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.

This dataset was created to represent the land surface elevation at 1:24,000 scale for Florida. The elevation contour lines representing the land surface elevation were digitized from United States Geological survey 1:24,000 (7.5 minute) quadrangles and were compiled by South Florida, South West Florida, St. Johns River and Suwannee River Water Management Districts and FDEP. QA and corrections to the data were supplied by the Florida Department of Environmental Protection's Florida Geological Survey and the Division of Water Resource Management. This data, representing over 1,000 USGS topographic maps, spans a variety of contour intervals including 1 and 2 meter and 5 and 10 foot. The elevation values have been normalized to feet in the final data layer. Attributes for closed topographic depressions were also captured where closed (hautchered) features were identified and the lowest elevation determined using the closest contour line minus one-half the contour interval. This data was derived from the USGS 1:24,000 topographic map series. The data is more than 20 years old and is likely out-of-date in areas of high human activity.

Coral reefs serve as natural barriers that protect adjacent shorelines from coastal hazards such as storms, waves and erosion but projections indicate global degradation of coral reefs due to anthropogenic impacts and climate change will cause a transition to net erosion by mid-century. The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by measuring regional-scale changes in seafloor elevation. USGS staff assessed five coral reef ecosystems in the Atlantic Ocean (Upper and Lower Florida Keys), Caribbean Sea (U.S. Virgin Islands: St. Thomas and Buck Island, St. Croix), and Pacific Ocean (Maui, Hawaii), including both coral-dominated and adjacent, non-coral dominated habitats. Scientists used historical bathymetric data from the 1930s to 1980s and contemporary light detection and ranging (lidar) digital elevation models (DEMs) from the late 1990s to 2000s to calculate changes in seafloor elevation for each study site over time periods reflecting low to high anthropogenic impacts. LFK_ElevationChange.zip contains the _location, elevation, and elevation change data for the Lower Florida Keys. Using these changes in elevation, further analysis was done to calculate corresponding changes in seafloor volume for all study areas and habitat types within each site.

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Lower Neches River Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 23, 25, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point density of 1.4 points per square meter. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

The D-DIRT experiment in Idaho was established in 2013,and is situated at the Reynold’s Creek Experimental Watershed (RCEW), which is also the site of the Reynold’s Creek Critical Zone Observatory (CZO) (http://criticalzone.org/reynolds/research/). The RCEW is located in the Owyhee Range in southwest Idaho, and situated along a 1000 m elevation range, it encompasses a wide range of environments typical of the intermountain region of the western USA. Precipitation in the RCEW generally increases with elevation from less than 250 mm/y to greater than 1100 mm/y, while mean annual temperature decreases by about 5°C, from 10.2°C to 5.6°C. Rain is the dominant form of precipitation in the RCEW, with snow dominating in the highest elevations. Corresponding vegetation types include sagebrush steppe in the lower elevations, transitioning to mountain sagebrush, western juniper, aspen and coniferous forest. An extensive description of the RCEW environment can be found in Seyfried et al., (2001). The RCEW-DIRT site is one of the sites in the D-DIRT network (Dryland Detrital Inputs and Removal Treatments), and is located at the lowest elevation (1184m) at RCEW (43°15’ N,116°46’ W). Mean annual temperature at the site is 10.2°C, and mean annual precipitation is 236mm. The vegetation consists of a patchy mosaic of shrubs and grasses. The main shrub is big sagebrush (Artemisia tridentata), and common herbaceous species at the site are P. secunda, P. spicata, and B. tectorum.

This dataset consists of contours showing the generalized altitude of the potentiometric surface for the shallow groundwater system in the Lower Gunnison River Basin in Delta, Montrose, Ouray, and Gunnison Counties, Colorado. Potentiometric-surface altitude was contoured from values in the raster dataset potalt. The U.S. Geological Survey prepared this dataset in cooperation with the Colorado Water Conservation Board.

In May 2023, the U.S. Geological Survey provided training for bathymetric data acquisition and processing for the Iraq Ministry of Water Resources. The training included multibeam sonar theory, survey planning, data collection and processing, and dissemination. This data release presents the raw survey data, a digital elevation model (DEM), and a thalweg shapefile for three survey areas in the Pacific Northwest, USA (Mores Creek, Idaho; Columbia River, OR; Willamette River, OR). Additionally, metadata describes the processing steps, quality assurance and control, and an overall summary of each dataset. The bathymetry point cloud data were collected at selected study sites in the Pacific Northwest, U.S.A, May 2023 to produce a digital elevation model that was used to delineate a thalweg for each of the selected study sites. The DEM files were used to determine the best estimate of the location of the channel thalweg line for each selected study site. The thalweg is the lowest elevation along the longitudinal profile of the riverbed.

In 2011-12, the U.S. Geological Survey conducted a study of the and hydrogeomorphic history and hydrodynamic characteristics of the lower 5 kilometers of the Sheboygan River, a tributary to Lake Michigan in eastern Wisconsin. The hydrogeomorphic history and stability of an ecologically important island complex in the Sheboygan River, the Wildwood Islands, was studied to determine the potential effects of inundation of island surfaces on riparian vegetation and potential areas of erosion and deposition. A two-dimensional (2D) channel hydraulics model was developed for simulating the interaction of riverine flows with varying lake levels and seiche effects. This dataset contains model input and output associated with 10 scenarios involving combinations of Lake Michigan water surface elevations and Sheboygan River discharge values.

This dataset consists of altitude values representing the top surface (in feet) of well-consolidated bedrock at the base of the shallow groundwater system in the Lower Gunnison River Basin in Delta, Montrose, Ouray, and Gunnison Counties, Colorado. Bedrock-altitude values were computed as the difference between land-surface altitude and the thickness of regolith sediments represented by dataset rglth. The U.S. Geological Survey prepared this dataset in cooperation with the Colorado Water Conservation Board.

The land surface forms were identified using the method developed by the Missouri Resource Assessment Partnership (MoRAP). The MoRAP method is an automated land surface form classification based on Hammond's (1964a, 1964b) classification. MoRAP made modifications to Hammond's classification, which allowed finer-resolution elevation data to be used as input data and analyses to be made using 1 km2 moving window (True, 2002; True et al., 2000). While Hammond's methodology was based on three variables, slope, local relief, and profile type, MoRAP's methodology uses only slope and local relief (True, 2002). Slope is classified as gently sloping or not gently sloping using a threshold value of 8%. Local relief, the difference between the maximum and minimum elevation in a 1km2 neighborhood for analysis, is classified into five classes (0-15m, 16-30m, 31-90m, 91-150m, and >150m). Slope classes and relief classes were subsequently combined to produce eight land surface form classes (flat plains, smooth plains, irregular plains, escarpments, low hills, hills, breaks/foothills, and low mountains). In the implementation for the contiguous United States, Sayre et al. (2009) further refined the MoRAP methodology to identify a new land surface form class, "high mountains/deep canyons", by using an additional local relief class (>400 m). This method was implemented for Africa using a void-filled 90m SRTM elevation dataset which was created from the 30m SRTM elevation data provided by the National Geospatial-Intelligence Agency. In the preliminary output, which had nine land surface form classes (flat plains, smooth plains, irregular plains, escarpments, low hills, hills, breaks/foothills, and low mountains, and high mountains/deep canyons), artifacts were identified over flat desert areas affecting the classification between the two lowest relief classes, "flat plains" and "smooth plains." Since this problem was especially pronounced in areas where the input SRTM elevation data originally had data-voids, the problem could have been caused by anomalies or artifacts in the input data, which resulted from the void-filling processes. Instead of further investigating causes of the problem, the two land surface form classes were combined. In addition, the "low hills" class which had a very low occurrence was combined with the "hills" class. As a result, seven land surface form classes were identified in the final dataset (smooth plains, irregular plains, escarpments, hills, breaks/foothills, low mountains, and high mountains/deep canyons). References: Hammond, E.H., 1964a. Analysis of Properties in Land Form Geography - An Application to Broad-Scale Land Form Mapping. Annals of the Association of American Geographers, v. 54, no. 1, p. 11-19. Hammond, E.H. 1964b. Classes of land surface form in the forty-eight states, U.S.A. Annals of the Association of American Geographers. 54(1): map supplement no. 4, 1: 5,000,000. Sayre, R., P. Comer, H. Warner, and J. Cress. 2009. A new map of standardized terrestrial ecosystems of the conterminous United States: U. S. Geological Survey professional Paper 1768, 17 p. True, D. 2002. Landforms of the Lower Mid-West. Missouri Resource Assessment Partnership. MoRAP Map Series MS-2003-001, scale 1:1,500,000. http://www.cerc.usgs.gov/morap/Assets/maps/Landforms_of_the_Lower_Mid-West_MS-2002-01.pdf. True, D., T. Gordon, and D. Diamond. 2000. How the size of a sliding window impacts the generation of landforms. Missouri Resources Assessment Partnership. http://www.cerc.cr.usgs.gov/morap/projects/landform_model/landforms2001_files/frame.htm.

Severe drought across the Western United States has caused water levels at Lake Mead in Nevada to drop in recent decades. Since 1970, the lowest end of month water level of Lake Mead at Hoover Dam was recorded in July 2022, at ***** feet above sea level. This was also the lowest level since the 1930s, when the lake was formed by the Hoover Dam. Seven of the 10 lowest water levels recorded since 1970 were in 2022, while three were recorded in 2023. Lake Mead is considered at full capacity when water levels reach 1,220 feet above sea level, but it’s able to hold a maximum of 1,229 feet of water. The last time the lake approached this capacity was in the summer of 1983. Lake Mead, the largest artificial reservoir by volume in the United States, generates electricity and supplies drinking water to California, Arizona, Nevada, and parts of Mexico.

Many forests in dry mountain regions are characterized by a lower elevational treeline. Understanding the controls on the position of lower treeline is important for predicting future forest distributional shifts in response to global environmental change. Lower treelines currently at their climate limit are expected to be more sensitive to changing climate, whereas lower treelines constrained by non-climatic factors are less likely to respond directly to climate change but may be sensitive to other global change agents. In this study, we used existing vegetation classifications to map lower treelines for our 1.7 million km2 study region in the Intermountain West, USA. We modeled topoclimatic drivers of lower treeline position for each of three dominant forest types to identify topoclimatically-limited treelines. We then used spatial data of edaphic properties, recent fire, and land use to identify lower treelines potentially constrained above their ecophysiological limits by non-climatic processes. We found that the lower treeline ecotone of pinyon-juniper woodlands is largely limited by topoclimate and is likely to be sensitive to increasing temperatures and associated droughts, though these effects may be heterogeneously distributed across the landscape. In contrast, dry mixed conifer lower treelines in the northern portion of the study area rarely reached their modeled topoclimatic limit, suggesting that non-climatic processes, including fire and land use, constrain lower treeline above its ecophysiological limits in this forest type. Our results suggest that much of the lower treeline in the Intermountain West is currently climate-limited and will thus be sensitive to ongoing climate changes. Lower treelines in other arid or semi-arid mountainous regions around the globe may also be strongly sensitive to climate, though treeline response to climate change will be mediated at the local scale by soil properties, biotic interactions, and natural or anthropogenic disturbances. Our regional study of lower treeline provides a framework for identifying the drivers of lower treeline formation and allows for more robust projections of future treeline dynamics, which are needed to anticipate shifting global distributions of the forest biome. Methods 1. ltl_forest

Description: line shapefile of the lower treeline between the Continental Divide and the Pacific Crest attributed with the predominant forest type from the USGS National GAP Landcover ECOLSYS_LU field

Methods: We mapped lower treelines across the entire study area using National Land Cover data from the Gap Analysis Program (US Geological Survey 2011), a 30m-resolution classification of major vegetation types from Landsat imagery. Land cover data were reclassified into a binary forest/non-forest raster. Pixels classified as “forest” included all ‘Warm or Cool Temperate Forests and Woodlands’ in the Formation class from the Gap Analysis Program National Land Cover data (US Geological Survey 2011). This dataset conforms with the National Vegetation Classification Standard, which uses both ‘forest’ and ‘woodland’ to indicate the dominance of the tree growth form, including various combinations of needle-leaved conifer, broad-leaved deciduous, and broad-leaved evergreen tree species of varying height and canopy spacing (Federal Geographic Data Committee 2008). Pixels classified as “non-forest” represented all other land cover types, including vegetation dominated by shrubs and herbaceous species, flooded or swamp forests, and areas used for agriculture or human development. Discrete patches of forest or non-forest smaller than 1,000 pixels were merged with their surrounding cover type, resulting in a minimum cartographic unit of 0.9 km2. The binary forest/non-forest raster was converted to polygons, and the edges between forest and non-forest polygons were converted to a polyline representing all forest edges. We used the contrast between the elevations for forest and non-forest patches bordering the forest edge to differentiate between upper and lower treelines for each polyline segment. Using Digital Elevation Models (US Geological Survey 2009), mean elevations of forest and non-forest pixels were calculated within a 4 km2 neighborhood surrounding each polyline vertex. For each polyline segment, the mean non-forest elevation was subtracted from the mean forest elevation. Lower treelines were identified as segments with a positive elevation contrast (where adjacent forested areas were at a higher elevation than adjacent non-forested areas). Lower treeline segments occurring within 100m of water bodies and segments that were outliers in elevation (mean elevation greater than 2500m a.s.l.) were removed. Finally, we visually inspected the resulting map with high-resolution aerial imagery, excluding segments that were not representative of lower treeline (e.g. sections around interior fires, harvested patches, or meadows), removing <1% of the treelines resulting from the automated process. All spatial processing required for mapping treeline was done in ArcGIS (ArcGIS Version 10.5; Computer Software, ESRI Redlands, CA, USA). Each lower treeline segment was attributed with the adjacent forest type from the USGS National GAP Landcover ECOLSYS_LU 2. wUS_studyarea

Description: polygon shapefile of the study area used in the paper "Evidence of widespread topoclimatic limitation for lower treelines of the Intermountain West, U.S.A."

Methods: The study area included the Intermountain West of the United States, defined here as the area between the Pacific Crest and the Continental Divide. Watershed boundaries were used to delineate the Pacific Crest and the Continental Divide, which represent the western and eastern boundaries. The northern and southern boundaries follow the borders of the United States of America.

Elevation strongly influences soil moisture and patterns of tundra plant communities. Areas less than 100 m above sea level were separated to show low-elevation plains. Areas above 100 m elevation were divided into 333-m intervals to show decreases of about 2 °C, as predicted by the adiabatic lapse rate of 6 °C per 1000 m. This corresponds to the change in mean July temperature between Bioclimate Subzones. Vegetation in mountainous regions changes with elevation, forming distinct elevational belts which correspond approximately to bioclimatic subzones. Vegetation is also modified by local topographic effects such as slope, aspect, and cold-air drainage. This heterogeneity was too detailed to map at this scale, so vegetation in mountainous areas was mapped as a complex, using a diagonal hachure pattern. The background color and the orientation of the hatching represent the pH of the dominant bedrock (magenta for non-carbonate bedrock including sandstone and granite, purple for carbonate bedrock including limestone and dolomite). The color of the hatching represents the bioclimate subzone at the lowest elevation within the polygon (yellow hatching for Subzone D and red hatching for Subzone E). Back to Alaska Arctic Tundra Vegetation Map (Raynolds et al. 2006) Go to Website Link :: Toolik Arctic Geobotanical Atlas below for details on legend units, photos of map units and plant species, glossary, bibliography and links to ground data. Map Themes AVHRR NDVI, Bioclimate Subzone, Elevation, False Color-Infrared CIR, Floristic Province, Lake Cover, Landscape, Substrate Chemistry, Vegetation References Raynolds, M.K., Walker, D.A., Maier, H.A. 2005. Plant community-level mapping of arctic Alaska based on the Circumpolar Arctic Vegetation Map. Phytocoenologia. 35(4):821-848. http://doi.org/10.1127/0340-269X/2005/0035-0821 Raynolds, M.K., Walker, D.A., Maier, H.A. 2006. Alaska Arctic Tundra Vegetation Map. 1:4,000,000. U.S. Fish and Wildlife Service. Anchorage, AK.

Valleys, featured in the Valley Identification Tool, are locations that have a lower elevation than surrounding areas. EPA Region 1 GIS Center applied ArcGIS' Focal Statistics tool to the USGS 30-meter NED DEM to find places where elevations are significantly less than average. We then quantified population and wood fuel usage within Census County Subdivisions to find locations which may be vulnerable to wood smoke pollution during winter thermal inversions. Created by US EPA Region 1 GIS Center; and implemented in EPA Regions 2, 3 and 9 in 2022 and Region 10 in 2024 by regional GIS staff, US EPA Office of Mission Support (OMS).

This dataset consists of the boundary extent used to evaluate regolith thickness, bedrock altitude, depth to water, potentiometric-surface altitude, and saturated thickness for the shallow groundwater system in the Lower Gunnison River Basin, in Delta, Montrose, Ouray, and Gunnison Counties, Colorado. The U.S. Geological Survey prepared this dataset in cooperation with the Colorado Water Conservation Board.

Elevation Derivatives for National Applications (EDNA) is a seamless, nationwide, multi-layered three-dimensional (3D) hydrologic database derived from a version of the National Elevation Dataset. EDNA's 3D hydrologic layers are vertically consistent by their very nature, meaning that hydrologic drainage always flows from a higher elevation to a lower elevation and that reach catchment boundaries always follow the elevation drainage divide. This consistency allows for transfer of valuable information from digital elevation models onto EDNA-derived drainage lines and watersheds, including stream gradient, minimum and maximum elevation within a watershed, average watershed slope, and elevation.

In 2016, the U.S. Army Corps of Engineers (USACE) started collecting high-resolution multibeam echosounder (MBES) data on Lake Koocanusa. The survey originated near the International Boundary (River Mile (RM) 271.0) and extended down the reservoir, hereinafter referred to as downstream, about 1.4 miles downstream of the Montana 37 Highway Bridge near Boulder Creek (about RM 253). USACE continued the survey in 2017, completing a reach that extended from about RM 253 downstream to near Tweed Creek (RM 244.5). In 2018, the U.S. Geological Survey (USGS) Idaho Water Science Center completed the remaining portion of the reservoir from RM 244.5 downstream to Libby Dam (RM 219.9). The MBES data collected in 2016 and 2017 by the USACE was combined with the MBES data collected in 2018 by the USGS. The USGS also developed an elevation-area-capacity table at one-foot intervals from the minimum pool elevation (2,290.84 ft) to the maximum pool elevation (2462.84 ft) using the new bathymetry data. The updated stage-capacity table will be compared to the current usable storage estimate of 4,979,500 acre-feet and published in a USGS Scientific Investigations Report. A 10-ft digital elevation model (DEM) and minimum and maximum pool contours also were generated from the bathymetric data and are provided in this data release.

Lake Mead's water elevation at the end of August 2025 was ******* feet above sea level, a small decrease in comparison to the previous month. In July 2022, the reservoir reached the lowest monthly water level recorded since Lake Mead was first formed by the Hoover Dam in the 1930s. At full capacity, Lake Mead has a water level of 1,229 feet above sea level. Lake Mead nearing dead pool status Situated on the border of Arizona and Nevada, Lake Mead is the largest reservoir in the United States. It is a crucial water source that provides drinking water to tens of millions of people in the states of Arizona, California, and Nevada. However, experts have warned that if the lake continues to recede due to the severe droughts across the Southwestern United States, it will become a dead pool. This means that there will not be enough water for the Hoover Dam to produce hydropower or deliver water downstream to metropolitan centers. U.S. water resources are depleting With large swathes of western U.S. recently suffering from a megadrought, which is a period of prolonged drought that spans more than two decades, many other lakes have been severely depleted in recent years. Water levels of major reservoirs in California have fallen to all-time lows in recent years. California’s two largest reservoirs, Shasta Lake and Oroville Lake, were at less than half capacity in July 2022. However, in spring 2023 they were both mostly replenished due to more favorable environmental factors.

A first-surface topography Digital Surface Model (DSM) mosaic for the Lower Neches River Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 23, 25, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point density of 1.4 points per square meter. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Beaumont and Lower Neches River Units of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 22, 23, 25, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 0.5-1.6 meters. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.