At 20,310 feet (6.2km) above sea level, the highest point in the United States is Denali, Alaska (formerly known as Mount McKinley). The highest point in the contiguous United States is Mount Whitney, in the Sierra Nevada mountain range in California; followed by Mount Elbert, Colorado - the highest point in the Rocky Mountains. When looking at the highest point in each state, the 13 tallest peaks are all found in the western region of the country, while there is much more diversity across the other regions and territories.

Despite being approximately 6,500 feet lower than Denali, Hawaii's Mauna Kea is sometimes considered the tallest mountain (and volcano) on earth. This is because its base is well below sea level - the mountain has a total height of 33,474 feet, which is almost 4,500 feet higher than Mount Everest.

At 282 feet below sea level, Death Valley in the Mojave Desert, California is the lowest point of elevation in the United States (and North America). Coincidentally, Death Valley is less than 85 miles from Mount Whitney, the highest point of elevation in the mainland United States. Death Valley is one of the hottest places on earth, and in 1913 it was the location of the highest naturally occurring temperature ever recorded on Earth (although some meteorologists doubt its legitimacy). New Orleans Louisiana is the only other state where the lowest point of elevation was below sea level. This is in the city of New Orleans, on the Mississippi River Delta. Over half of the city (up to two-thirds) is located below sea level, and recent studies suggest that the city is sinking further - man-made efforts to prevent water damage or flooding are cited as one reason for the city's continued subsidence, as they prevent new sediment from naturally reinforcing the ground upon which the city is built. These factors were one reason why New Orleans was so severely impacted by Hurricane Katrina in 2005 - the hurricane itself was one of the deadliest in history, and it destroyed many of the levee systems in place to prevent flooding, and the elevation exacerbated the damage caused. Highest low points The lowest point in five states is over 1,000 feet above sea level. Colorado's lowest point, at 3,315 feet, is still higher than the highest point in 22 states or territories. For all states whose lowest points are found above sea level, these points are located in rivers, streams, or bodies of water.

The statistic shows the highest mountains in North America.

United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data was reported at 2.264 % in 2010. This records an increase from the previous number of 2.246 % for 2000. United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data is updated yearly, averaging 2.264 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 2.329 % in 1990 and a record low of 2.246 % in 2000. United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Land Use, Protected Areas and National Wealth. Urban population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

The United States has an average elevation of roughly 2,500 feet (763m) above sea level, however there is a stark contrast in elevations across the country. Highest states Colorado is the highest state in the United States, with an average elevation of 6,800 feet (2,074m) above sea level. The 10 states with the highest average elevation are all in the western region of the country, as this is, by far, the most mountainous region in the country. The largest mountain ranges in the contiguous western states are the Rocky Mountains, Sierra Nevada, and Cascade Range, while the Appalachian Mountains is the longest range in the east - however, the highest point in the U.S. is Denali (Mount McKinley), found in Alaska. Lowest states At just 60 feet above sea level, Delaware is the state with the lowest elevation. Delaware is the second smallest state, behind Rhode Island, and is located on the east coast. Larger states with relatively low elevations are found in the southern region of the country - both Florida and Louisiana have an average elevation of just 100 feet (31m) above sea level, and large sections of these states are extremely vulnerable to flooding and rising sea levels, as well as intermittent tropical storms.

United States US: Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 1.168 % in 2010. This stayed constant from the previous number of 1.168 % for 2000. United States US: Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 1.168 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 1.168 % in 2010 and a record low of 1.168 % in 2010. United States US: Land Area Where Elevation is Below 5 Meters: % of Total Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Land Use, Protected Areas and National Wealth. Land area below 5m is the percentage of total land where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 (NAD83). All bare earth elevation values are in meters and are referenced to the North American Vertical Datum of 1988 (NAVD88). Each tile is distributed in the UTM Zone in which it lies. If a tile crosses two UTM zones, it is delivered in both zones. The one-meter DEM is the highest resolution standard DEM offered in the 3DEP product suite. Other 3DEP products are nationally seamless DEMs in resolutions of 1/3, 1, and 2 arc seconds. These seamless DEMs were referred to as the National Elevation Dataset (NED) from about 2000 through 2015 at which time they became the seamless DEM layers under the 3DEP program and the NED name and system were retired. Other 3DEP products include five-meter DEMs in Alaska as well as various source datasets including the lidar point cloud and interferometric synthetic aperture radar (Ifsar) digital surface models and intensity images. All 3DEP products are public domain.

A nationwide listing of known publicly available high-accuracy topographic and bathymetric source elevation data for the United States and its territories. The inventory provides a single resource for information about all known completed and in-progress broad-area public domain elevation data. The information provided for each elevation dataset includes many attributes such as vertical accuracy, point spacing, and date of collection. A direct link to access the data or information about the contact organization is also available through the inventory. The United States Interagency Elevation Inventory raises awareness of and increases access to existing elevation data, thereby reducing data duplication efforts. It helps to identify data gaps and informs and encourages collaboration on future data collection efforts. The inventory displays data set boundaries and provides information about the elevation data but does not host the data itself. If available, links to access the data, metadata, and reports are included. The inventory viewer uses map services from multiple sources to provide information both topography and bathymetry. Map services from NOAA NCEI display the footprints and attribute information for the NOAA Hydrographic Surveys, Multibeam Bathymetry, and Trackline Surveys. A map service from USACE provides the USACE Hydrographic Surveys. Map services from NOAA Office for Coastal Management provide the bulk of the topographic and bathymetric lidar information. The NOAA NCEI and USACE service are updated regularly as new data in ingested. The data supporting the NOAA OCM hosted services are maintained by a partnership of federal agencies and supports the federal elevation theme. The agencies include NOAA, the U.S. Geological Survey, the Federal Emergency Management Agency, the U.S. Department of Agriculture, the U.S. Forest Service, the National Park Service and the U.S. Army Corps of Engineers. This service is updated quarterly through an active process of data discovery and validation.

The High Accuracy Elevation Data Project collected elevation data (meters) on a 400 meter topographic grid with a vertical accuracy of +/- 15 centimeters to define the topography in South Florida. The data are referenced to the horizontal datum North American Datum 1983 (NAD 83) and the vertical datum North American Vertical Datum 1988 (NAVD 88). The High Accuracy Elevation Data Project began with a pilot study in FY 1995 to determine if the then state-of-the-art GPS technology could be used to perform a topographic survey that would meet the vertical accuracy requirements of the hydrologic modeling community. The initial testing platform was from a truck and met the accuracy requirements. Data were collected in areas near Homestead, Florida. The data are available for the areas shown on the USGS High Accuracy Elevation Data graphic at http://sofia.usgs.gov/exchange/desmond/desmondelev.html.

The U.S. Interagency Elevation Inventory (USIEI) displays high-accuracy topographic and bathymetric data for the United States and its territories. The project is a collaborative effort between the National Oceanic and Atmospheric Administration, the U.S. Geological Survey, the Federal Emergency Management Agency, the U.S. Department of Agriculture - Natural Resources Conservation Service and U.S. Forest Service, the National Park Service, and the U.S. Army Corps of Engineers. This resource is a comprehensive, nationwide listing of known high-accuracy topographic data, including lidar and IfSAR, and bathymetric data, including NOAA hydrographic surveys, multibeam data, and bathymetric lidar. This zip file contains the attribute information and footprints about the data sets that are displayed in the Topographic Lidar, Topobathy Shoreline Lidar, IfSAR Data, and Bathymetric Lidar layers in the USIEI viewer. This does not include the elevation data itself. The data are provided in Esri file geodatabase format (gdb) and in the open format of OGC GeoPackage (gpkg). The data is also available via this map service: https://coast.noaa.gov/arcgis/rest/services/USInteragencyElevationInventory/USIEIv2/MapServer. The data is updated quarterly. The information provided for each elevation data set includes many attributes such as vertical accuracy, point spacing, and date of collection. A direct link to access the data or information about the contact organization is also available through the inventory. The footprints in this data set are generalized to represent the coverage of the collection. If the exact data coverage is needed, please contact the data provider for an authoritative footprint. The fields in the gdb and gpkg are in four tables. The fields in each table are listed in the Entity Attribute Overview field.

The High Accuracy Elevation Data Project collected elevation data (meters) on a 400 meter topographic grid with a vertical accuracy of +/- 15 centimeters to define the topography in South Florida. The data are referenced to the horizontal datum North American Datum 1983 (NAD 83) and the vertical datum North American Vertical Datum 1988 (NAVD 88). In some areas, the surveying was accomplished using airboats. Because access was a logistical problem with airboats, the USGS developed a helicopter-based instrument known as the Airborne Height Finder (AHF). All subsequent data collection used the AHF. Data were collected from the Loxahatchee National Wildlife Refuge, south through the Water Conservation Areas (1A, 2A, 2B, 3A, and 3B), Big Cypress National Park, the Everglades National Park, to the Florida Bay. The data are available for the areas shown on the USGS High Accuracy Elevation Data graphic at http://sofia.usgs.gov/exchange/desmond/desmondelev.html. The work was performed for Everglades ecosystem restoration purposes.

The highest city in the world with a population of more than one million is La Paz. The Capital of Bolivia sits ***** meters above sea level, and is more than 1,000 meters higher than the second-ranked city, Quito. La Paz is also higher than Mt. Fuji in Japan, which has a height of 3,776 meters. Many of the world's largest cities are located in South America. The only city in North America that makes the top 20 list is Denver, Colorado, which has an altitude of ***** meters.

This is a tiled collection of the 3D Elevation Program (3DEP) and is 1 arc-second (approximately 30 m) resolution. The elevations in this Digital Elevation Model (DEM) represent the topographic bare-earth surface. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The seamless 1 arc-second DEM layers are derived from diverse source data that are processed to a common coordinate system and unit of vertical measure. These data are distributed in geographic coordinates in units of decimal degrees, and in conformance with the North American Datum of 1983 (NAD 83). All elevation values are in meters and, over the continental United States, are referenced to the North American Vertical Datum of 1988 (NAVD88). The seamless 1 arc-second DEM layer provides coverage of the conterminous United States, Hawaii, Puerto Rico, other territorial islands, and much of Alaska and Canada. The seamless 1 arc-second DEM is available as pre-staged current and historical products tiled in GeoTIFF format. The seamless 1 arc-second DEM layer is updated continually as new data become available in the current folder. Previously created 1 degree blocks are retained in the historical folder with an appended date suffix (YYYYMMDD) when they were produced. Other 3DEP products are nationally seamless DEMs in resolutions of 1 and 1/3 arc-second. These seamless DEMs were referred to as the National Elevation Dataset (NED) from about 2000 through 2015 at which time they became the seamless DEM layers under the 3DEP program and the NED name and system were retired. Other 3DEP products include one-meter DEMs produced exclusively from high resolution light detection and ranging (lidar) source data and five-meter DEMs in Alaska as well as various source datasets including the lidar point cloud and interferometric synthetic aperture radar (Ifsar) digital surface models and intensity images. All 3DEP products are public domain.

Official Technical Information * Distance: 25.8 miles * Start Elevation: 8,756 feet * Finish Elevation: 9,080 feet * Low Point: 8,745 feet * High Point: 9,945 feet * Total Climbing: 4,011 feet

Comprehensive dataset containing 6 verified High Point locations in Tennessee, United States with complete contact information, ratings, reviews, and location data.

The U.S. Geological Survey (USGS) coordinated the acquisition of high accuracy elevation data (meters) for the Lake Okeechobee Littoral Zone collected on a 400 meter topographic grid with a vertical accuracy of +/- 15 centimeters. The elevations are referenced to the horizontal North American Datum of 1983 (NAD83) and vertical North American Vertical Datum of 1988 (NAVD88). The topographic surveys were performed using differential GPS technology and a USGS developed helicopter-based instrument known as the Airborne Height Finder (AHF).

The data are available for the areas shown on the USGS High Accuracy Elevation Data graphic at http://sofia.usgs.gov/exchange/desmond/desmondelev.html.

The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Strategy implemented by NRCan. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps.

The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements.

In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generated. Most of these datasets have optical imagery as their source data. They are generated at a 5 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km.

The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada.

Complete coverage of the Canadian landmass is gradually implemented. HRDEM datasets are processed and made available as the data is acquired.

Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project.

Collaboration is a key factor to the success of the National Elevation Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

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

Landslide susceptibility models show the potential of landslide occurrence at a _location. These models are pivotal for reducing losses associated with landslides (Godt et al., 2022). In this data release, we include susceptibility results from the associated manuscript by Woodard and Mirus (2025). This manuscript shows how a morphometric model can create consistent and effective susceptibility models over large regions (> 100 km2) by analyzing the terrain’s topography. The model assumes that areas with high relative slope and hillslope area in comparison to the rest of the terrain are more susceptible to landsliding. As the model’s only input is elevation data, it mitigates the data biases common in the data-driven statistical methods (e.g., machine learning) generally used over these scales. We compare the morphometric model outputs to a parsimonious national susceptibility map and logistic regression machine learning models. The national susceptibility map is available in Belair et al., (2024). The two logistic regression models are trained on the landslide data available in the Willamette Valley Hydrologic Unit Code (HUC) 4 watershed (DOGAMI, 2024). To account for the effects of the sampling ratio of event to non-event data points, we create two logistic regression models. The first uses a 1:1 sampling ratio of landslide to non-landslide points and the second uses all the data within the training data which results in a 1:33 sampling ratio. Environmental datasets requisite for the logistic regression models are all derived from the three-dimensional elevation program (3DEP) (U.S. Geological Survey, 2019a) preprocessed within the National Hydrography Dataset (U.S. Geological Survey, 2019b). The morphometric model was derived using only the 3DEP dataset without any input of where landslides have occurred. All model outputs are shown with slope units. This data release includes the following files: 1) logistic regression results with 1:1 sampling ratio over Willamette Valley HUC4 watershed (1709) (Logistic_1709_1.zip); 2) logistic regression results with 1:33 sampling ratio over Willamette Valley HUC4 watershed (1709) (Logistic_1709_All.zip); 3) morphometric results with uniform weights over the Willamette Valley HUC4 watershed (1709) (Morph_Uniform_1709.zip); 4) morphometric results with area weights over the 1701 HUC 4 watershed (Morph_Area_1701.zip); 5) morphometric results with area weights over the 1702 HUC 4 watershed (Morph_Area_1702.zip); 6) morphometric results with area weights over the 1703 HUC 4 watershed (Morph_Area_1703.zip); 7) morphometric results with area weights over the 1704 HUC 4 watershed (Morph_Area_1704.zip); 8) morphometric results with area weights over the 1705 HUC 4 watershed (Morph_Area_1705.zip); 9) morphometric results with area weights over the 1706 HUC 4 watershed (Morph_Area_1706.zip); 10) morphometric results with area weights over the 1707 HUC 4 watershed (Morph_Area_1707.zip); 11) morphometric results with area weights over the 1708 HUC 4 watershed (Morph_Area_1708.zip); 12) morphometric results with area weights over the 1709 HUC 4 watershed (Morph_Area_1709.zip); 13) morphometric results with area weights over the 1710 HUC 4 watershed (Morph_Area_1710.zip); 14) morphometric results with area weights over the 1711 HUC 4 watershed (Morph_Area_1711.zip); 15) morphometric results with area weights over the 1712 HUC 4 watershed (Morph_Area_1712.zip). 16) shape file field descriptors (Field_Descriptors.txt) Each zip-file contains the vector shapefiles of interest which can be extracted using most archiver software. References Cited DOGAMI. (2024). SLIDO (Version 4.5) [Data set]. https://pubs.oregon.gov/dogami/SLIDO/4.5/SLIDO_Release_4p5_wMetadata.gdb.zip. Gina M Belair, Jeanne M Jones, Sabrina N Martinez, Benjamin B Mirus, & Nathan J Wood. (2024). Slope-Relief Threshold Landslide Susceptibility Models for the United States and Puerto Rico [Data Release]. U.S. Geological Survey. https://doi.org/10.5066/P13KAGU3 Godt, J. W., Wood, N. J., Pennaz, A. B., Mirus, B. B., Schaefer, L. N., & Slaughter, S. L. (2022). National Strategy for Landslide Loss Reduction (p. 36). Geological Survey Open-File Report 2022–1075. https://doi.org/10.3133/ofr20221075 U.S. Geological Survey. (2019a). 3D Elevation Program 1/3 arcsecond. Retrieved from https://apps.nationalmap.gov/downloader/ U.S. Geological Survey. (2019b). USGS National Hydrography Dataset Plus High Resolution [Data set]. Retrieved from https://www.sciencebase.gov/catalog/item/57645ff2e4b07657d19ba8e8

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