The United States and its territories have a total area of more than 3.8 million square miles - of this, 269,717 square miles (around seven percent of the total) is made up of water area, such as rivers, lakes, and inlets, as well as territorial waters along the coast.

Alaska, the largest state, has the largest water area by a significant margin, at almost 95,000 square miles (35 percent of the country's total). This is followed by Michigan, which has over 40,000 square miles of water area - the majority of this comes form the Great Lakes, as large shares of Lake Huron, Lake Michigan, and Lake Superior fall within Michigan's boundaries.

This statistic shows the total land and water area of the United States by state and territory. Alabama covers an area of 52,420 square miles.

Idaho had one of the largest per capita uses of the public water supply in the United States, totaling 184 gallons per day, followed by Utah with 169 gallons and Wyoming at 156 gallons. The public supply of water refers to water that is withdrawn by both public and private suppliers and is delivered to domestic, commercial, thermoelectric, irrigation, and industrial users. Overall, the most populous states tend to be the largest consumers of water. Sources of public supply water can include desalinated seawater and treated brackish groundwater. California and Texas withdrew 5.15 billion gallons and 2.89 billion gallons per day, respectively, for public supply in 2015. Almost 90 percent of the U.S. population relies on public water supplies.

U.S. Water Consumption Water withdrawal in the United States has increased over the last decades, reaching 322 billion gallons per day in 2015. The U.S. is one of the largest per capita consumers water in the world, in addition to being one of the largest absolute consumers of water. The average U.S. family uses some 400 gallons of water per day. However, a large share of water is lost or wasted through leaky pipes or just evaporation and over-watering landscapes. Minor changes such as fixing a leaky faucet, using a dishwasher, upgrading to a water-efficient toilet, or taking showers instead of baths can help save conserve water.

In 2023, around 91 percent of the water supplied to American Water's customers in Pennsylvania was sourced from surface water. Surface water is collected from bodies of water found on the surface of the earth, such as rivers and lakes. In comparison, California was heavily more reliant on groundwater and purchased water. Ground water is extracted from below the Earth's surface between rocks and soil. California is reliant on this type of water source due to the dryness of the state, with concerns rising over the increased occurrence of droughts. Groundwater is most used in agriculture in California, especially in the dry farmlands of the San Juan Valley, where increasing groundwater pumping for irrigation has led to the area sinking as much as two meters in recent years.

The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across the census block-group, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations in order to more precisely locate public supply users. This dataset consists of the total estimated population using public supply surface water and groundwater combined, distributed using the urban land-use enhanced method.

This layer provides an estimate of flood frequency as one of seven classes:

None: No reasonable possibility of flooding; one chance out of 500 of flooding in any year or less than 1 time in 500 years.Very Rare: Flooding is very unlikely but is possible under extremely unusual weather conditions; less than 1 percent chance of flooding in any year or less than 1 time in 100 years but more than 1 time in 500 years.Rare: Flooding is unlikely but is possible under unusual weather conditions; 1 to 5 percent chance of flooding in any year or nearly 1 to 5 times in 100 years.Occasional: Flooding is expected infrequently under usual weather conditions; 5 to 50 percent chance of flooding in any year or 5 to 50 times in 100 years.Common: (Obsolete Class) Combination of Occasional and FrequentFrequent: Flooding is likely to occur often under usual weather conditions; more than a 50 percent chance of flooding in any year (i.e., 50 times in 100 years), but less than a 50 percent chance of flooding in all months in any year.Very Frequent: Flooding is likely to occur very often under usual weather conditions; more than a 50 percent chance of flooding in all months of any year.Dataset SummaryPhenomenon Mapped: Flooding frequencyUnits: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: WKID 5070 USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WKID 3338 WGS 1984 Albers (Alaska), WKID 4326 WGS 1984 Decimal Degrees (Guam, Republic of the Marshall Islands, Northern Mariana Islands, Republic of Palau, Federated States of Micronesia, American Samoa, and Hawaii).Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Northern Mariana Islands, Republic of Palau, Republic of the Marshall Islands, Federated States of Micronesia, and American Samoa.Source: Natural Resources Conservation ServicePublication Date: November 2023ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the for the contiguous United States and Alaska. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Puerto Rico, the U.S. Virgin Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, Republic of the Marshall Islands, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for flooding frequency is derived from the gSSURGO map unit aggregated attribute table field Flooding Frequency - Dominant Condition (flodfreqdcd).What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "flooding frequency" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "flooding frequency" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Water quality data can be downloaded in Excel, CSV, TSV, and KML formats. Fourteen site types are found in the WQP: aggregate groundwater use, aggregate surface water use, atmosphere, estuary, facility, glacier, lake, land, ocean, spring, stream, subsurface, well, and wetland. Water quality characteristic groups include physical conditions, chemical and bacteriological water analyses, chemical analyses of fish tissue, taxon abundance data, toxicity data, habitat assessment scores, and biological index scores, among others. Within these groups, thousands of water quality variables registered in the EPA Substance Registry Service (https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do) and the Integrated Taxonomic Information System (https://www.itis.gov/) are represented. Across all site types, physical characteristics (e.g., temperature and water level) are the most common water quality result type in the system. The Water Quality Exchange data model (WQX; http://www.exchangenetwork.net/data-exchange/wqx/), initially developed by the Environmental Information Exchange Network, was adapted by EPA to support submission of water quality records to the EPA STORET Data Warehouse [USEPA, 2016], and has subsequently become the standard data model for the WQP. Contributing organizations: ACWI The Advisory Committee on Water Information (ACWI) represents the interests of water information users and professionals in advising the federal government on federal water information programs and their effectiveness in meeting the nation's water information needs. ARS The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief in-house scientific research agency, whose job is finding solutions to agricultural problems that affect Americans every day, from field to table. ARS conducts research to develop and transfer solutions to agricultural problems of high national priority and provide information access and dissemination to, among other topics, enhance the natural resource base and the environment. Water quality data from STEWARDS, the primary database for the USDA/ARS Conservation Effects Assessment Project (CEAP) are ingested into WQP via a web service. EPA The Environmental Protection Agency (EPA) gathers and distributes water quality monitoring data collected by states, tribes, watershed groups, other federal agencies, volunteer groups, and universities through the Water Quality Exchange framework in the STORET Warehouse. NWQMC The National Water Quality Monitoring Council (NWQMC) provides a national forum for coordination of comparable and scientifically defensible methods and strategies to improve water quality monitoring, assessment, and reporting. It also promotes partnerships to foster collaboration, advance the science, and improve management within all elements of the water quality monitoring community. USGS The United States Geological Survey (USGS) investigates the occurrence, quantity, quality, distribution, and movement of surface waters and ground waters and disseminates the data to the public, state, and local governments, public and private utilities, and other federal agencies involved with managing the United States' water resources. Resources in this dataset:Resource Title: Website Pointer for Water Quality Portal. File Name: Web Page, url: https://www.waterqualitydata.us/ The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Links to Download Data, User Guide, Contributing Organizations, National coverage by state.

The United States is the largest producer of goods and services in the world. Rainfall, surface water supplies, and groundwater aquifers represent a fundamental input to economic production. Despite the importance of water resources to economic activity, we do not have consistent information on water use for specific locations and economic sectors. A national, spatially detailed database of water use by sector would provide insight into U.S. utilization and dependence on water resources for economic production. To this end, we calculate the water footprint of over 500 food, energy, mining, services, and manufacturing industries and goods produced in the United States. To do this, we employ a data intensive approach that integrates water footprint and input-output techniques into a novel methodological framework. This approach enables us to present the most detailed and comprehensive water footprint analysis of any country to date. This study broadly contributes to our understanding of water in the U.S. economy, enables supply chain managers to assess direct and indirect water dependencies, and provides opportunities to reduce water use through benchmarking. In fact, we find that 94% of U.S. industries could reduce their total water footprint more by sourcing from more water-efficient suppliers in their supply chain than they could by converting their own operations to be more water-efficient.

Represents the borders for the Southwest Water Pipeline (SWPP), Northwest Area Water Supply (NAWS), and the Western Area Water Supply (WAWS) projects and service areas

Constraints:
Not to be used for navigation, for informational purposes only. See full disclaimer for more information

Class I and II surface water classification boundaries. The Clean Water Act requires that the surface waters of each state be classified according to designated uses. Florida has six classes with associated designated uses, which are arranged in order of degree of protection required: Class I - Potable Water Supplies Fourteen general areas throughout the state including: impoundments and associated tributaries, certain lakes, rivers, or portions of rivers, used as a drinking water supply. Class II - Shellfish Propagation or Harvesting Generally coastal waters where shellfish harvesting occurs. For a more detailed description of classes and specific waterbody designations, see 62-302.400.

This dataset captures in digital form previously published maps showing the inferred extent and subsurface elevation of several Paleozoic consolidated rock units in the northern Midwest of the United States. Data released here were published as figures within a U.S. Geological Survey (USGS) Water Mission Area report documenting results from a study of the regional hydrogeology and ground-water quality of the Cambrian-Ordovician aquifer system in the northern Midwest. This study was part of the USGS national Regional Aquifer-System Analysis (RASA) Program. Sandstone and carbonate rocks of Cambrian and Ordovician age compose much of the sedimentary rocks overlying the Precambrian basement in the northern Midwest and form the major aquifer system of that area, named the Cambrian-Ordovician aquifer system by the USGS RASA Program. This aquifer system underlies about 161,000 mi2 (square miles) in northern Illinois, northwestern Indiana, Iowa, southeastern Minnesota, northern Missouri, and Wisconsin. The published USGS RASA investigation defined the subsurface extent and altitude of the top of eight stratigraphic intervals within the lower Paleozoic consolidated rocks, typically including a major named formation or group plus its regional stratigraphic equivalents. Major mapped intervals include, from lowest to highest, the Upper Cambrian Mount Simon Sandstone, Eau Claire Formation, Ironton and Galesville Sandstones, and St. Lawrence and Franconia Formations, Lower Ordovician Prairie du Chien Group, Middle Ordovician St. Peter Sandstone and Galena Dolomite, and the Upper Ordovician Maquoketa Shale. The USGS RASA study also included maps of the contoured top of Precambrian rocks, top of combined Middle Devonian through Silurian rocks, and top of combined Pennsylvanian, Mississippian, and Upper Devonian rocks; these maps were also digitized and are included in this data release. This dataset includes vector structure contour data digitized from page-sized figures in USGS Professional Paper 1405-B (Young, 1992). Some maps from this report had previously been digitized by a USGS saline groundwater assessment project and released as digital datasets on the USGS Water Mission Area’s National Spatial Data Infrastructure (NSDI) node (U.S. Geological Survey, 2015). For consistency and completeness, those data have been reformatted, attributed, and assembled with additional data digitized from the source RASA report for this data release. The dataset includes a geographic information system geodatabase that contain digital structure contour data as polyline feature classes for all of the geologic units contoured in USGS Professional Paper 1405-B (Young, 1992). Vector data are attributed according to the USGS National Cooperative Geologic Mapping Program’s GeMS digital geologic map schema. The geodatabase includes non-spatial tables that describe the sources of geologic information, a glossary of terms, a description of units, and a geomaterials dictionary. Also included is a Data Dictionary that duplicates the Entity and Attribute information contained in the metadata file. To maximize usability, spatial data are also distributed as shapefiles and tabular data are distributed as ascii text files in comma separated values (CSV) format.

IntroductionClimate Central’s Surging Seas: Risk Zone map shows areas vulnerable to near-term flooding from different combinations of sea level rise, storm surge, tides, and tsunamis, or to permanent submersion by long-term sea level rise. Within the U.S., it incorporates the latest, high-resolution, high-accuracy lidar elevation data supplied by NOAA (exceptions: see Sources), displays points of interest, and contains layers displaying social vulnerability, population density, and property value. Outside the U.S., it utilizes satellite-based elevation data from NASA in some locations, and Climate Central’s more accurate CoastalDEM in others (see Methods and Qualifiers). It provides the ability to search by location name or postal code.The accompanying Risk Finder is an interactive data toolkit available for some countries that provides local projections and assessments of exposure to sea level rise and coastal flooding tabulated for many sub-national districts, down to cities and postal codes in the U.S. Exposure assessments always include land and population, and in the U.S. extend to over 100 demographic, economic, infrastructure and environmental variables using data drawn mainly from federal sources, including NOAA, USGS, FEMA, DOT, DOE, DOI, EPA, FCC and the Census.This web tool was highlighted at the launch of The White House's Climate Data Initiative in March 2014. Climate Central's original Surging Seas was featured on NBC, CBS, and PBS U.S. national news, the cover of The New York Times, in hundreds of other stories, and in testimony for the U.S. Senate. The Atlantic Cities named it the most important map of 2012. Both the Risk Zone map and the Risk Finder are grounded in peer-reviewed science.Back to topMethods and QualifiersThis map is based on analysis of digital elevation models mosaicked together for near-total coverage of the global coast. Details and sources for U.S. and international data are below. Elevations are transformed so they are expressed relative to local high tide lines (Mean Higher High Water, or MHHW). A simple elevation threshold-based “bathtub method” is then applied to determine areas below different water levels, relative to MHHW. Within the U.S., areas below the selected water level but apparently not connected to the ocean at that level are shown in a stippled green (as opposed to solid blue) on the map. Outside the U.S., due to data quality issues and data limitations, all areas below the selected level are shown as solid blue, unless separated from the ocean by a ridge at least 20 meters (66 feet) above MHHW, in which case they are shown as not affected (no blue).Areas using lidar-based elevation data: U.S. coastal states except AlaskaElevation data used for parts of this map within the U.S. come almost entirely from ~5-meter horizontal resolution digital elevation models curated and distributed by NOAA in its Coastal Lidar collection, derived from high-accuracy laser-rangefinding measurements. The same data are used in NOAA’s Sea Level Rise Viewer. (High-resolution elevation data for Louisiana, southeast Virginia, and limited other areas comes from the U.S. Geological Survey (USGS)). Areas using CoastalDEM™ elevation data: Antigua and Barbuda, Barbados, Corn Island (Nicaragua), Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Blas (Panama), Suriname, The Bahamas, Trinidad and Tobago. CoastalDEM™ is a proprietary high-accuracy bare earth elevation dataset developed especially for low-lying coastal areas by Climate Central. Use our contact form to request more information.Warning for areas using other elevation data (all other areas)Areas of this map not listed above use elevation data on a roughly 90-meter horizontal resolution grid derived from NASA’s Shuttle Radar Topography Mission (SRTM). SRTM provides surface elevations, not bare earth elevations, causing it to commonly overestimate elevations, especially in areas with dense and tall buildings or vegetation. Therefore, the map under-portrays areas that could be submerged at each water level, and exposure is greater than shown (Kulp and Strauss, 2016). However, SRTM includes error in both directions, so some areas showing exposure may not be at risk.SRTM data do not cover latitudes farther north than 60 degrees or farther south than 56 degrees, meaning that sparsely populated parts of Arctic Circle nations are not mapped here, and may show visual artifacts.Areas of this map in Alaska use elevation data on a roughly 60-meter horizontal resolution grid supplied by the U.S. Geological Survey (USGS). This data is referenced to a vertical reference frame from 1929, based on historic sea levels, and with no established conversion to modern reference frames. The data also do not take into account subsequent land uplift and subsidence, widespread in the state. As a consequence, low confidence should be placed in Alaska map portions.Flood control structures (U.S.)Levees, walls, dams or other features may protect some areas, especially at lower elevations. Levees and other flood control structures are included in this map within but not outside of the U.S., due to poor and missing data. Within the U.S., data limitations, such as an incomplete inventory of levees, and a lack of levee height data, still make assessing protection difficult. For this map, levees are assumed high and strong enough for flood protection. However, it is important to note that only 8% of monitored levees in the U.S. are rated in “Acceptable” condition (ASCE). Also note that the map implicitly includes unmapped levees and their heights, if broad enough to be effectively captured directly by the elevation data.For more information on how Surging Seas incorporates levees and elevation data in Louisiana, view our Louisiana levees and DEMs methods PDF. For more information on how Surging Seas incorporates dams in Massachusetts, view the Surging Seas column of the web tools comparison matrix for Massachusetts.ErrorErrors or omissions in elevation or levee data may lead to areas being misclassified. Furthermore, this analysis does not account for future erosion, marsh migration, or construction. As is general best practice, local detail should be verified with a site visit. Sites located in zones below a given water level may or may not be subject to flooding at that level, and sites shown as isolated may or may not be be so. Areas may be connected to water via porous bedrock geology, and also may also be connected via channels, holes, or passages for drainage that the elevation data fails to or cannot pick up. In addition, sea level rise may cause problems even in isolated low zones during rainstorms by inhibiting drainage.ConnectivityAt any water height, there will be isolated, low-lying areas whose elevation falls below the water level, but are protected from coastal flooding by either man-made flood control structures (such as levees), or the natural topography of the surrounding land. In areas using lidar-based elevation data or CoastalDEM (see above), elevation data is accurate enough that non-connected areas can be clearly identified and treated separately in analysis (these areas are colored green on the map). In the U.S., levee data are complete enough to factor levees into determining connectivity as well.However, in other areas, elevation data is much less accurate, and noisy error often produces “speckled” artifacts in the flood maps, commonly in areas that should show complete inundation. Removing non-connected areas in these places could greatly underestimate the potential for flood exposure. For this reason, in these regions, the only areas removed from the map and excluded from analysis are separated from the ocean by a ridge of at least 20 meters (66 feet) above the local high tide line, according to the data, so coastal flooding would almost certainly be impossible (e.g., the Caspian Sea region).Back to topData LayersWater Level | Projections | Legend | Social Vulnerability | Population | Ethnicity | Income | Property | LandmarksWater LevelWater level means feet or meters above the local high tide line (“Mean Higher High Water”) instead of standard elevation. Methods described above explain how each map is generated based on a selected water level. Water can reach different levels in different time frames through combinations of sea level rise, tide and storm surge. Tide gauges shown on the map show related projections (see just below).The highest water levels on this map (10, 20 and 30 meters) provide reference points for possible flood risk from tsunamis, in regions prone to them.

The National Water Quality Network (NWQN) for Rivers and Streams includes 113 surface-water river and stream sites monitored by the U.S. Geological Survey (USGS) National Water Quality Program (NWQP). The NWQN represents the consolidation of four historical national networks: the USGS National Water-Quality Assessment (NAWQA) Project, the USGS National Stream Quality Accounting Network (NASQAN), the National Monitoring Network (NMN), and the Hydrologic Benchmark Network (HBN). The NWQN includes 22 large river coastal sites, 41 large river inland sites, 30 wadeable stream reference sites, 10 wadeable stream urban sites, and 10 wadeable stream agricultural sites. In addition to the 113 NWQN sites, 3 large inland river monitoring sites from the USGS Cooperative Matching Funds (Co-op) program are also included in this annual water-quality reporting Web site to be consistent with previous USGS studies of nutrient transport in the Mississippi-Atchafalaya River Basin. This data release contains geo-referenced digital data and associated attributes of watershed boundaries for 113 NWQN and 3 Co-op sites. Two sites, "Wax Lake Outlet at Calumet, LA"; 07381590, and "Lower Atchafalaya River at Morgan City, LA"; 07381600, are outflow distributaries into the Gulf of Mexico. Watershed boundaries were delineated for the portion of the watersheds between "Red River near Alexandria, LA"; 07355500 and "Atchafalaya River at Melville, LA"; 07381495 to the two distributary sites respectively. Drainage area was undetermined for these two distributary sites because the main stream channel outflows into many smaller channels so that streamflow is no longer relative to the watershed area. NWQN watershed boundaries were derived from the Watershed Boundary Dataset-12-digit hydrologic units (WBD-12). The development of the WBD-12 was a coordinated effort between the United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS), the USGS, and the Environmental Protection Agency (EPA) (U.S. Department of Agriculture-Natural Resources Conservation Service, 2012). A hydrologic unit is a drainage area delineated to nest in a multi-level, hierarchical drainage system. Its boundaries are defined by hydrographic and topographic criteria that delineate an area of land upstream from a specific point on a river, stream or similar surface waters. The United States is divided and sub-divided into successively smaller hydrologic units identified by a unique hydrologic unit code (HUC) consisting of two to 12 digits based on the six levels of classification in the hydrologic unit system: regions, sub-regions, accounting units, cataloging units, watersheds, and sub-watersheds. NWQN watershed boundaries were delineated by selecting all sub-watershed polygons that flow into the most downstream WBD-12 polygon in which the NWQN site is located. The WBD-12 attribute table contains 8-digit, 10-digit, and 12-digit HUCs which were used to identify which sub-watersheds flow into the watershed pour point at the NWQN site location. When the NWQN site was located above the pour point of the most downstream sub-watershed, the sub-watershed was edited to make the NWQN site the pour point of that sub-watershed. To aid editing, USGS 1:24,000 digital topographic maps were used to determine the hydrologic divide from the sub-watershed boundary to the NWQN pour point. The number of sub-watersheds which are contained within the NWQN watersheds ranged from less than one to nearly 32,000 internal sub-watersheds. Internal sub-watershed boundaries were dissolved so that a single watershed boundary was generated for each NWQN watershed. Data from this release are presented at the USGS Tracking Water Quality page: http://cida.usgs.gov/quality/rivers/home (Deacon and others, 2015). Watershed boundaries delineated for this release do not take into account non-contributing area, diversions out of the watershed, or return flows into the watershed. Delineations are based solely on contributing WBD-12 polygons with modifications done only to the watershed boundary at the NWQN site location pour point. For this reason calculated drainage areas for these delineated watersheds may not match National Water Information System (MWIS) published drainage areas (http://dx.doi.org/10.5066/F7P55KJN). Deacon, J.R., Lee, C.J., Toccalino, P.L., Warren, M.P., Baker, N.T., Crawford, C.G., Gilliom, R.G., and Woodside, M.D., 2015, Tracking water-quality of the Nation’s rivers and streams, U.S. Geological Survey Web page: http://cida.usgs.gov/quality/rivers, https://dx.doi.org/doi:10.5066/F70G3H51. U.S. Department of Agriculture-Natural Resources Conservation Service, 2012, Watershed Boundary Dataset-12-digit hydrologic units: NRCS National Cartography and Geospatial Center, Fort Worth, Tex., WBDHU12_10May2012_9.3 version, accessed June 2012 at http://datagateway.nrcs.usda.gov.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Census Bureau includes landmarks in the MTDB for locating special features and to help enumerators during field operations. Some of the more common landmark types include area landmarks such as airports, cemeteries, parks, schools, and churches and other religious institutions. The Census Bureau added landmark features to MTDB on an as-needed basis and made no attempt to ensure that all instances of a particular feature were included. The presence or absence of a landmark such as a hospital or prison does not mean that the living quarters associated with that landmark were geocoded to that census tabulation block or excluded from the census enumeration. The Area Landmark Shapefile does not include military installations or water bodies because they each appear in their own separate shapefiles, MIL.shp and AREAWATER.shp respectively.

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.

These sets of data include the drinking water supply management area boundaries and the vulnerability levels within each management area in Minnesota.

More information can be found at:
https://www.health.state.mn.us/communities/environment/water/swp/reqrec.html

Follow the links below to the access the individual metadata pages for each layer:

Drinking Water Supply Management Areas: drinking_water_supply_management_areas.html

Drinking Water Supply Management Areas Vulnerability: drinking_water_supply_management_area_vulnerability.html

Over the past 15 years Douglas County, NV has removed production wells in northern Carson Valley from use due to relatively high arsenic concentrations (Carl Ruschmeyer, January 2013, Douglas County Public Works Director, verbal communication). To maintain the supply of water to the public, the town of Minden has been providing water to Douglas County and Carson City. Due to the projected increases in municipal demand, water resource managers are concerned that increasing pumping rates from wells in Minden may change groundwater chemistry and degrade the resource by potentially drawing in arsenic enriched water. Long-term exposure to arsenic can cause illnesses ranging from skin discoloration to various cancers including those of the bladder, skin, and kidney (U.S. Environmental Protection Agency, 2001). Naturally occurring arsenic is one of the most common contaminants in groundwater in the western United States. Arsenic found in basin-fill aquifers is oftentimes associated with alluvial/lacustrine sedimentary deposits derived from the weathering of volcanic rocks and geothermal waters (Welch and others, 1988). The primary aquifers beneath Carson Valley are comprised of quaternary aged basin-fill deposits of weathered granitic and volcanic material (Welch, 1994). Factors contributing to increasing arsenic concentrations in groundwater include, but are not limited to, proximity to arsenic bearing rocks, relatively long groundwater flow paths, the application of phosphate containing fertilizers, and leaching from soils in irrigated areas (Busbee and others, 2009; Anning and others, 2012). The vulnerability of groundwater resources to contamination is influenced by the physical properties of the aquifer, pumping rates, locations of wells and screened intervals relative to the groundwater flow system, and geochemical environment (Focazio and others, 2006). Arsenic mobility and transport through the subsurface is largely controlled by the interaction of groundwater with aquifer sediments. Arsenite (As(III)), the reduced form of inorganic arsenic, usually exhibits greater mobility in groundwater than the oxidized form, arsenate (As(V)) largely due to the greater attraction of As(V) to aquifer sediments relative to that of As(III) at pH values exceeding 8.5 (Smedley and Kinniburgh, 2002). Arsenic speciation (form) is influenced by the relative redox condition of the aquifer environment. For example, in the vicinity of the Douglas County Airport, where arsenic speciation has been characterized, arsenic in groundwater collected at depths greater than 250 feet below land surface was found to be primarily As(III); however, in the upper 150 feet of the aquifer As(V) predominated (Paul and others, 2010). This data set provides a spatial and temporal assessment of available chemical and physical data from local, county, state, and federal databases for the Carson Valley, near Minden, Nevada. Critical data gaps will be identified and, if necessary, additional sample collection and monitoring under conditions of routine groundwater pumping from both municipal and agricultural supply wells will be suggested. Data included as part of this data set, are data provided by the USGS and Carson Valley water purveyors with the support of the Carson Water Subconservancy District and Nevada Division of Environmental Protection to evaluate arsenic mobility and transport in Carson Valley. The data available and described in this release are groundwater water level observations and water chemistry for selected wells in the Carson Valley, Nevada. Cited reference information are available in the supplemental information field in the metadata file associated with this data release.

As of 2021, California and Texas were the U.S. states with the highest needs for investment in drinking water infrastructure for the following 20 years. The majority of states and territories required most of that investment in the distribution and transmission of water. Despite having a smaller land area, New York, Florida, and Pennsylvania were also among the states with the highest infrastructure investment needs.

As included in this EnviroAtlas dataset, the community level domestic water use is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking, hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). Three reports were used with city- or water supply authority- level domestic water demand data, in addition to county level data. The 2011 Northern Virginia Regional Water Supply Plan provides detailed publicly, privately, and self supplied water use and population served for 2007 and covers most of the Virginia side of the EnviroAtlas study area. The 2011 Fauquier County Regional Water Supply Plan provides detailed publicly, privately, and self supplied water use and population served for 2007 and covers Fauquier County, Virginia. The 2010 Washington Metropolitan Area Water Supply Reliability Study, Part 1 from the Interstate Commission on the Potomac River Basin provides detailed publicly, privately, and self supplied water use and population served for 2008 by water supplier for suppliers drawing from the Potomac River. Data from these reports were weighted across publicly, privately, and self-supplied sources by population served, resulting in a single water use estimate between 25 and 204 GPD for each of the subregions in the study area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This is the 2014 Integrated Report. EPA approved this submission in accordance with Sections 303(d), 305(b), and 314(l) of the Clean Water Act, on October 16, 2015. The Integrated Report (IR) combines two water quality reports required under sections 305(b) and 303(d) of the federal Clean Water Act. Section 305(b) requires states, territories and authorized tribes to perform annual water quality assessments to determine the status of jurisdictional waters. Section 303(d) requires states, territories and authorized tribes to identify waters assessed as not meeting water quality standards(see Code of Maryland Regulations 26.08.02). Waters that do not meet standards may require a Total Maximum Daily Load to determine the maximum amount of an impairing substance or pollutant that a particular water body can assimilate and still meet water quality criteria. Historically, the 303(d) List and the 305(b) report were submitted to the Environmental Protection Agency (EPA) as separate documents but more recent guidance has called for combining these two reports into a single biennial publication.

More information is available at http://www.mde.state.md.us/PROGRAMS/WATER/TMDL/INTEGRATED303DREPORTS/Pages/Programs/WaterPrograms/TMDL/Maryland%20303%20dlist/index.aspx

A searchable version of this data is available at http://www.mde.state.md.us/programs/Water/TMDL/Integrated303dReports/Pages/303d.aspx