This data release contains data used to develop models and maps that estimate the occurrence of lithium in groundwater used as drinking water throughout the conterminous United States. An extreme gradient boosting model was developed to estimate the most probable lithium concentration category (≤4, >4 to ≤10, >10 to ≤30 or >30 µg/L). The model uses lithium concentration data from wells located throughout the conterminous United States and predictor variables that are available as geospatial data. The model is included in this data release in the zipped folder named Model_Archive and was used to produce maps that are also included in this data release. The model input data (predictor variables) that were used to make the maps are within a zipped folder (Map_Input_Data.zip) that contains 20 tif-raster files, one for each model predictor variable. The map probability estimates that are outputs from the model are in a zipped folder (Map_Output_Data.zip) that contains 10 tif-raster files, two model estimate maps for each of the lithium concentration categories and the category with the highest probability for public supply well depths and domestic supply well depths.

This map layer shows areal and linear water features of the United States, Puerto Rico, and the U.S. Virgin Islands. The original file was produced by joining the individual State hydrography layers from the 1:2,000,000- scale Digital Line Graph (DLG) data produced by the USGS. This map layer was formerly distributed as Hydrography Features of the United States. This is a revised version of the January 2003 map layer.

Information on water depth in river channels is important for a number of applications in water resource management but can be difficult to obtain via conventional field methods, particularly over large spatial extents and with the kind of frequency and regularity required to support monitoring programs. Remote sensing methods could provide a viable alternative means of mapping river bathymetry (i.e., water depth). The purpose of this study was to develop and test new, spectrally based techniques for estimating water depth from satellite image data. More specifically, a neural network-based temporal ensembling approach was evaluated in comparison to several other neural network depth retrieval (NNDR) algorithms. These methods are described in a manuscript titled "Neural Network-Based Temporal Ensembling of Water Depth Estimates Derived from SuperDove Images" and the purpose of this data release is to make available the depth maps produced using these techniques. The images used as ...

USGS groundwater data, information, data, and maps for Georgia. In particular - Figure 2: Surface-water and ground-water data-collection stations in Georgia.

From site: The USGS provides maps, reports, and information to help others meet their needs to manage, develop, and protect America's water, energy, mineral, and land resources. We help find natural resources needed to build tomorrow, and supply scientific understanding needed to help minimize or mitigate the effects of natural hazards and environmental damage caused by human activities. The results of our efforts touch the daily lives of almost every American.

The Dynamic Surface Water Extent MODIS (DSWEmod) surface water maps for the conterminous United States were used for a study conducted by the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team quantifying seasonal and annual surface water trends within Environmental Protection Agency (EPA) Level I and Level III Ecoregions (Omernik, 1987) across the U.S. from 2003 through 2019. The overarching objectives of this study were to, (i) generate the monthly DSWEmod maps for the conterminous United States, (ii) review the spatial and temporal dynamics of surface water extent across ecoregions, and (iii) compare surface water area trends to streamgage discharge trends to determine where and how well different approaches to measuring water dynamics align. The DSWEmod model classifies the landscape (i.e., each 250-meter Moderate Resolution Imaging Spectroradiometer, or MODIS, pixel) into different classes of surface water based on quantified levels of confidence, including, (i) high-confidence surface water (class 1), (ii) moderate-confidence surface water (class 2), (iii) potential wetland (class 3), and (iv) low-confidence water/wetland (class 4), as well as a not-water class (class 0) and a no-data class (class 9). The confidence level is based on thresholds within various water- and vegetation-based indices. The level of confidence is based on how many, and, which index thresholds are met. Only high-confidence surface water (class 1) was considered in this study. This data release includes a vector shapefile consisting of 85 polygons, delineating EPA Level III Ecoregions for the conterminous United States. For each Level III Ecoregion, we include attributes identifying, (i) their respective Level I Ecoregion name and identification number, (ii) quantified seasonal and overall mean water area, (iii) comparisons with U.S. Geological Survey (USGS) National Water Information System (NWIS) streamgage discharge trends, (iv) mean surface water extent statistics (mean, minimum, maximum, standard deviation, coefficient of variation, percent of ecoregion), and (v) seasonal and overall results from the Mann-Kendall statistical analysis. An associated manuscript describes the methodology, results, and conclusions from this study.

This digital data set consists of contours for predevelopment water-level elevations for the High Plains aquifer in the central United States. The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude and from 96 degrees 30 minutes to 106 degrees west longitude. The outcrop area covers 174,000 square miles and is present in Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital data set was created by digitizing the contours for predevelopment water-level elevations from a 1:1,000,000-scale base map created by the U.S. Geological Survey High Plains Regional Aquifer-System Analysis (RASA) project (Gutentag, E.D., Heimes, F.J., Krothe, N.C., Luckey, R.R., and Weeks, J.B., 1984, Geohydrology of the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming: U.S. Geological Survey Professional Paper 1400-B, 63 p.) The data are not intended for use at scales larger than 1:1,000,000.

This data set consists of digital water-level-change contours for the High Plains aquifer in the central United States, 1980 to 1997. The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude and from 96 degrees 30 minutes to 104 degrees west longitude. The aquifer underlies about 174,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming.

This digital data set was created from 5,233 wells measured in both 1980 and 1997. The water-level-change contours were drawn manually on mylar at a scale of 1:1,000,000. The contours then were converted to a digital map.

The USGS compiles online access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands.

Information on water depth in river channels is important for a number of applications in water resource management but can be difficult to obtain via conventional field methods, particularly over large spatial extents and with the kind of frequency and regularity required to support monitoring programs. Remote sensing methods could provide a viable alternative means of mapping river bathymetry (i.e., water depth). The purpose of this study was to develop and test new, spectrally based techniques for estimating water depth from satellite image data. More specifically, a neural network-based temporal ensembling approach was evaluated in comparison to several other neural network depth retrieval (NNDR) algorithms. These methods are described in a manuscript titled "Neural Network-Based Temporal Ensembling of Water Depth Estimates Derived from SuperDove Images" and the purpose of this data release is to make available the depth maps produced using these techniques. The images used as input were acquired by the SuperDove cubesats comprising the PlanetScope constellation, but the original images cannot be redistributed due to licensing restrictions; the end products derived from these images are provided instead. The large number of cubesats in the PlanetScope constellation allows for frequent temporal coverage and the neural network-based approach takes advantage of this high density time series of information by estimating depth via one of four NNDR methods described in the manuscript: 1. Mean-spec: the images are averaged over time and the resulting mean image is used as input to the NNDR. 2. Mean-depth: a separate NNDR is applied independently to each image in the time series and the resulting time series of depth estimates is averaged to obtain the final depth map. 3. NN-depth: a separate NNDR is applied independently to each image in the time series and the resulting time series of depth estimates is then used as input to a second, ensembling neural network that essentially weights the depth estimates from the individual images so as to optimize the agreement between the image-derived depth estimates and field measurements of water depth used for training; the output from the ensembling neural network serves as the final depth map. 4. Optimal single image: a separate NNDR is applied independently to each image in the time series and only the image that yields the strongest agreement between the image-derived depth estimates and the field measurements of water depth used for training is used as the final depth map. MATLAB (Version 24.1, including the Deep Learning Toolbox) for performing this analysis is provided in the function NN_depth_ensembling.m available on the main landing page for the data release of which this is a child item, along with a flow chart illustrating the four different neural network-based depth retrieval methods. To develop and test this new NNDR approach, the method was applied to satellite images from the American River near Fair Oaks, CA, acquired in October 2020. Field measurements of water depth available through another data release (Legleiter, C.J., and Harrison, L.R., 2022, Field measurements of water depth from the American River near Fair Oaks, CA, October 19-21, 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P92PNWE5) were used for training and validation. The depth maps produced via each of the four methods described above are provided as GeoTIFF files, with file name suffixes that indicate the method employed: American_mean-spec.tif, American_mean-depth.tif, American_NN-depth.tif, and American-single-image.tif. The spatial resolution of the depth maps is 3 meters and the pixel values within each map are water depth estimates in units of meters.

This web map was created to show 30 surface water plants within the State of Florida. The full version, Public Water Supply Plants, can be viewed within FDEP's Geospatial Open Data website http://geodata.dep.state.fl.us/datasets/public-water-supply-pws-plants-non-federal. For general questions, please contact the Source & Drinking Water Program:Source and Drinking Water Program2600 Blair Stone RoadMS 3520Tallahassee, Florida 32399-2400Call: 850-245-8624 / Fax: 850-245-8669

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

This dataset provides maps of tidal marsh green vegetation, non-vegetation, and open water for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD, Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Maps were derived from current National Agriculture Imagery Program data (2013-2015) using object-based classification for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program (C-CAP) map. These 1m resolution maps were used to calculate the fraction of green vegetation within 30m Landsat pixels for the same tidal marsh regions and these data are provided in a related dataset.

Named Waterbody is a 1:24,000-scale, polygon and line feature-based layer that includes all named waterbodies depicted on the U.S. Geological Survey (USGS) 7.5 minute topographic quadrangle maps for the State of Connecticut. This layer only includes features located in Connecticut. Named Waterbody features include water, dams, flow connectors, aqueducts, canals, ditches, shorelines, and islands. The layer does not include the marsh areas, tidal flats, rocks, shoals, or channels typically shown on USGS 7.5 minute topographic quadrangle maps. However, the layer includes linear (flow) connector features that fill in gaps between river and stream features where water passes through marshes or underground through pipelines and tunnels. Note that connectors represent general pathways and do not represent the exact location or orientation of actual underground pipelines, tunnels, aqueducts, etc. The Named Waterbody layer is comprised of polygon and line features. Polygon features represent areas of water for rivers, streams, brooks, reservoirs, lakes, ponds, bays, coves, and harbors. Polygon features also depict related information such as dams and islands. Line features represent single-line rivers and streams, flow connectors, aqueducts, canals, and ditches. Line features also enclose all polygon features in the form of shorelines, dams, and closure lines separating adjacent water features. The Named Waterbody layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 so it does not depict conditions at any one particular point in time. Also, the layer does not reflect recent changes with the course of streams or location of shorelines impacted by natural events or changes in development since the time the USGS 7.5 minute topographic quadrangle maps were published. Attribute information is comprised of codes to identify waterbody features by type, cartographically represent (symbolize) waterbody features on a map, select waterbodies appropriate to display at different map scales, identify individual waterbodies on a map by name, and describe waterbody feature area and length. The names assigned to individual waterbodies are based on information published on the USGS 7.5 minute topographic quadrangle maps or other state and local maps. The Named Waterbody layer does not include bathymetric, stream gradient, water flow, water quality, or biological habitat information. Derived from the Hydrography layer, the Named Waterbody layer was originally published in 1999. The 2005 edition includes the same water features published in 1999, however some attribute information has been slightly modified and made easier to use. Also, the 2005 edition corrects previously undetected attribute coding errors and includes the flow connector features. Connecticut Named Waterbody Polygon includes the polygon features of a layer named Named Waterbody. Named Waterbody is a 1:24,000-scale, polygon and line feature-based layer that includes all named waterbodies depicted on the U.S. Geological Survey (USGS) 7.5 minute topographic quadrangle maps for the State of Connecticut. This layer only includes features located in Connecticut. Named Waterbody features include water, dams, flow connectors, aqueducts, canals, ditches, shorelines, and islands. The layer does not include the marsh areas, tidal flats, rocks, shoals, or channels typically shown on USGS 7.5 minute topographic quadrangle maps. However, the layer includes linear (flow) connector features that fill in gaps between river and stream features where water passes through marshes or underground through pipelines and tunnels. Note that connectors represent general pathways and do not represent the exact location or orientation of actual underground pipelines, tunnels, aqueducts, etc. The Named Waterbody layer is comprised of polygon and line features. Polygon features represent areas of water for rivers, streams, brooks, reservoirs, lakes, ponds, bays, coves, and harbors. Polygon features also depict related information such as dams and islands. Line features represent single-line rivers and streams, flow connectors, aqueducts, canals, and ditches. Line features also enclose all polygon features in the form of shorelines, dams, and closure lines separating adjacent water features. The Named Waterbody layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 so it does not depict conditions at any one particular point in time. Also, the layer does not reflect recent changes with the course of streams or location of shorelines impacted by natural events or changes in development since the time the USGS 7.5 minute topographic quadrangle maps were published. Attribute information is comprised of codes to identify waterbody features by type, cartographically represent (symbolize) waterbody features on a map, select waterbodies appropriate to display at different map scales, identify individual waterbodies on a map by name, and describe waterbody feature area and length. The names assigned to individual waterbodies are based on information published on the USGS 7.5 minute topographic quadrangle maps or other state and local maps. The Named Waterbody layer does not include bathymetric, stream gradient, water flow, water quality, or biological habitat information. Derived from the Hydrography layer, the Named Waterbody layer was originally published in 1999. The 2005 edition includes the same water features published in 1999, however some attribute information has been slightly modified and made easier to use. Also, the 2005 edition corrects previously undetected attribute coding errors and includes the flow connector features.

This is a running list of all water quality complaint types logged in Hansen.

Map Direct focus for viewing GWIS data. Please refer to http://gwis.dep.state.fl.us/ for more information (DEP login is required). Originally created on 12/07/2006, and moved to Map Direct Lite on 03/17/2015. Please contact GIS.Librarian@floridadep.gov for more information.

The maritime limits and boundaries of the U.S., found in the A-16 National Geospatial Data Asset Portfolio, is recognized as the low-water line along the coast measured from the U.S. baseline. This is marked on official U.S. nautical charts in accordance with the articles of the Law of the Sea. The baseline and related maritime limits are reviewed and approved by the inter-agency U.S. Baseline Committee.The primary purpose of this data is to update the official depiction of these maritime limits and boundaries on the National Oceanic and Atmospheric Administration's nautical charts. The Office of Coast Survey depicts on its nautical charts the territorial sea (12 nautical miles), contiguous zone (24 nautical miles), and Exclusive Economic Zone (200 nautical miles, plus maritime boundaries with adjacent/opposite countries). U.S. maritime limits are ambulatory and are subject to revision based on accretion or erosion of the charted low-water line. For more information about U.S. maritime limits and boundaries and to download data, see U.S. Maritime Limits & Boundaries. For the full Federal Geographic Data Committee metadata record, see Maritime Limits and Boundaries of United States of America.Thumbnail source image courtesy of: David Restivo

The sea level rise (SLR) coastal inundation layers were created using existing federal products: the (1) NOAA Coastal Digital Elevation Models (DEMs) and (2) 2022 Interagency Sea Level Rise Technical Report Data Files. The DEMs for the Continental United States (CONUS) are provided in North American Vertical Datum 1988 (NAVD 88) and were converted to Mean Higher High Water (MHHW) using the NOAA VDatum conversion surfaces; the elevation values are in meters (m). The NOAA Scenarios of Future Mean Sea Level are provided in centimeters (cm). The MHHW DEMs for CONUS were merged and converted to cm and Scenarios of Future Mean Sea Level were subtracted from the merged DEM. Values below 0 represent areas that are below sea level and are “remapped” to 1, all values above 0 are remapped to “No Data”, creating a map that shows only areas impacted by SLR. Areas protected by levees in Louisiana and Texas were then masked or removed from the results. This was done for each of the emissions scenarios (Lower Emissions = 2022 Intermediate SLR Scenario Higher Emissions = 2022 Intermediate High SLR Scenario) at each of the mapped time intervals (Early Century - Year 2030, Middle Century - Year 2050, and Late Century - Year 2090). The resulting maps are displayed in the CMRA Assessment Tool. County, tract, and tribal geographies summaries of percentage SLR inundation were also calculated using Zonal Statistics tools. The Sea Level Rise Scenario year 2020 is considered “baseline” and the impacts are calculated by subtracting the baseline value from each of the near-term, mid-term and long-term timeframes. General Disclaimer The data and maps in this tool illustrate the scale of potential flooding, not the exact location, and do not account for erosion, subsidence, or future construction. Water levels are relative to Mean Higher High Water (MHHW) (excludes wind driven tides). The data, maps, and information provided should be used only as a screening-level tool for management decisions. As with all remotely sensed data, all features should be verified with a site visit. Hydroconnectivity was not considered in the mapping process. The data and maps in this tool are provided “as is,” without warranty to their performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of these data is assumed by the user. This tool should be used strictly as a planning reference tool and not for navigation, permitting, or other legal purposes. SLR visualizations and statistics are not available in CMRA for Hawaii, Alaska, or U.S. territories at this time. Levees Disclaimer Enclosed levee areas are displayed as gray areas on the maps. Major federal leveed areas were assumed high enough and strong enough to protect against inundation depicted in this viewer, and therefore no inundation was mapped in these regions. Major federal leveed areas were taken from the National Levee Database. Minor (nonfederal) leveed areas were mapped using the best available elevation data that capture leveed features. In some cases, however, breaks in elevation occur along leveed areas because of flood control features being removed from elevation data, limitations of the horizontal and vertical resolution of the elevation data, the occurrence of levee drainage features, and so forth. Flooding behind levees is only depicted if breaks in elevation data occur or if the levee elevations are overtopped by the water surface. At some flood levels, alternate pathways around—not through—levees, walls, dams, and flood gates may exist that allow water to flow into areas protected at lower levels. In general, imperfect levee and elevation data make assessing protection difficult, and small data errors can have large consequences. Citations 2022 Sea Level Rise Technical Report - Sweet, W.V., B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, and C. Zuzak, 2022: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines. NOAA Technical Report NOS 01. National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nostechrpt01-global-regional-SLR-scenarios-US.pdf

The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses. For more information on the NHDPlus dataset see the NHDPlus v2 User Guide.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territories not including Alaska.Geographic Extent: The United States not including Alaska, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: EPA and USGSUpdate Frequency: There is new new data since this 2019 version, so no updates planned in the futurePublication Date: March 13, 2019Prior to publication, the NHDPlus network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the NHDPlus Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, On or Off Network (flowlines only), Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original NHDPlus dataset. No data values -9999 and -9998 were converted to Null values for many of the flowline fields.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute. Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map. Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Ge ...

USGS Topo is a topographic tile cache base map service visible from world scale to 1:18,000 that combines the most current data (Boundaries, Elevation, Geographic Names, Hydrography, Land Cover, Structures, Transportation, and other themes) that make up The National Map. Contours generated for the US Topo product are included and are visible at 1:36:000 and 1:18,000 scales. This service is designed to provide a seamless view of the data in a geographic information system (GIS) accessible format, closely resembling the US Topo product at large scales.