This North American Environmental Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Environmental Atlas data sets is strictly to complete the context of the data.The North American Environmental Atlas – Lakes and Rivers dataset displays the coastline, linear hydrographic features (major rivers, streams, and canals), and area hydrographic features (major lakes and reservoirs) of North America at a reference spatial scale of 1:1,000,000.This map offers a seamless integration of hydrographic features derived from cartographic products generated by Natural Resources Canada (NRCan), United States Geological Survey (USGS), National Institute of Statistics and Geography, (Instituto Nacional de Estadística y Geografía-Inegi), National Water Commission (Comisión Nacional del Agua-Conagua).This current version of the North America Lakes and Rivers dataset supersedes the version published by the Commission for Environmental Cooperation in 2011.Files Download

This layer is sourced from maps.bts.dot.gov.

U.S. Lakes (Generalized) provides a base map layer of major lakes of United States.

The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data.The North American Environmental Atlas – Lakes dataset displays area hydrographic features (major lakes and reservoirs) of North America at a reference spatial scale of 1:1,000,000.This map offers a seamless integration of hydrographic features derived from cartographic products generated by Natural Resources Canada (NRCan), United States Geological Survey (USGS), National Institute of Statistics and Geography, (Instituto Nacional de Estadística y Geografía-Inegi), National Water Commission (Comisión Nacional del Agua-Conagua).This current version of the North America Lakes and Rivers dataset supersedes the version published by the Commission for Environmental Cooperation in 2011.Files Download

This U.S. Geological Survey (USGS) data release presents a digital database of geospatially enabled vector layers and tabular data transcribed from the geologic map of the Lake Owen quadrangle, Albany County, Wyoming, which was originally published as U.S. Geological Survey Geologic Quadrangle Map GQ-1304 (Houston and Orback, 1976). The 7.5-minute Lake Owen quadrangle is located in southeastern Wyoming approximately 25 miles (40 kilometers) southwest of Laramie in the west-central interior of southern Albany County, and covers most of the southern extent of Sheep Mountain, the southeastern extent of Centennial Valley, and a portion of the eastern Medicine Bow Mountains. This relational geodatabase, with georeferenced data layers digitized at the publication scale of 1:24,000, organizes and describes the geologic and structural data covering the quadrangle's approximately 35,954 acres and enables the data for use in spatial analyses and computer cartography. The data types presented in this release include geospatial features (points, lines, and polygons) with matching attribute tables, nonspatial descriptive and reference tables, and ancillary resource files for correct symbolization, in formats that conform to the Geologic Map Schema (GeMS) developed and released by the U.S. Geological Survey's National Cooperative Geologic Mapping Program (GeMS, 2020). When reconstructed from the geodatabase's vector layers and tabular data that has been symbolized according to specifications encoded in the accompanying style file, and using the supplied Federal Geographic Data Committee (FGDC) GeoAge font for labeling formations and GeoSym fonts for structural line decorations and orientation measurement symbols, this data release presents the Geologic Map as shown on the published GQ-1304 map sheet. These GIS data augment but do not supersede the information presented on GQ-1304. References: Houston, R.S., and Orback, C.J., 1976, Geologic Map of the Lake Owen Quadrangle, Albany County, Wyoming: U.S. Geological Survey Geologic Quadrangle Map GQ-1304, scale 1:24,000, https://doi.org/10.3133/gq1304. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema)- A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org//10.3133/tm11B10.

In the Great Lakes basin, there are numerous organizations undertaking scientific monitoring and research efforts with the goal of identifying threats and evaluating management strategies that will protect and restore the Great Lakes ecosystem. Coordination among all these stakeholders is a challenge, and having a centralized location where researchers and managers can identify relevant scientific activities and access fundamental information about these activities is crucial for efficient management. The Science in the Great Lakes (SiGL) Mapper was a map-based discovery tool that spatially displayed basin-wide multidisciplinary monitoring and research activities conducted by both USGS and partners from all five Great Lakes. It was designed to help Great Lakes researchers and managers strategically plan, implement, and analyze monitoring and restoration activities by providing easy access to historical and on-going project metadata while allowing them to identify gaps (spatially a ...

Water supply lakes are the primary source of water for many communities in northern and western Missouri. Therefore, accurate and up-to-date estimates of lake capacity are important for managing and predicting adequate water supply. Many of the water supply lakes in Missouri were previously surveyed by the U.S. Geological Survey in the early 2000s (Richards, 2013) and in 2013 (Huizinga, 2014); however, years of potential sedimentation may have resulted in reduced water storage capacity. Periodic bathymetric surveys are useful to update the area/capacity table and to determine changes in the bathymetric surface. In June and July 2020, the U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources and in collaboration with various cities in north- and west-central Missouri, completed bathymetric surveys of 12 lakes using a marine-based mobile mapping unit, which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Bathymetric data were collected as the vessel traversed longitudinal transects to provide nearly complete coverage of the lake. The MBES was electronically tilted in some areas to improve data collection along the shoreline, in coves, and in areas that are shallower than about 2.0 meters deep (the practical limit of reasonable and safe data collection with the MBES). At some lakes, supplemental data were collected in shallow areas using an acoustic Doppler current profiler (ADCP) mounted on a remote-controlled vessel equipped with a differential global positioning system (DGPS). Bathymetric quality-assurance data also were collected at each lake to evaluate the vertical accuracy of the gridded bathymetric point data from the MBES. As part of the survey at each of these lakes, one or more reference marks or temporary bench marks were established to provide a point of known location and elevation from which the water surface could be measured or another survey could be referenced at a later date. In addition, the elevation of a primary spillway or intake was surveyed, when present. These points were surveyed using a real-time kinematic (RTK) Global Navigation Satellite System (GNSS) receiver connected to the Missouri Department of Transportation real-time network (RTN), which provided real-time survey-grade horizontal and vertical positioning, using field procedures as described in Rydlund and Densmore (2012) for a Level II real-time positioning survey. Mozingo Lake and Maryville Reservoir were surveyed in June 2020 as part of the group of lakes surveyed in 2020. However, extraordinary interest in the bathymetry at Mozingo Lake by the city of Maryville necessitated these data being released earlier than the other 2020 lakes (Huizinga and others, 2021, 2022). The MBES data can be combined with light detection and ranging (lidar) data to prepare a bathymetric map and a surface area and capacity table for each lake. These data also can be used to compare the current bathymetric surface with any previous bathymetric surface. Data from each of the remaining 10 lakes surveyed in 2020 are provided in ESRI Shapefile format (ESRI, 2021). Each of the lakes surveyed in 2020 except Higginsville has a child page containing the metadata and two zip files, one for the bathymetric data, and the other for the bathymetric quality-assurance data. Data from the surveys at the Upper and Lower Higginsville Reservoirs are in two zip files on a single child page, one for the bathymetric data and one for the bathymetric quality assurance data of both lakes, and a single summary metadata file. The zip files follow the format of "####2020_bathy_pts.zip" or "####2020_QA_raw.zip," where "####" is the lake name. Each of these zip files contains a shapefile with an attribute table. Attribute/column labels of each table are described in the "Entity and attribute" section of the metadata file. The various reference marks and additional points from all the lake surveys are provided in ESRI Shapefile format (ESRI, 2021) with an attribute table on the main landing page. Attribute/column labels of this table are described in the "Entity and attribute" section of the metadata file. References Cited: Environmental Systems Research Institute, 2021, ArcGIS: accessed May 20, 2021, at https://www.esri.com/en-us/arcgis/about-arcgis/overview Huizinga, R.J., 2014, Bathymetric surveys and area/capacity tables of water-supply reservoirs for the city of Cameron, Missouri, July 2013: U.S. Geological Survey Open-File Report 2014–1005, 15 p., https://doi.org/10.3133/ofr20141005. Huizinga, R.J., Oyler, L.D., and Rivers, B.C., 2022, Bathymetric contour maps, surface area and capacity tables, and bathymetric change maps for selected water-supply lakes in northwestern Missouri, 2019 and 2020: U.S. Geological Survey Scientific Investigations Map 3486, 12 sheets, includes 21-p. pamphlet, https://doi.org/10.3133/sim3486. Huizinga R.J., Rivers, B.C., and Oyler, L.D., 2021, Bathymetric and supporting data for various water supply lakes in northwestern Missouri, 2019 and 2020 (ver. 1.1, September 2021): U.S. Geological Survey data release, https://doi.org/10.5066/P92M53NJ. Richards, J.M., 2013, Bathymetric surveys of selected lakes in Missouri—2000–2008: U.S. Geological Survey Open-File Report 2013–1101, 9 p. with appendix, https://pubs.usgs.gov/of/2013/1101. Rydlund, P.H., Jr., and Densmore, B.K., 2012, Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey: U.S. Geological Survey Techniques and Methods, book 11, chap. D1, 102 p. with appendixes, https://doi.org/10.3133/tm11D1.

Note: This description is taken from a draft report entitled "Creation of a Database of Lakes in the St. Johns River Water Management District of Northeast Florida" by Palmer Kinser. Introduction“Lakes are among the District’s most valued resources. Their aesthetic appeal adds substantially to waterfront property values, which in turn generate tax revenues for local governments. Fish camps and other businesses, that provide lake visitors with supplies and services, benefit local economies directly. Commercial fishing on the District’s larger lakes produces some income, , but far greater economic benefits are produced from sport fishing. Some of the best bass fishing lakes in the world occur in the District. Trophy fishing, guide services and high-stakes fishing tournaments, which they support, also generate substantial revenues for local economies. In addition, the high quality of District lakes has allowed swimming, fishing, and boating to become among the most popular outdoor activities for many District residents and attracts many visitors. Others frequently take advantage of the abundant opportunities afforded for duck hunting, bird watching, photography, and other nature related activities.”(from likelihood of harm to lakes report).ObjectiveThe objective of this work was to create a consistent database of natural lake polygon features for the St. Johns River Water Management District. Other databases examined contained point features only, polygons representing a wide range of dates, water bodies not separated or coded adequately by feature type (i.e. no distinctions were made between lakes, rivers, excavations, etc.), or were incomplete. This new database will allow users to better characterize and measure the lakes resource of the District, allowing comparisons to be made and trends detected; thereby facilitating better protection and management of the resource.BackgroundPrior to creation of this database, the District had 2 waterbody databases. The first of these, the 2002 FDEP Primary Lake Location database, contained 3859 lake point features, state-wide, 1418 of which were in SJRWMD. Only named lakes were included. Data sources were the Geographic Names Information System (GNIS), USGS 1:24000 hydrography data, 1994 Digital orthophoto quarter quadrangles (DOQQs), and USGS digital raster graphics (DRGs). The second was the SJRWMD Hydrologic Network (Lake / Pond and Reservoir classes). This data base contained 42,002 lake / pond and reservoir features for the SJRWMD. Lakes with multiple pools of open water were often mapped as multiple features and many man-made features (borrow pits, reservoirs, etc.) were included. This dataset was developed from USGS map data of varying dates.MethodsPolygons in this new lakes dataset were derived from a "wet period" landcover map (SJRWMD, 1999), in which most lake levels were relatively high. Polygons from other dates, mostly 2009, were used for lakes in regionally dry locations or for lakes that were uncharacteristically wet in 1999, e.g. Alachua Sink. Our intension was to capture lakes in a basin-full condition; neither unusually high nor low. To build the data set, a selection was made of polygons coded as lakes (5200), marshy lakes (5250, enclosed saltwater ponds in salt marsh (5430), slough waters (5600), and emergent aquatic vegetation (6440). Some large, regionally significant or named man-made reservoirs were also included, as well as a small number of named excavations. All polygons were inspected and edited, where appropriate, to correct lake shores and merge adjacent lake basin features. Water polygons separated by marshes or other low-ground features were grouped and merged to form multipart features when clearly associated within a single lake basin. The initial set of lake names were captured from the Florida Primary Lake Location database. Labels were then moved where needed to insure that they fell within the water bodies referenced. Additional lake names were hand entered using data from USGS 7.5 minute quads, Google Maps, MapQuest, Florida Department of Transportation (FDOT) county maps, and other sources. The final dataset contains 4892 polygons, many of which are multi-part.Operationally, lakes, as captured in this data base, are those features that were identified and mapped using the District’s landuse/landcover scheme in the 5200, 5250, 5430, 5600 classes referenced above; in addition to some areas mapped tin the 6440 class. Some additional features named as lakes, ponds, or reservoirs were also included, even when not currently appearing to be lakes. Some are now very marshy or even dry, but apparently held deeper pools of water in the past. A size limit of 1 acre or more was enforced, except for named features, 30 of which were smaller. The smallest lake was Fox Lake, a doline of 0.04 acres in Orange county. The largest lake, Lake George covered 43,212.8 acres.The lakes of the SJRWMD are a diverse set of features that may be classified in many ways. These include: by surrounding landforms or landcover, by successional stage (lacustrine to palustrine gradient), by hydrology (presence of inflows and/or outflows, groundwater linkages, permanence, etc.), by water quality (trophic state, water color, dissolved solids, etc.), and by origin. We chose to classify the lakes in this set by origin, based on the lake type concepts of Hutchinson (1957). These types are listed in the table below (Table 1). We added some additional types and modified the descriptions to better reflect Florida’s geological conditions (Table 2). Some types were readily identified, others are admittedly conjectural or were of mixed origins, making it difficult to pick a primary mechanism. Geological map layers, particularly total thickness of overburden above the Floridan aquifer system and thickness of the intermediate confining unit, were used to estimate the likelihood of sinkhole formation. Wind sculpting appears to be common and sometimes is a primary mechanism but can be difficult to judge from remotely sensed imagery. For these and others, the classification should be considered provisional. Many District lakes appear to have been formed by several processes, for instance, sinkholes may occur within lakes which lie between sand dunes. Here these would be classified as dune / karst. Mixtures of dunes, deflation and karst are common. Saltmarsh ponds vary in origin and were not further classified. In the northern coastal area they are generally small, circular in outline and appear to have been formed by the collapse and breakdown of a peat substrate, Hutchinson type 70. Further south along the coast additional ponds have been formed by the blockage of tidal creeks, a fluvial process, perhaps of Hutchinson’s Type 52, lateral lakes, in which sediments deposited by a main stream back up the waters of a tributary. In the area of the Cape Canaveral, many salt marsh ponds clearly occupy dune swales flooded by rising ocean levels. A complete listing of lake types and combinations is in Table 3. TypeSub-TypeSecondary TypeTectonic BasinsMarine BasinTectonic BasinsMarine BasinCompound dolineTectonic BasinsMarine BasinkarstTectonic BasinsMarine BasinPhytogenic damTectonic BasinsMarine BasinAbandoned channelTectonic BasinsMarine BasinKarstSolution LakesCompound dolineSolution LakesCompound dolineFluvialSolution LakesCompound dolinePhytogenicSolution LakesDolineSolution LakesDolineDeflationSolution LakesDolineDredgedSolution LakesDolineExcavatedSolution LakesDolineExcavationSolution LakesDolineFluvialSolution LakesKarstKarst / ExcavationSolution LakesKarstKarst / FluvialSolution LakesKarstDeflationSolution LakesKarstDeflation / excavationSolution LakesKarstExcavationSolution LakesKarstFluvialSolution LakesPoljeSolution LakesSpring poolSolution LakesSpring poolFluvialFluvialAbandoned channelFluvialFluvialFluvial Fluvial PhytogenicFluvial LeveeFluvial Oxbow lakeFluvial StrathFluvial StrathPhytogenicAeolianDeflationAeolianDeflationDuneAeolianDeflationExcavationAeolianDeflationKarstAeolianDuneAeolianDune DeflationAeolianDuneExcavationAeolianDuneAeolianDuneKarstShoreline lakesMaritime coastalKarst / ExcavationOrganic accumulationPhytogenic damSalt Marsh PondsMan madeExcavationMan madeDam

America’s Great Lakes — Superior, Michigan, Huron, Erie and Ontario — hold 21 percent of the world’s surface fresh water and host habitat for a variety of fish and wildlife species of concern. They provide drinking water for more than 40 million people and economic benefits from fishing and recreation. The Great Lakes Region is also a major agricultural area, with more than 55 million acres of land under production. All of these uses impact the Great Lakes ecosystem. With the CCA designation, USDA will build on existing strong partnerships in the Great Lakes Region to provide approaches and tools for producers to better manage nutrients and sediment on agricultural land. Accelerated conservation on private lands will help improve water quality, leading to better habitat for fish and wildlife and increased economic opportunities, including maintaining agricultural productivity in this vital region. This dataset includes a printer-friendly CCA map and shapefiles for GIS. Resources in this dataset:Resource Title: Great Lakes Region. File Name: Web Page, url: https://www.nrcs.usda.gov/programs-initiatives/rcpp-regional-conservation-partnership-program/critical-conservation-areas Information about the project and links to a printer-friendly CCA map (PDF, 1.2MB) and Shapefiles for GIS (ZIP, 232KB).

The 2024 Integrated Report is a biennial publication on the quality of Michigan’s water resources.The Clean Water Act (CWA) requires Michigan to prepare a biennial report on the quality of its water resources as the principal means of conveying water quality protection/monitoring information to the United States Environmental Protection Agency (USEPA) and the United States Congress. The Integrated Report satisfies the listing requirements of Section 303(d) and the reporting requirements of Section 305(b) and 314 of the CWA. The Section 303(d) list includes Michigan water bodies that are not attaining one or more designated use and require the establishment of Total Maximum Daily Loads (TMDLs) to meet and maintain Water Quality Standards. It should be noted that these comprehensive datasets include assessment units throughout the state of Michigan and are not limited to those on the Section 303d list. The 303d status of an assessment unit is indicated in the EPA303dImpairment field, with 0 as not listed and 1 as listed.Further information, including a comprehensive 303(d) list, can be found on EGLE’s Integrated Report webpage.Field NameDescriptionAUIDAssessment Unit Identification number includes the corresponding HUC12 of the hydrographic feature, followed by a unique numeric identifier. This field is used to identify assessment units and submit water quality information to EPA. It should be used to reference assessments described in EGLE’s biannual integrated report and EPA’s How’s My Waterway information systemAssessment Unit NameWaterbody name derived from authoritative sources or local knowledge.Assessment Unit DescriptionA basic location description of the hydrographic features contained in an AUID.HowsMyWaterwayLinkLink to how’s my waterway, an EPA data hub that displays additional information about AUIDsEPAIRCategoryEnvironmental Protection Agency Integrated Report Category for an individual AUID. These categories indicate whether a waterbody is supporting designated uses or not. More information can be found here. PartialBodyContactAttainmentThis field indicates the attainment status of AUIDs in respect to the Partial Body Contact designated use. This refers to the use of a surface water that may cause the human body to come into direct contact with the water, but normally not to the point of complete submergence, such as wading or boating. Water bodies are evaluated for the Total Body Contact (TBC) and Partial Body Contact (PBC) recreation using E. coli bacteria as an indicator for other harmful pathogens.TotalBodyContactAttainmentThis field indicates the attainment status of AUIDs in respect to the Total Body Contact designated use. This refers to the use of a surface water for swimming or other recreational activity that causes the human body to come into direct contact with the water to the point of complete submergence. Water bodies are evaluated for the Total Body Contact (TBC) and Partial Body Contact (PBC) recreation using E. coli bacteria as an indicator for other harmful pathogens.ColdWaterFisheryAttainmentThis field indicates the attainment status of AUIDs in respect to the Cold Water Fishery designated use. This use includes the protection of waters where the dominant species under natural conditions would be temperature intolerant indigenous species. Examples include members of the following families: Salmon, Trout, Cod, Whitefish.WarmWaterFisheryAttainmentThis field indicates the attainment status of AUIDs in respect to the Warm Water Fishery designated use. This use includes the protection of waters where the dominant species under natural conditions would be temperature tolerant indigenous non- salmonid species. Examples include members of the following families: Pearch, Panfish, Bowfin, Bass, Catfish, Pike.OtherIndigenousAquaticLifeAttainmentThis field indicates the attainment status of AUIDs in respect to the Other Indigenous Aquatic Life designated use. This use includes the protection of waters for macroinvertebrate and aquatic plant communities. Macroinvertebrate examples include mayflies, stoneflies, and caddisflies.FishConsumptionAttainmentThis field indicates the attainment status of AUIDs in respect to the Fish Consumption designated use. This use includes the protection of aquatic communities and human health related to.consumption of fish and shellfish. In other words, this use means that not only can fish and shellfish thrive in a waterbody, but when caught, can also be safely eaten by humans.PublicWaterSupplyAttainmentThis field indicates the attainment status of AUIDs in respect to the Public Water Supply designated use. This use includes waters that are the source for drinking water supplies and often includes waters for food processing. Waters for drinking water may require treatment prior to distribution in public water systems.EPA303dImpairmentThis field indicates whether an AUID is listed as impaired, or not supporting a designated use, in the corresponding integrated report. 1 = Impaired, 0 = not Impaired

The geodatabase contains 13 relate tables that together provide updated and synchronized classifications to an existing vegetation map layer for each of the nine park units in the Great Lakes Network (GLKN) of the National Park Service (NPS) Natural Resource Inventory and Monitoring Program. The classifications include 1) vegetation types at every hierarchical level in the 2015 version of the U.S. National Vegetation Classification (USNVC) and 2) map classes that represent vegetation and land cover in the vegetation map layers. Furthermore, the tables provide a crosswalk between the two classifications (vegetation and map). Each park unit in GLKN has received, at different times over several years, vegetation data products from the NPS Vegetation Mapping Inventory (VMI) Program. However, the vegetation and map classifications were at different stages of development over these years. With this geodatabase product, having a series of already linked relate tables, the original vegetation map layer for each park unit can be linked to the updated and synchronized classification information for both vegetation types and map classes.

This layer is sourced from maritimeboundaries.noaa.gov.

The ENC_General map service displays ENC data within the scale range of 1:600,001 and 1:1,500,000. The ENC data will be updated weekly. This map service is not intended for navigation purpose.

Data from Washington State Department of Ecology. Downloaded from web page http://www.ecy.wa.gov/services/gis/data/data.htm on 3/28/2016.This GIS layer contains bathymetric contours of selected freshwater lakes in Grant County, Washington during the mid-seventies. The bathymetric contours were digitized from maps contained in a series of seven documents: Reconnaissance Data on Lakes in Washington, Water-Supply Bulletin 43, Volume 1 through 7 by the United States Geological Survey in cooperation with the Washington State Department of Ecology.

Layer showing shoreline boundaries for selected lakes and reservoirs in Nebraska where bathymetric surveys were conducted. This feature class is mainly to show the waters' edge in the context of bathymetric lake mapping. The lake mapping program was developed as a cooperative initiative between the Nebraska Game and Parks Commission and the U.S. Bureau of Reclamation (BOR) to provide detailed survey information on Nebraska's lakes and reservoirs. Each year a list of proposed lakes and reservoirs is submitted by biologists across the state and reviewed by a committee to determine the lakes of highest priority. A number of factors are taken into consideration including Aquatic Habitat Projects, lake conditions, fish communities, and angler use. The overall goal of the program is to provide fisheries managers with detailed information to be used in management and monitoring of Nebraska's lakes. Detailed bathymetric lake maps are also produced and made available to the public on the NGPC web site.This shoreline data provides the outline of the lakes surveyed and contains information detailing when and where the survey was collected and how the bathymetric data was processed. The shoreline data is representative of the lakes that have been surveyed for bathymetric contours. Lakes that have not been surveyed are not part of this feature class, you may find the remaining waterbodies as well as these in the RecreationWaters dataset under PublicFishingAreas feature class.

This layer is sourced from maritimeboundaries.noaa.gov.

The ENC_Coastal map service displays ENC data within the scale range of 1:150,001 and 1:600,000. The ENC data will be updated weekly. This map service is not intended for navigation purpose.

The Unpublished Digital Geologic-GIS Map of Lake Clark National Park and Preserve and Vicinity, Alaska is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (lacl_geology.gdb), a 10.1 ArcMap (.mxd) map document (lacl_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (lacl_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.txt) and FAQ (.pdf) formats, and a GIS readme file (lacl_geology_gis_readme.pdf). Please read the lacl_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. Google Earth software is available for free at: http://www.google.com/earth/index.html. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (lacl_geology_metadata.txt or lacl_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:1584,000 and United States National Map Accuracy Standards features are within (horizontally) 804.7 meters or 2640 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm). The GIS data projection is NAD83, Alaska Albers, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Lake Clark National Park and Preserve.

The National Hydrography Dataset (NHD) is a comprehensive set of digital spatial data that contains information about surface water features such as lakes, ponds, streams, rivers, springs and wells. Within the NHD, surface water features are combined to form reaches, which provide the framework for linking water-related data to the NHD surface waterdrainage network. These linkages enable the analysis and display of these water-related data in upstream and downstream order.

The NHD is based upon the content of USGS Digital Line Graph (DLG) hydrography data integrated with reach-related information from the EPA Reach File Version 3 (RF3). The NHD supersedes DLG and RF3 by incorporating them, not by replacing them. Users of DLG or RF3 will find the National Hydrography Dataset both familiar and greatly expanded and refined.

While initially based on 1:100,000-scale data, the NHD is designed to incorporate and encourage the development of higher resolution data required by many users.

The NHD data are distributed as tarred and compressed ARC/INFO workspaces. Each workspace contains the data for a single hydrologic cataloging unit. Cataloging units are drainage basins averaging 700 square miles (1,813 square kilometers) in area. Within a workspace, there are three ARC/INFO coverages plus several related INFO tables. There is also a folder containing the metadata text files.

The NHD data support many applications, such as: making maps; geocoding observations (i.e., the means to link data to water features); modeling the flow of water along the Nation's waterways (e.g., information about the direction of flow, when combined with other data, can help users model the transport of materials in hydrographic networks, and other applications); and cooperative data maintenance.

Static flood inundation boundary extents were created along the entire shoreline of Lake Ontario in Cayuga, Jefferson, Monroe, Niagara, Orleans, Oswego, and Wayne Counties in New York by using recently acquired (2007, 2010, 2014, and 2017) light detection and ranging (lidar) data. The flood inundation maps, accessible 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 water depth of shoreline flooding in 8 segments corresponding to adjacent water-surface elevations (stages) at 8 USGS lake gages on Lake Ontario. This item includes data sets for segment B - Lake Ontario at Hamlin Beach State Park near North Hamlin, NY (station number 04220209). These datasets demonstrate the estimated extent and depth of lake flooding at specific water levels of 1-foot increments from 247.0 ft to 251.0 ft (International Great Lakes Datum of 1985). In this study, wind and seiche effects were not represented; therefore, the flood inundation maps reflect five stages for Lake Ontario that are static for the entire shoreline area of the lake. This item is a package of flood inundation data for segment B - Lake Ontario at Hamlin Beach State Park near North Hamlin, NY (station number 04220209) including: 1) 1 shapefile showing 5 estimated flood extents as polygons, 2) 5 raster datasets showing the depth of the water at 5 flood stages, 3) 1 shapefile showing the study limit extent of segment B, and 4) a metadata file. The polygon flood extent shapefiles were developed from digital elevation models (DEMs) derived from the lidar to represent the estimated areal extent for five flood stages for segment B. The raster files depict the depth, in feet, of the water in the inundated areas along the shoreline of Lake Ontario during the five theoretical flood stages. The depth grids were created by subtracting the digital elevation model (DEM) values (in feet) from each of five raster files representing the flood extent at each constant water level (in feet). An approximately 100-meter buffer was used as the extent into the lake. First posted June 21, 2021, ver 1.0 Revised November 2021, ver 2.0 Version 2.0: This version of the dataset has the same data as version 1.0, but some shapefile attributes were renamed to be more accurate and clearer, and the depth-grid rasters were renamed to include the associated water surface elevation within the raster file name. Detailed version history is included in Version_History_LakeOntarioFIMDataRelease.txt. Version 1.0: This version is a package of flood inundation data for Lake Ontario including: 1) 8 shapefiles showing 40 estimated flood extents as polygons, 2) 40 raster datasets showing the depth of the water at 5 flood stages, divided into 8 shoreline segments, 3) 8 shapefiles showing the study limit extent of each segment, and 4) a metadata file.

This geologic map database is a reproduction of U.S. Geological Survey Miscellaneous Investigations Map I–2362: “Geologic Map and Structure Sections of the Clear Lake Volcanics, Northern California” (Hearn, Donnelly-Nolan, and Goff, 1995). The database consists of a geologic map, three structural cross sections and a table of petrographic data for each map unit by mineral type, abundance, and size. The Clear Lake Volcanics are in the California Coast Ranges about 150 km north of San Francisco. This Quaternary volcanic field has erupted intermittently since 2.1 million years ago. This volcanic field is considered a high-threat volcanic system (Ewert and others, 2005). The adjacent Geysers geothermal field, the largest power-producing geothermal field in the world, is powered by the magmatic heat source for the volcanic field. The geology of parts of the area underlain by the Cache Formation is based on mapping by Rymer (1981); the geology of parts of the areas underlain by the Sonoma Volcanics, Franciscan assemblage, and Great Valley sequence is based on mapping by McLaughlin (1978). Volcanic compositional map units are basalt, basaltic andesite, andesite, dacite, rhyodacite, and rhyolite, based on SiO2 content. Most ages are potassium-argon (K/Ar) ages determined for whole-rock samples and mineral separates by Donnelly-Nolan and others (1981), unless otherwise noted. A few ages are carbon-14 ages or were estimated from geologic relationships. Magnetic polarities are from Mankinen and others (1978; 1981) or were determined in the field by B.C. Hearn, Jr., using a portable fluxgate magnetometer. Thickness for most units is estimated from topographic relief except where drill-hole data were available. This database does not reproduce all elements of the original publication. Omissions include the chart and figures showing erupted volumes of different lava types through time, and the chart and diagram for the correlation of map units. Users of this database are highly encouraged to cross reference this database with the original publication.

Heavy rainfall occurred across Louisiana during March 8-19, 2016, as a result of a massive, slow-moving southward dip in the jet stream, which moved eastward across Mexico, then neared the Gulf Coast, funneling deep tropical moisture into parts of the Gulf States and the Mississippi River Valley. The storm caused major flooding in north-central and southeastern Louisiana. Digital flood-inundation maps for a 20.1-mile reach within the community of Minden near Lake Bistineau in Bossier Parish and Bienville Parish, LA was created by the U.S. Geological Survey (USGS) in cooperation with Federal Emergency Management Agency (FEMA) to support response and recovery operations following a March 8-19, 2016 flood event. The inundation maps depict estimates of the areal extent and depth of flooding corresponding to 5 high-water marks (HWM) identified and surveyed by the USGS following the flood event.