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At least 1,261 records · Page 70Linked to original sources
USGS2021

Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019

Digital flood-inundation maps for a 4.6-mile reach of the Blue River near Red Bridge Road in Kansas City, Missouri, were created by the U.S. Geological Survey (USGS), in cooperation with the City of Kansas City, Missouri. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 06893195, Blue River at Red Bridge Road, Kansas City, Mo. Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the Johnson County, Kansas, StormWatch Automated Local Elevation in Real Time Flood Warning System at https://www.stormwatch.com . Flood profiles were computed for the Blue River reach by means of a one-dimensional model for simulating water-surface profiles with steady-state flow computations. The model was calibrated by using the current stage-streamflow relations at the upstream USGS streamgage 06893150, Blue River at Blue Ridge Boulevard Extension, Kansas City, Mo., and the downstream streamgage 06893500, Blue River at Kansas City, Mo. The hydraulic model was then used to compute 37 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 11 ft, or near bankfull, to 47 ft at the reference streamgage 06893195. The upper stage for the map library exceeds the stage corresponding to the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood) in the model reach. The simulated water-surface profiles were then combined with a geographic information system digital elevation model with a maximum 10-centimeter vertical root mean square error and 4.0-ft horizontal resolution to delineate the area flooded at each water level. The availability of these maps, along with real-time internet information regarding current stage from the USGS streamgage, will help guide emergency management personnel and residents in flood mitigation, preparedness and planning, flood-response activities such as evacuations and road closures, and any postflood recovery efforts.

Kansas, Missouri↗
USGS2002

Sea otter studies in Glacier Bay National Park and Preserve

Following translocations to the outer coast of Southeast Alaska in 1965, sea otters have been expanding their range and increasing in abundance. We began conducting surveys for sea otters in Cross Sound, Icy Strait, and Glacier Bay, Alaska in 1994, following initial reports (in 1993) of their presence in Glacier Bay. Since 1995, the number of sea otters in Glacier Bay proper has increased from around 5 to more than 1500. Between 1993 and 1997 sea otters were apparently only occasional visitors to Glacier Bay, but in 1998 long-term residence was established as indicated by the presence of adult females and their dependent pups. Sea otter distribution is limited to the Lower Bay, south of Sandy Cove, and is not continuous within that area. Concentrations occur in the vicinity of Sita Reef and Boulder Island and between Pt. Carolus and Rush Pt. on the west side of the Bay (Figure 1). We describe the diet of sea otters during 2001 in Glacier Bay based on visual observations of prey during 456 successful forage dives. In Glacier Bay, diet consisted of 62% clam, 15% mussel, 9% crab, 7% unidentified, 4& urchins, and 4% other. Most prey recovered by sea otters are commercially, socially, or ecologically important species. Species of clam include Saxidomus gigantea, Protothaca staminea, and Mya truncata. Urchins are primarily Strongylocentrotus droebachiensis and the mussel is Modiolus modiolus. Crabs include species of three genera: Cancer, Chinoecetes, and Telmessus. Although we characterize diet at broad geographic scales, we found diet to vary between sites separated by as little as several hundred meters. Dietary variation among and within sites can reflect differences in prey availability and individual specialization. We estimated species composition, density, biomass, and sizes of subtidal clams, urchins, and mussels at 9 sites in lower Glacier Bay. All sites were selected based on the presence of abundant clam siphons. Sites were not selected to allow inference to any area larger than the sampling area (approx 400 m^2). Sites were selected to achieve a broad geographic sample of dense subtidal clam beds within Glacier Bay prior to occupation and foraging by sea otters. There was no direct evidence of otter foraging at any of our clam sampling sites. We sampled 11,568 bivalves representing 14 speces of clam and 2 species of mussel. We sampled 4,981 urchins, all Strongylocentrotus droeobachiensis. Only four species of clam (littleneck clams, Protothaca staminea; butter clams, Saxidomus gigantea; soft-shell claims, Mya truncata; and Macoma sp.) accounted for 91.6% of all clams sampled. Mean total clam density (#/0.25 m^2) across the 9 sites was 62.3. Densities (and se ) of P. staminea averaged 22.6 (1.6) and ranged from 0 to 97. Densities of S. gigantea averaged 14.4 (1.0) and ranged from 0 to 63. Densities of Macoma sp. averaged 14.5 (1.2) and ranged from 0 to 78. Densities of S. droebachiensis averaged 27.3 (1.7) and ranged from 0 to 109. Mean S. droebachiensis sizes ranged from 16 to 30 mm by site. Mean P. staminea sizes ranged from 30 to 53 mm, mean S. gigantea sizes ranged from 51 to 85 mm, and mean Macoma sp. sizes ranged from 14 to 19 mm. Although not the most abundant clam, S. gigantea contributed the greatest proportion to total clam biomass (63%), followed by P. staminea (24%). Sea otters are now well established in limited areas of the lower portions of Glacier Bay. It is likely that distribution and numbers of sea otters will continue to increase in Glacier Bay in the near future. Glacier Bay supports large and diverse populations of clams that are largely unexploited by sea otters presently. It is predictable that the density and sizes of clam populations will decline in response to otter predation. This will result in fewer opportunities for human harvest, but will also trigger ecosystem level changes, as prey for other predators, such as octopus, sea stars, fishes, birds and mammals are modified. Sea ott

Annual Report↗
USGS2012

Archive of single-beam bathymetry data collected during USGS cruise 07CCT01 nearshore of Fort Massachusetts and within Camille Cut, West and East Ship Islands, Gulf Islands National Seashore, Mississippi, July 2007

The Gulf Islands National Seashore (GUIS) is composed of a series of barrier islands along the Mississippi - Alabama coastline. Historically these islands have undergone long-term shoreline change. The devastation of Hurricane Katrina in 2005 prompted questions about the stability of the barrier islands and their potential response to future storm impacts. Additionally, there was concern from the National Park Service (NPS) about the preservation of the historical Fort Massachusetts, located on West Ship Island. During the early 1900s, Ship Island was an individual island. In 1969 Hurricane Camille breached Ship Island, widening the cut and splitting it into what is now known as West Ship Island and East Ship Island. In July of 2007, the U.S. Geological Survey (USGS) was able to provide the NPS with a small bathymetric survey of Camille Cut using high-resolution single-beam bathymetry. This provided GUIS with a post-Katrina assessment of the bathymetry in Camille Cut and along the northern shoreline directly in front of Fort Massachusetts. Ultimately, this survey became an initial bathymetry dataset toward a larger USGS effort included in the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project ( http://ngom.usgs.gov/gomsc/mscip/ ). This report serves as an archive of the processed single-beam bathymetry. Data products herein include gridded and interpolated digital depth surfaces and x,y,z data products. Additional files include trackline maps, navigation files, geographic information system (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Scanned images of the handwritten FACS logs and digital FACS logs are also provided as PDF files. Refer to the Acronyms page for description of acronyms and abbreviations used in this report or hold the cursor over an acronym for a pop-up explanation. The USGS St. Petersburg Coastal and Marine Science Center assigns a unique identifier to each cruise or field activity. For example, 07CCT01 tells us the data were collected in 2007 for the Coastal Change and Transport (CCT) study and the data were collected during the first (01) field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. Data were collected using a 26-foot (ft) Glacier Bay catamaran. The single-beam transducers were sled mounted on a rail attached between the catamaran hulls. Navigation was acquired using HYPACK, Inc., Hypack version 4.3a.7.1 and differentially corrected using land-based GPS stations. See the digital FACS equipment log for details about the acquisition equipment used. Raw datasets were stored digitally and processed systematically using NovAtel's Waypoint GrafNav version 7.6, SANDS version 3.7, and ESRI ArcGIS version 9.3.1. For more information on processing refer to the Equipment and Processing page.

Mississippi↗
USGS2013

Estimates of future inundation of salt marshes in response to sea-level rise in and around Acadia National Park, Maine

Salt marshes are ecosystems that provide many important ecological functions in the Gulf of Maine. The U.S. Geological Survey investigated salt marshes in and around Acadia National Park from Penobscot Bay to the Schoodic Peninsula to map the potential for landward migration of marshes using a static inundation model of a sea-level rise scenario of 60 centimeters (cm; 2 feet). The resulting inundation contours can be used by resource managers to proactively adapt to sea-level rise by identifying and targeting low-lying coastal areas adjacent to salt marshes for conservation or further investigation, and to identify risks to infrastructure in the coastal zone. For this study, the mapping of static inundation was based on digital elevation models derived from light detection and ranging (LiDAR) topographic data collected in October 2010. Land-surveyed control points were used to evaluate the accuracy of the LiDAR data in the study area, yielding a root mean square error of 11.3 cm. An independent accuracy assessment of the LiDAR data specific to salt-marsh land surfaces indicated a root mean square error of 13.3 cm and 95-percent confidence interval of ± 26.0 cm. LiDAR-derived digital elevation models and digital color aerial photography, taken during low tide conditions in 2008, with a pixel resolution of 0.5 meters, were used to identify the highest elevation of the land surface at each salt marsh in the study area. Inundation contours for 60-cm of sea-level rise were delineated above the highest marsh elevation for each marsh. Confidence interval contours (95-percent,± 26.0 cm) were delineated above and below the 60-cm inundation contours, and artificial structures, such as roads and bridges, that may present barriers to salt-marsh migration were mapped. This study delineated 114 salt marshes totaling 340 hectares (ha), ranging in size from 0.11 ha (marshes less than 0.2 ha were mapped only if they were on Acadia National Park property) to 52 ha, with a median size of 1.0 ha. Inundation contours were mapped at 110 salt marshes. Approximately 350 ha of low-lying upland areas adjacent to these marshes will be inundated with 60 cm of sea-level rise. Many of these areas are currently freshwater wetlands. There are potential barriers to marsh migration at 27 of the 114 marshes. Although only 23 percent of the salt marshes in the study are on ANP property, about half of the upland areas that will be inundated are within ANP; most of the predicted inundated uplands (approximately 170 ha) include freshwater wetlands in the Northeast Creek and Bass Harbor Marsh areas. Most of the salt marshes analyzed do not have a significant amount of upland area available for migration. Seventy-five percent of the salt marshes have 20 meters or less of adjacent upland that would be inundated along most of their edges. All inundation contours, salt marsh locations, potential barriers, and survey data are stored in geospatial files for use in a geographic information system and are a part of this report.

Maine↗
USGS2013

Water volume and sediment volume and density in Lake Linganore between Boyers Mill Road Bridge and Bens Branch, Frederick County, Maryland, 2012

To assist in understanding sediment loadings and the management of water resources, a bathymetric survey was conducted in the part of Lake Linganore between Boyers Mill Road Bridge and Bens Branch in Frederick County, Maryland. The bathymetric survey was performed in January 2012 by the U.S. Geological Survey, in cooperation with the City of Frederick and Frederick County. A separate, but related, field effort to collect 18 sediment cores was conducted in March and April 2012. Depth and location data from the bathymetric survey and location data for the sediment cores were compiled and edited by using geographic information system (GIS) software. A three-dimensional triangulated irregular network (TIN) model of the lake bottom was created to calculate the volume of stored water in the reservoir. Large-scale topographic maps of the valley prior to inundation in 1972 were provided by the Frederick County Division of Utilities and Solid Waste Management and digitized for comparison with current (2012) conditions in order to calculate sediment volume. Cartographic representations of both water depth and sediment accumulation were produced, along with an accuracy assessment for the resulting bathymetric model. Vertical accuracies at the 95-percent confidence level for the collected data, the bathymetric surface model, and the bathymetric contour map were calculated to be 0.64 feet (ft), 1.77 ft, and 2.30 ft, respectively. A dry bulk sediment density was calculated for each of the 18 sediment cores collected during March and April 2012, and used to determine accumulated sediment mass. Water-storage capacity in the study area is 110 acre-feet (acre-ft) at a full-pool elevation 308 ft above the National Geodetic Vertical Datum of 1929, whereas total sediment volume in the study area is 202 acre-ft. These totals indicate a loss of about 65 percent of the original water-storage capacity in the 40 years since dam construction. This corresponds to an average rate of sediment accumulation of 5.1 acre-ft per year since Linganore Creek was impounded. Sediment thicknesses ranged from 0 to 16.7 ft. Sediment densities ranged from 0.38 to 1.08 grams per cubic centimeter, and generally decreased in the downstream direction. The total accumulated-sediment mass was 156,000 metric tons between 1972 and 2012.

Maryl↗
USGS2016

Archive of bathymetry and backscatter data collected in 2014 nearshore Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana

As part of the Barrier Island Monitoring Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off Breton and Gosier Islands, Louisiana, in July and August of 2014. To assist the United States Fish and Wildlife Service (USFWS) with restoration planning efforts, the USGS was tasked with answering fundamental questions about the physical environment of the southern Chandeleur Islands, including the geology, morphology, and oceanography. Baseline data needed to answer these questions were either insufficient or missing. The USGS conducted a comprehensive geologic investigation in the summer of 2014, collecting geophysical and sedimentological data. Breton Island, located at the southern end of the Chandeleur Island chain in southeastern Louisiana, was recognized as a natural, globally significant nesting sanctuary for several bird species and was established as the Breton National Wildlife Refuge (NWR) in 1904. The areal extent of Breton Island has diminished 90 percent since 1920. Land loss is attributed to ongoing relative sea-level rise, diminished sediment supply, and storm impacts. The bird population on Breton Island has also declined over the years, most notably after Hurricane George in 1998 and after Hurricane Katrina in 2015; the latter completely submerged the island. Despite decreasing habitable acreage, migratory seabirds continue to return and nest on Breton Island. To prevent the island from being submerged in the future, and to protect, stabilize, and provide more nesting and foraging areas for the bird population, the USFWS proposed a restoration effort to rebuild Breton Island to its pre-Katrina footprint. This data series serves as an archive of processed interferometric swath and single-beam bathymetry data, and side-scan sonar data, collected in the nearshore of Breton and Gosier Islands, NWR, Louisiana. The data were collected during two USGS cruises (USGS Field Activity Numbers 2014-314-FA and 2014-317-FA) in July and August 2014. Geographic information system data products include a 100-meter-cell-size interpolated bathymetry grid, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Louisiana↗
USGS1986

Identification and description of potential ground-water quality monitoring wells in Florida

The results of a survey of existing wells in Florida that meet the following criteria are presented: (1) well location is known , (2) principal aquifer is known, (3) depth of well is known, (4) well casing depth is known, (5) well water had been analyzed between 1970 and 1982, and (6) well data are stored in the U.S. Geological Survey 's (USGS) computer files. Information for more than 20,000 wells in Florida were stored in the USGS Master Water Data Index of the National Water Data Exchange and in the National Water Data Storage and Retrieval System 's Groundwater Site Inventory computerized files in 1982. Wells in these computer files that had been sampled for groundwater quality before November 1982 in Florida number 13,739; 1,846 of these wells met the above criteria and are the potential (or candidate) groundwater quality monitoring wells included in this report. The distribution by principal aquifer of the 1,846 wells identified as potential groundwater quality monitoring wells is as follows: 1,022 tap the Floridan aquifer system, 114 tap the intermediate aquifers, 232 tap the surficial aquifers, 246 tap the Biscayne aquifer, and 232 tap the sand-and-gravel aquifer. These wells are located in 59 of Florida 's 67 counties. This report presents the station descriptions, which include location , site characteristics, period of record, and the type and frequency of chemical water quality data collected for each well. The 1,846 well locations are plotted on 14 USGS 1:250,000 scale, 1 degree by 2 degree, quadrangle maps. This relatively large number of potential (or candidate) monitoring wells, geographically and geohydrologically dispersed, provides a basis for a future groundwater quality monitoring network and computerized data base for Florida. There is a large variety of water quality determinations available from these wells, both areally and temporally. Future sampling of these wells would permit analyses of time and areal trends for selected water quality characteristics throughout the State. The identification and description of the potential monitoring wells and the listing of the type and frequency of the groundwater quality data forms a foundation for both the network and the data base. (Author 's abstract)

Water-Resources Investigations Report↗
USGS2025

Assessment of coastal and fluvial morphodynamic changes using Structure-for-Motion: A case study of the Sfȃntu Gheorghe Mouth (Danube Delta, Romania)

The ability to accurately map erosion, flooding, and habitat loss in coastal environments is crucial for formulating national strategies aimed at preventing and mitigating the impacts of natural disasters. A fundamental component of this process is the implementation of coastal morphodynamics monitoring through Structure-from-Motion (SfM) techniques, utilizing high-resolution 2D/3D data obtained from aerial photogrammetry. To assess morphodynamic changes over a three-year period (2022 – 2024), several SfM-based photogrammetric studies were conducted, each year, in the Romanian sector of the Danube-Black Sea coastal zone, specifically at the mouth of one of the Danube River distributaries (Sf Gheorghe branch) into the Black Sea, and along the left bank, near Sf Gheorghe locality, located within the Danube Delta Biosphere Reserve (DDBR). The essential equipment for aerial photogrammetry comprises Unmanned Aerial Vehicles (UAVs) and Global Navigation Satellite Systems (GNSS). In this study, the UAV used was a DJI Mavic 3T (Enterprise/Thermal) drone, complemented by two Trimble R12i and R4 GNSS systems, as well as approximately 10 Ground Control Points (GCPs). Data acquisition and processing were carried out using specialized photogrammetric software (Agisoft Metashape) along with various GIS tools (e.g., Blue Marble Geographics Global Mapper and ESRI ArcMap). The photogrammetric products generated for the study, as detailed in this paper, include Digital Elevation Models (DEMs), Digital Terrain Models (DTMs), orthomosaics (orthophotos), and others. At Sfântu Gheorghe beach, a comparison between 2023 and 2024 photogrammetric surveys revealed that the left bank of the Sf. Gheorghe Arm, at the river mouth into the Black Sea, suffered from a twist (erosion) of up to 64 metres. Additionally, on the selected perimetre (total area of 31,910 square meters ) from the beach and dune zone of Sf. Gheorghe, an area of up to 16,202 square meters was eroded between 2023 and 2024. This contrasts with the period between 2022 and 2023, during which deposition predominated. Erosion at the Danube mouths and the adjacent Black Sea coastline is driven by a complex interaction of natural and anthropogenic factors. Natural processes, including subsidence, sea-level rise, and episodic extreme storm events, contribute significantly to coastal dynamics. Meanwhile, human-induced factors, such as upstream hydrotechnical works that limits sediment transport, cutting of navigation canals, as well as the exacerbating effects of climate change, further accelerate erosion. The recent Structure-from-Motion (SfM) surveys provide essential quantitative data, enabling a detailed analysis of both short-term and long-term morphodynamic changes influenced by seasonal variations and extreme hydrometeorological events in this highly dynamic coastal system.

Sfȃntu Gheorghe Mouth (Danube Delta)↗
USGS2018

Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois

A two-dimensional hydraulic model and digital flood‑inundation maps were developed for a 30-mile reach of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois. The flood-inundation maps, which can be accessed through the U.S. Geological Survey (USGS) Flood Inundation Mapping Science web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Wabash River at Mount Carmel, Ill (USGS station number 03377500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site (NWS AHPS site MCRI2). The NWS AHPS forecasts peak stage information that may be used with the maps developed in this study to show predicted areas of flood inundation. Flood elevations were computed for the Wabash River reach by means of a two-dimensional, finite-volume numerical modeling application for river hydraulics. The hydraulic model was calibrated by using global positioning system measurements of water-surface elevation and the current stage-discharge relation at both USGS streamgage 03377500, Wabash River at Mount Carmel, Ill., and USGS streamgage 03378500, Wabash River at New Harmony, Indiana. The calibrated hydraulic model was then used to compute 27 water-surface elevations for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from less than the action stage (9 ft) to the highest stage (35 ft) of the current stage-discharge rating curve. The simulated water‑surface elevations were then combined with a geographic information system digital elevation model, derived from light detection and ranging data, to delineate the area flooded at each water level. The availability of these maps, along with information on the internet regarding current stage from the USGS streamgage at Mount Carmel, Ill., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Illinois↗
USGS2009

Movements of juvenile Gyrfalcons from western and interior Alaska following departure from their natal areas

J uvenile raptors often travel thousands of kilometers from the time they leave their natal areas to the time they enter a breeding population. Documenting movements and identifying areas used by raptors before they enter a breeding population is important for understanding the factors that influence their survival. In North America, juvenile Gyrfalcons ( Falco rusticolus ) are routinely observed outside the species' breeding range during the nonbreeding season, but the natal origins of these birds are rarely known. We used satellite telemetry to track the movements of juvenile Gyrfalcons during their first months of independence. We instrumented nestlings with lightweight satellite transmitters within 10 d of estimated fledging dates on the Seward Peninsula in western Alaska and in Denali National Park (Denali) in interior Alaska. Gyrfalcons spent an average of 41.4 ± 6.1 d (range = 30–50 d) in their natal areas after fledging. The mean departure date from natal areas was 27 August ± 6.4 d. We tracked 15 individuals for an average of 70.5 ± 28.1 d post-departure; Gyrfalcons moved from 105 to 4299 km during this period and tended to move greater distances earlier in the tracking period than later in the tracking period. Gyrfalcons did not establish temporary winter ranges within the tracking period. We identified several movement patterns among Gyrfalcons, including unidirectional long-distance movements, multidirectional long- and short-distance movements, and shorter movements within a local region. Gyrfalcons from the Seward Peninsula remained in western Alaska or flew to eastern Russia with no movements into interior Alaska. In contrast, Gyrfalcons from Denali remained in interior Alaska, flew to northern and western Alaska, or flew to northern Alberta. Gyrfalcons from both study areas tended to move to coastal, riparian, and wetland areas during autumn and early winter. Because juvenile Gyrfalcons dispersed over a large geographic area and across three international boundaries, conservation efforts should focus on both regional and international scales.

Journal of Raptor Research↗
USGS1987

Hydrologic unit maps

A set of maps depicting approved boundaries of, and numerical codes for, river-basin units of the United States has been developed by the U.S . Geological Survey. These 'Hydrologic Unit Maps' are four-color maps that present information on drainage, culture, hydrography, and hydrologic boundaries and codes of (1) the 21 major water-resources regions and the 222 subregions designated by the U.S . Water Resources Council, (2) the 352 accounting units of the U.S. Geological Survey's National Water Data Network, and (3) the 2,149 cataloging units of the U.S . Geological Survey's 'Catalog of information on Water Data:' The maps are plotted on the Geological Survey State base-map series at a scale of 1 :500,000 and, except for Alaska, depict hydrologic unit boundaries for all drainage basins greater than 700 square miles (1,813 square kilometers). A complete list of all the hydrologic units, along with their drainage areas, their names, and the names of the States or outlying areas in which they reside, is contained in the report. These maps and associated codes provide a standardized base for use by water-resources organizations in locating, storing, retrieving, and exchanging hydrologic data, in indexing and inventorying hydrologic data and information, in cataloging water-data acquisition activities, and in a variety of other applications. Because the maps have undergone extensive review by all principal Federal, regional, and State water-resource agencies, they are widely accepted for use in planning and describing water-use and related land-use activities, and in geographically organizing hydrologic data . Examples of these uses are given in the report . The hydrologic unit codes shown on the maps have been approved as a Federal Information Processing Standard for use by the Federal establishment.

Water Supply Paper↗
USGS2013

Volcano crisis response at Yellowstone volcanic complex - after-action report for exercise held at Salt Lake City, Utah, November 15, 2011

A functional tabletop exercise was run on November 14-15, 2011 in Salt Lake City, Utah, to test crisis response capabilities, communication protocols, and decision-making by the staff of the multi-agency Yellowstone Volcano Observatory (YVO) as they reacted to a hypothetical exercise scenario of accelerating volcanic unrest at the Yellowstone caldera. The exercise simulated a rapid build-up of seismic activity, ground deformation, and hot-spring water-chemistry and temperature anomalies that culminated in a small- to moderate-size phreatomagmatic eruption within Yellowstone National Park. The YVO scientific team's responses to the unfolding events in the scenario and to simulated requests for information by stakeholders and the media were assessed by (a) the exercise organizers; (b) several non-YVO scientists, who observed and queried participants, and took notes throughout the exercise; and (c) the participants themselves, who kept logs of their actions during the exercise and later participated in a group debriefing session and filled out detailed questionnaires. These evaluations were tabulated, interpreted, and summarized for this report, and on the basis of this information, recommendations have been made. Overall, the YVO teams performed their jobs very well. The exercise revealed that YVO scientists were able to successfully provide critical hazards information, issue information statements, and appropriately raise alert levels during a fast-moving crisis. Based on the exercise, it is recommended that several measures be taken to increase YVO effectiveness during a crisis: 1. Improve role clarification within and between YVO science teams. 2. Improve communications tools and protocols for data-sharing and consensus-building among YVO scientists, who are geographically and administratively dispersed among various institutions across the United States. 3. Familiarize YVO staff with Incident Command System (ICS) procedures and protocols, and provide more in-depth training to appropriate staff members, as needed. 4. Train all science team members in the use of all analytical and computational tools available to them, in order to maximize effectiveness of teams in tracking and interpreting possible accelerating unrest at Yellowstone. Desirable pre-crisis preparations include: (a) updating a catalog of existing map and information products (and identifying additional products) that would be helpful during a crisis; (b) creating "to do" lists of early-crisis tasks for each scientific team; (c) coordinating radio frequencies among partner agencies; and (d) brief training on and promotion of the internal YVO Web log as a repository for scientific observations, data, photographs, and other material to be shared among YVO scientific teams during a crisis. This exercise was designed as an opportunity to practice response to a fast-developing volcano crisis and to test for organizational and procedural weaknesses that could emerge during a real crisis. This report is based upon the observations of the exercise organizers during the one-day exercise and upon written evaluations by the participants. It does not attempt to evaluate any other aspect of YVO or the scientific expertise of any of the highly competent YVO staff. Participants unanimously found the exercise to be helpful for improving their response capabilities, and it is our hope that the report will be a starting point for internal discussions that will make YVO even better-prepared for some future volcano crisis.

Utah↗
USGS2007

Latin hypercube approach to estimate uncertainty in ground water vulnerability

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Ground Water↗
USGS2014

Flood-inundation maps for the East Fork White River near Bedford, Indiana

Digital flood-inundation maps for an 1.8-mile reach of the East Fork White River near Bedford, Indiana (Ind.) were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selectedwater levels (stages) at USGS streamgage 03371500, East Fork White River near Bedford, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/uv?site_no=03371500. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the East Fork White River near Bedford, Ind. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the East Fork White River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 03371500, East Fork White River near Bedford, Ind., and documented high-water marks from the flood of June 2008. The calibrated hydraulic model was then used to determine 20 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging (LiDAR) data having a 0.593-foot vertical accuracy) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage near Bedford, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery eforts.

Indiana↗
USGS2015

Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science through data reuse

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km 2 ). LAGOS includes two modules: LAGOS GEO , with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOS LIMNO , with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.

Connecticut, Delaware, Illinois, Indiana, Iowa, Ma↗
USGS2014

Flood-inundation maps for the North Branch Elkhart River at Cosperville, Indiana

Digital flood-inundation maps for a reach of the North Branch Elkhart River at Cosperville, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, Detroit District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/uv?site_no=04100222 . In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system ( http:/water.weather.gov/ahps/ ). The NWS AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the North Branch Elkhart River at Cosperville, Ind. NWS AHPS-forecast peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the North Branch Elkhart River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and preliminary high-water marks from the flood of March 1982. The calibrated hydraulic model was then used to determine four water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [LiDAR]) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and forecast stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Indiana↗
USGS2018

Flood-inundation maps for the Wabash River at Lafayette, Indiana

Digital flood-inundation maps for an approximately 4.8-mile reach of the Wabash River at Lafayette, Indiana (Ind.) were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science web site at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 03335500, Wabash River at Lafayette, Ind. Current streamflow conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the internet at https://waterdata.usgs.gov/in/nwis/uv?site_no=03335500 . In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood-warning system ( https://water.weather.gov/ahps/ ). The NWS AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the Wabash River at Lafayette, Ind. NWS AHPS-forecast peak-stage information may be used with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the Wabash River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 03335500, Wabash River at Lafayette, Ind., and high-water marks from the flood of July 2003 (U.S. Army Corps of Engineers [USACE], 2007). The calibrated hydraulic model was then used to determine 23 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging to delineate the area flooded at each water level. The availability of these maps, along with internet information regarding current stage from the USGS streamgage 03335500, Wabash River at Lafayette, Ind., and forecasted high-flow stages from the NWS AHPS, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, and for postflood recovery efforts.

Indiana↗
USGS2001

Geologic map and digital database of the Porcupine Wash 7.5 minute Quadrangle, Riverside County, southern California

This data set maps and describes the geology of the Porcupine Wash 7.5 minute quadrangle, Riverside County, southern California. The quadrangle, situated in Joshua Tree National Park in the eastern Transverse Ranges physiographic and structural province, encompasses parts of the Hexie Mountains, Cottonwood Mountains, northern Eagle Mountains, and south flank of Pinto Basin. It is underlain by a basement terrane comprising Proterozoic metamorphic rocks, Mesozoic plutonic rocks, and Mesozoic and Mesozoic or Cenozoic hypabyssal dikes. The basement terrane is capped by a widespread Tertiary erosion surface preserved in remnants in the Eagle and Cottonwood Mountains and buried beneath Cenozoic deposits in Pinto Basin. Locally, Miocene basalt overlies the erosion surface. A sequence of at least three Quaternary pediments is planed into the north piedmont of the Eagle and Hexie Mountains, each in turn overlain by successively younger residual and alluvial deposits. The Tertiary erosion surface is deformed and broken by north-northwest-trending, high-angle, dip-slip faults and an east-west trending system of high-angle dip- and left-slip faults. East-west trending faults are younger than and perhaps in part coeval with faults of the northwest-trending set. The Porcupine Wash database was created using ARCVIEW and ARC/INFO, which are geographical information system (GIS) software products of Envronmental Systems Research Institute (ESRI). The database consists of the following items: (1) a map coverage showing faults and geologic contacts and units, (2) a separate coverage showing dikes, (3) a coverage showing structural data, (4) a scanned topographic base at a scale of 1:24,000, and (5) attribute tables for geologic units (polygons and regions), contacts (arcs), and site-specific data (points). The database, accompanied by a pamphlet file and this metadata file, also includes the following graphic and text products: (1) A portable document file (.pdf) containing a navigable graphic of the geologic map on a 1:24,000 topographic base. The map is accompanied by a marginal explanation consisting of a Description of Map and Database Units (DMU), a Correlation of Map and Database Units (CMU), and a key to point-and line-symbols. (2) Separate .pdf files of the DMU and CMU, individually. (3) A PostScript graphic-file containing the geologic map on a 1:24,000 topographic base accompanied by the marginal explanation. (4) A pamphlet that describes the database and how to access it. Within the database, geologic contacts , faults, and dikes are represented as lines (arcs), geologic units as polygons and regions, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum and link it to other tables (.rel) that provide more detailed geologic information.

California↗