To support the modeling of the Colorado River water storage area capacity tables by the U.S. Geological Survey (USGS) Utah Water Science Center in the Glen Canyon National Recreation Area in Utah and Arizona, the USGS Earth Resources Observation and Science (EROS) Center has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for Lake Powell, the second largest man-made reservoir in the United States. Located in south-central Utah and north-central Arizona, Lake Powell is a reservoir on the Colorado River created by the flooding of a natural canyon by the construction of Glen Canyon Dam. The new Lake Powell TBDEM consists of the best available multi-source topographic and bathymetric elevation data for Lake Powell onshore and offshore areas. The Lake Powell TBDEM integrates three different data sources including topographic light detection and ranging (lidar) point cloud data, multibeam bathymetric surveys, and historic topographic surveys obtained from the Department of the Interior (DOI) Bureau of Reclamation (BOR) and USGS Woods Hole Coastal Marine Science Center. The topographic, bathymetric, and historic topographic surveys were sorted and prioritized based on survey date, accuracy, spatial distribution, and point density to develop a TBDEM model based on the best available elevation data. The Lake Powell TBDEM spatial resolution is 1-meter with the general location ranging from Glen Canyon Dam northwest of Page, Arizona to White Canyon, Utah with elevations from 948.28 meters to 1440.94 meters referenced to North American Vertical Datum of 1988 (NAVD88), National Geodetic Survey Geoid 12B. The topographic lidar survey was acquired from 4/2/18 to 4/3/18. The bathymetry survey was acquired from 10/8/17 to 11/15/17. The historic topographic surveys ranged from 1947-1959. Some of the nearshore void zone (not covered by lidar or multibeam) was filled with historic topographic surveys digitized from historical maps from 1947-1959 and a kriging interpolation as published by the USGS Coastal National Elevation Database (CoNED) Applications Project at https://doi.org/10.2112/SI76-008. Additional information regarding the CoNED Applications Project is located at https://www.usgs.gov/land-resources/eros/coned.

NOTE: The authors believe that this dataset is likely to be LESS accurate than using a clip of the larger San Francisco Bay groundwater dataset, here: https://dash.berkeley.edu/stash/dataset/doi:10.6078/D1W01Q. The reason is that additional datapoints and editing were used to improve the San Francisco Bay groundwater map after this Alameda County map was produced. We expect that the most recent San Francisco Bay map is the most accurate, even for smaller geographic scales.

This dataset contains a comparison of four interpolation methods used to estimate a minimum depth to groundwater surface for Alameda County, within one kilometer/0.6 mi of San Francisco Bay. The interpolation is based on well data from the CA State Water Board GAMA GeoTracker database, and the depth to water was calculated using a 2m USGS Digital Elevation Model.

Methods Well data - California State Water Control Board: GAMA GeoTracker http://geotracker.waterboards.ca.gov/data_download_by_county. Ground elevation data - U.S. Geological Survey https://topotools.cr.usgs.gov/coned/sanfrancisco.php. 2 meter DEM. SF Bay extent (includes open water and tidal wetlands) San Francisco Estuary Institute (SFEI): Bay Area Aquatic Resource Inventory (BAARI) http://www.sfei.org/baari. GIS FILE PROPERTIES: File format: ESRI Layer Package. Cellsize: 6.56. Linear unit: Feet. Z unit: Feet. Projected Coordinate System: NAD_1983_2011_StatePlane_California_III_FIPS_0403_Ft_US. Geographic Coordinate System: GCS_NAD_1983_2011.

METHODS: We subtracted the minimum depth to water at each well point from the ground elevation (extracted from the 2m DEM) to determine groundwater elevation at each well point. These elevations represent the maximum measured groundwater table height in the past 20 years. We then performed the interpolation on this groundwater elevation dataset, a total of 3,183 individual well points. Wells within one mile of the coast were included in the interpolation; results are shown within one kilometer (0.6 miles) of the coast, a distance used in previous studies of sea level rise-induced groundwater inundation. Wells within one-half mile north and south of the county borders were included in the interpolation to ensure continuity, but results are shown only for area within Alameda County.

We tested a variety of methods available in ArcGIS and used cross-validation to determine which method minimized prediction error most. We compared root mean square error (RMSE) to see how accurately each model predicted values at non-sampled locations, and examined mean error (ME), or the averaged difference between actual and predicted values, to see if each model was skewed in one direction or another. For each interpolation technique, we chose the input parameters (e.g. power, number of neighbors included) that minimized RMSE most.

After performing the groundwater table interpolation, we subtracted the output from the original elevation surface to display estimated minimum depth to water values. The interpolation and subtraction method we used produced some negative values for depth to water, indicating water above the ground surface, especially in areas where there were no well sample points at the base of a slope or in a valley. In the provided data files, we have changed these negative values to zero for clarity.

This data package contains the minimum depth to water results obtained by using each of the four interpolation methods, as well as files showing the minimum and maximum of the four methods for comparison. Also included are files showing the bay edge file used and no data areas (greater than 1km/0.6mi from the nearest well point).

This data release contains areas within Delaware Bay and Delaware Inland Bays that are within tidal elevations, as determined by the Highest Astronomical Tide (HAT), but that are classified as non-tidal or managed wetlands by the National Wetlands Inventory (NWI) or as non-estuarine by the 2016 Coastal Change Analysis Program (C-CAP) land cover dataset. These areas have been assigned the classification codes of NWI, where available, and C-CAP. These data are based on a 5m resolution elevation raster from Coastal National Elevation Database (CoNED), an interpolated surface from Highest Astronomical Tide (HAT) data from National Oceanographic and Atmospheric Administration (NOAA) tide gauges, and NWI and C-CAP digital wetland products. The area was determined by identifying non-tidal or non-wetland land covers at or below the interpolated HAT tidal elevation. The underlying wetland category from NWI or land cover type from C-CAP was then applied to the entire area to indicate areas for possible land or hydrologic management and assess current and future conditions of land within tidal elevations.