and phreatophytes were calculated by using crop coefficient methods and meteorological data. Other methods of calculating evapotranspiration rates by using combinations of satellite imagery and ground-based data could be used for higher spatial and temporal resolution. Ground-water return flow during years of low flow on the Colorado River (1972–82, 1987–92, and 1994–96) averaged 79,000 acre-ft per year. Ground-water withdrawal data for 1970–99 were similar to other estimates made by the U.S. Geological Survey for the Yuma area. New water-chemistry data were collected in 12 wells and 8 canals/drains to characterize spatial patterns in chemical constituents, determine isotopic ages of water, infer possible sources of ground water, and locate the vertical intervals of the aquifer that contribute most water to wells. Depth-dependent samples were collected at one of the wells (YM-10). A large quantity of water-quality data were compiled from Bureau of Reclamation and U.S. Geological Survey records and merged into the U.S. Geological Survey National Water Information System database. New samples were analyzed for major ions, nutrients, stable isotopes of oxygen and hydrogen, tritium ( 3 H), and carbon-14 ( 14 C) (along with C 13 /C 12 ratios). Light values of oxygen-18 ( 18 O) and deuterium ( 2 H, D) in well 242-2 indicate recharge from the Colorado River. Heavy water samples from wells 242-22, CADC, and Mesa del Sol indicate local recharge sources. Tritium data indicate there is young water in wells in the valleys and near the edge of Yuma Mesa, while older water is found far from the Colorado River. 14 C data indicate that water from wells near the southerly international boundary is at least several thousand years old.

Arizona, California↗

USGS2014

Metadata Wizard: an easy-to-use tool for creating FGDC-CSDGM metadata for geospatial datasets in ESRI ArcGIS Desktop

Creating compliant metadata for scientific data products is mandated for all federal Geographic Information Systems professionals and is a best practice for members of the geospatial data community. However, the complexity of the The Federal Geographic Data Committee’s Content Standards for Digital Geospatial Metadata, the limited availability of easy-to-use tools, and recent changes in the ESRI software environment continue to make metadata creation a challenge. Staff at the U.S. Geological Survey Fort Collins Science Center have developed a Python toolbox for ESRI ArcDesktop to facilitate a semi-automated workflow to create and update metadata records in ESRI’s 10.x software. The U.S. Geological Survey Metadata Wizard tool automatically populates several metadata elements: the spatial reference, spatial extent, geospatial presentation format, vector feature count or raster column/row count, native system/processing environment, and the metadata creation date. Once the software auto-populates these elements, users can easily add attribute definitions and other relevant information in a simple Graphical User Interface. The tool, which offers a simple design free of esoteric metadata language, has the potential to save many government and non-government organizations a significant amount of time and costs by facilitating the development of The Federal Geographic Data Committee’s Content Standards for Digital Geospatial Metadata compliant metadata for ESRI software users. A working version of the tool is now available for ESRI ArcDesktop, version 10.0, 10.1, and 10.2 (downloadable at http:/www.sciencebase.gov/metadatawizard ).

Open-File Report↗

USGS1994

Permeability of soils in Mississippi

The permeability of soils in Mississippi was determined and mapped using a geographic information system (GIS). Soil permeabilities in Mississippi were determined to range in value from nearly 0.0 to values exceeding 5.0 inches per hour. The U.S. Soil Conservation Service's State Soil Geographic Data Base (STATSGO) was used as the primary source of data for the determination of area-weighted soil permeability. STATSGO provides soil layer properties that are spatially referenced to mapped areas. These mapped areas are referred to as polygons in the GIS. The polygons arc boundaries of soils mapped as a group and are given unique Map Unit Identifiers (MUIDs). The data describing the physical characteristics of the soils within each polygon are stored in a tabular data base format and are referred to as attributes. The U.S. Soil Conservation Service developed STATSGO to be primarily used as a guide for regional resource planning, management, and monitoring. STATSGO was designed so that soil information could be extracted from properties tables at the layer level, combined by component, and statistically expanded to cover the entire map unit. The results of this study provide a mapped value for permeability which is representative of the vertical permeability of soils in that area. The resultant permeability map provides a representative vertical soil permeability for a given area sufficient for county, multi- county, and area planning, and will be used as the soil permeability data component in the evaluation of the susceptibility of major aquifers to contami- nation in Mississippi.

Water-Resources Investigations Report↗

USGS2009

Geologic map of the St. Joe quadrangle, Searcy and Marion Counties, Arkansas

This map summarizes the geology of the St. Joe 7.5-minute quadrangle in the Ozark Plateaus region of northern Arkansas. Geologically, the area lies on the southern flank of the Ozark dome, an uplift that exposes oldest rocks at its center in Missouri. Physiographically, the St. Joe quadrangle lies within the Springfield Plateau, a topographic surface generally held up by Mississippian cherty limestone. The quadrangle also contains isolated mountains (for example, Pilot Mountain) capped by Pennsylvanian rocks that are erosional outliers of the higher Boston Mountains plateau to the south. Tomahawk Creek, a tributary of the Buffalo River, flows through the eastern part of the map area, enhancing bedrock erosion. Exposed bedrock of this region comprises an approximately 1,300-ft-thick sequence of Ordovician, Mississippian, and Pennsylvanian carbonate and clastic sedimentary rocks that have been mildly deformed by a series of faults and folds. The geology of the St. Joe quadrangle was mapped by McKnight (1935) as part of a larger area at 1:125,000 scale. The current map confirms many features of this previous study, but it also identifies new structures and uses a revised stratigraphy. Mapping for this study was conducted by field inspection of numerous sites and was compiled as a 1:24,000-scale geographic information system (GIS) database. Locations and elevations of sites were determined with the aid of a global positioning satellite receiver and a hand-held barometric altimeter that was frequently recalibrated at points of known elevation. Hill-shade-relief and slope maps derived from a U.S. Geological Survey 10-m digital elevation model as well as U.S. Geological Survey orthophotographs from 2000 were used to help trace ledge-forming units between field traverses within the Upper Mississippian and Pennsylvanian part of the stratigraphic sequence. Strikes and dips of beds were typically measured along stream drainages or at well-exposed ledges. Beds dipping less than 2 degrees are shown as horizontal. Structure contours constructed on the base of the Boone Formation were hand drawn based on elevations of control points on both lower and upper contacts of the Boone Formation as well as other limiting information on their maximum or minimum elevations.

Scientific Investigations Map↗

USGS2023

User’s Guide to planetary image analysis and geologic mapping in ArcGIS Pro

Geologic maps are valuable tools in planetary science. Though planetary geologic maps are similar to terrestrial (Earthbased) geologic maps, the nature of planetary exploration introduces unique challenges for geologic mappers. Terrestrial geologic mappers prepare products from field-based observation, often comparing or refining those with aerial and (or) orbital images. Planetary geologic mapping relies almost exclusively on remote observations, which are made by orbiting spacecraft. Therefore, with a few exceptions for locations with rovers, landers, or crewed surface missions, planetary geologic mappers are not able to observe their map area in detail or at smaller scales. As a result, they must interpret and describe their map features differently than those used in terrestrial geologic maps. For example, terrestrial geologic mappers commonly divide units by lithology (rock type) or grain size. However, planetary geologic mappers often do not have detailed enough information to know what type of rock or grain size is present, and instead must divide the planet’s surface into geologic units using differences in tone, color, and surface texture (at multiple scales). Cross-cutting relationships, where apparent, can provide excellent—and often crucial—observations for identifying and subdividing geologic units using orbital datasets. The process of creating planetary maps has evolved over time, from original hand-drawn maps created during the early 1800s through the late 1900s, to the fully digital products created today. Modern-day planetary geologic mapping uses Geographic Information Systems (GIS) software and tools to visualize data, delineate units and landforms, and accurately convey spatial relationships to a map user using cartographic features represented by points, lines, and polygons. This tutorial was written to familiarize both new and experienced planetary geologic mappers with ArcGIS Pro, a commonly used GIS software package developed by Esri. This tutorial introduces new planetary geologic mappers to fundamental concepts and best practices in planetary geologic mapping. For mappers with experience using ArcMap (a previous version of ArcGIS), this tutorial will help to familiarize users with new changes in layout and functionality, so current projects may be migrated into the ArcGIS Pro environment. No prior knowledge is required, although a general familiarity with geology, GIS, and planetary science is recommended. This tutorial includes links to helpful glossaries of common GIS terms and other GIS and planetary science resources in appendix 1. For additional information on planetary geologic mapping, see the U.S Geological Survey (USGS) Astrogeology NASA Planetary Geologic Mapping Program website and the Planetary Mapping Guidelines. Numerous ArcGIS tutorials are also available from Esri’s Tutorials page, through the Esri Academy catalog, and Esri’s ArcGIS Pro Resources page.

Techniques and Methods↗

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↗

USGS2015

California State Waters Map Series — Offshore of Point Reyes, California

This publication about the Offshore of Point Reyes map area includes ten map sheets that contain explanatory text, in addition to this descriptive pamphlet and a data catalog of geographic information system (GIS) files. Sheets 1, 2, and 3 combine data from four different sonar surveys to generate comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic features (highlighted in the perspective views on sheet 4) such as the flat, sediment-covered seafloor in Drakes Bay, as well as abundant “scour depressions” on the Bodega Head–Tomales Point shelf (see sheet 9) and local, tectonically controlled bedrock uplifts. To validate geological and biological interpretations of the sonar data shown in sheets 1, 2, and 3, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are summarized on sheet 6. Sheet 5 is a “seafloor character” map, which classifies the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. Sheet 7 is a map of “potential habitats,” which are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Sheet 8 compiles representative seismic-reflection profiles from the map area, providing information on the subsurface stratigraphy and structure of the map area. Sheet 9 shows the distribution and thickness of young sediment (deposited over the last about 21,000 years, during the most recent sea-level rise) in both the map area and the larger Salt Point to Drakes Bay region, interpreted on the basis of the seismic-reflection data, and it identifies the Offshore of Point Reyes map area as lying within the Bodega Head–Tomales Point shelf, Point Reyes bar, and Bolinas shelf domains. Sheet 10 is a geologic map that merges onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery (sheets 1, 2, 3), seafloor-sediment and rock samples (Reid and others, 2006), digital camera and video imagery (sheet 6), and high-resolution seismic-reflection profiles (sheet 8), as well as aerial-photographic interpretation of nearshore areas. The information provided by the map sheets, pamphlet, and data catalog have a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues.

California↗

USGS2014

Assessing potential effects of highway runoff on receiving-water quality at selected sites in Oregon with the Stochastic Empirical Loading and Dilution Model (SELDM)

In 2012, the U.S. Geological Survey and the Oregon Department of Transportation began a cooperative study to demonstrate use of the Stochastic Empirical Loading and Dilution Model (SELDM) for runoff-quality analyses in Oregon. SELDM can be used to estimate stormflows, constituent concentrations, and loads from the area upstream of a stormflow discharge site, from the site of interest and in the receiving waters downstream of the discharge. SELDM also can be used to assess the potential effectiveness of best management practices (BMP) for mitigating potential effects of runoff in receiving waters. Nominally, SELDM is a highway-runoff model, but it is well suited for analysis of runoff from other land uses as well. This report provides case studies and examples to demonstrate stochastic-runoff modeling concepts and to demonstrate application of the model. Basin characteristics from six Oregon highway study sites were used to demonstrate various applications of the model. The highway catchment and upstream basin drainage areas of these study sites ranged from 3.85 to 11.83 acres and from 0.16 to 6.56 square miles, respectively. The upstream basins of two sites are urbanized, and the remaining four sites are less than 5 percent impervious. SELDM facilitates analysis by providing precipitation, pre-storm streamflow, and other variables by region or from hydrologically similar sites. In Oregon, there can be large variations in precipitation and streamflow among nearby sites. Therefore, spatially interpolated geographic information system data layers containing storm-event precipitation and pre-storm streamflow statistics specific to Oregon were created for the study using Kriging techniques. Concentrations and loads of cadmium, chloride, chromium, copper, iron, lead, nickel, phosphorus, and zinc were simulated at the six Oregon highway study sites by using statistics from sites in other areas of the country. Water‑quality datasets measured at hydrologically similar basins in the vicinity of the study sites in Oregon were selected and compiled to estimate stormflow-quality statistics for the upstream basins. The quality of highway runoff and some upstream stormflow constituents were simulated by using statistical moments (average, standard deviation, and skew) of the logarithms of data. Some upstream stormflow constituents were simulated by using transport curves, which are relations between stormflow and constituent concentrations. Stochastic analyses were done by using SELDM to demonstrate use of the model and to illustrate the types of information that stochastic analyses may provide: 1. An analysis was done to demonstrate use of dilution factors as an initial reconnaissance tool for comparing relative risk among sites. 2. An analysis of hardness-dependent, water-quality criteria was done to illustrate the effects of variations in hardness and flow on the application and interpretation of such criteria. This analysis shows that hardness-dependent criteria can vary by an order of magnitude among storm events because hardness is diluted by stormflows. 3. An analysis of uncertainties in input and output values was done to demonstrate that properly selected robust datasets are needed to represent conditions at a site of interest. This analysis shows that the rate of water-quality exceedances that are measured or simulated may depend on sample size and the luck of the draw. 4. An analysis was done to demonstrate that SELDM and other Monte Carlo models may generate extreme values from input statistics, which may or may not be feasible based on physicochemical or hydrological limits. 5. An analysis of BMP modeling methods was done to demonstrate use of the model for estimating treatment requirements for meeting water-quality objectives. 6. An analysis of the use of grab sampling and nonstochastic upstream modeling methods was done to evaluate the potential effects on modeling outcomes. Additional analyses using surrogate water-quality datasets for the upstream basin and highway catchment were provided for six Oregon study sites to illustrate the risk-based information that SELDM will produce. These analyses show that the potential effects of highway runoff on receiving-water quality downstream of the outfall depends on the ratio of drainage areas (dilution), the quality of the receiving water upstream of the highway, and the concentration of the criteria of the constituent of interest. These analyses also show that the probability of exceeding a water-quality criterion may depend on the input statistics used, thus careful selection of representative values is important.

Oregon↗