Dataset contains contours at 10-foot intervals, spillway crest contour, and dam crest contour of the Calaveras Reservoir, California, based on the bathymetric survey completed in December 2019. Files are provided as geospatial shapefiles and CAD (.dwg file extension) files. Methodology is described in detail in a previous report of a similar reservoir survey project for the cooperator at a separate reservoir: Marineau, M.D., Wright, S.A, and Lopez, J.V., 2020, Storage capacity and sedimentation characteristics of the San Antonio Reservoir, California, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5151, 34 p., https://doi.org/10.3133/sir20195151

Dataset contains reservoir bathymetry collected using multibeam sonar and terrestrial lidar.

Dataset contains contours at 10-foot intervals, spillway crest contour, and dam crest contour of the Calaveras Reservoir, California, based on the bathymetric survey completed in December 2019. Files are provided as geospatial shapefiles and CAD (.dwg file extension) files. Methodology is described in detail in a previous report of a similar reservoir survey project for the cooperator at a separate reservoir: Marineau, M.D., Wright, S.A, and Lopez, J.V., 2020, Storage capacity and sedimentation characteristics of the San Antonio Reservoir, California, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5151, 34 p., https://doi.org/10.3133/sir20195151

This portion of the data release presents a digital elevation model (DEM) of portions of Oxbow Reservoir in Placer County, California. The DEM was created using topographic survey data collected on 26 October 2022, when the reservoir was partially de-watered to allow repairs to the dam infrastructure following the Mosquito Fire. Although the gates of the dam were open during this time, significant portions of the reservoir site remained inaccessible to surveyors due to the continued flow of the Middle Fork American River. Consequently, this DEM covers approximately 50 percent of the total surface area of the reservoir at full pool. The raw topographic data for the DEM were collected using two RTK GNSS backpack rovers which were referenced to a temporary GNSS base station occupying a fixed control point ("CP512") located less than 1 kilometer from the survey area. Precise coordinates for the GNSS base station were derived using the National Geodetic Survey (NGS) Online Positioning User Service (OPUS). The GNSS data were used to create a triangulated irregular network (TIN), which was converted to raster DEM. The resulting DEM has a horizontal resolution of 1 meter and is formatted as a GeoTIFF.

This child data release includes fused topo-bathymetric digital elevation models of the Merced and Tuolumne Rivers in California used to support research on anadromous salmonids. The purpose of this study was to calculate the capacity for reintroduction of salmonids above impassable barriers. Airborne, near-infrared (NIR) LiDAR and hyperspectral imagery were acquired simultaneously in September 2014 from a Cessna Caravan, with the LiDAR data used to map topography of dry land and the imagery used to map water depth in the wetted channel. Topo-bathymetric DEMs of channels and floodplains with 1-m resolution were constructed for the study reaches by using remotely sensed hyperspectral image data to estimate water depths within the below-water portion of the channel and using remotely-sensed LiDAR for the above-water portion of the channel. Water depths were subtracted from water-surface elevations measured by the LiDAR to obtain bed elevations within the wetted channel. The digital elevation model above the water surface was created using the LiDAR data. We used a Leica Airborne Laser Scanner ALS50, with mean point densities >12 points/m2 and reported horizontal and vertical accuracies of 2 cm and 7 cm, respectively. The raw LiDAR point cloud was processed into bare-earth DEMs with 1 m grid cells. The digital elevation model for areas below the water surface was created using the hyperspectral imagery. Hyperspectral imagery was collected using a Compact Airborne Spectographic Imager (CASI) 1500 (ITRES 2014), producing imagery with 48 spectral bands (wavelengths 380 to 1050 nm). Raw image flight strips were geometrically and radiometrically corrected with ITRES software, then atmospherically corrected using ATCOR4 (ReSe 2014). The final images were in units of reflectance for each band, with a spatial resolution of 0.5 m. Water depths were estimated from the imagery using the Optimal Band Ratio Analysis (OBRA) depth retrieval algorithm, a calibration technique that relates field-measured water depths (d) to an image-derived quantity defined as the natural logarithm of the ratio of two spectral bands (Legleiter et al. 2009).

This portion of the data release presents high-resolution Digital Surface Models (DSM) of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to maximize sub-aerial coverage. The raw imagery used to create the orthomosaics was acquired with a UAS quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines spaced to provide approximately 70 percent overlap between images from adjacent lines, from an approximate altitude of 100 meters above ground level (AGL), resulting in a nominal ground-sample-distance (GSD) of 2.6 centimeters per pixel. The raw imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Survey control was established using temporary ground control points (GCPs) consisting of a combination of small square tarps with black-and-white cross patterns and temporary chalk marks placed on the ground. The GCP positions were measured using dual-frequency real-time kinematic (RTK) GPS with corrections referenced to a static base station operating nearby. The images and GCP positions were used for structure-from-motion (SfM) processing to create topographic point clouds, high-resolution orthomosaic images, and DSMs. The DSMs are provided in a cloud optimized GeoTIFF format with internal overviews and masks to facilitate cloud-based queries and display.

A GIS polygon shapefile outlining the extent of small lakes or ponds within the terrain that were assigned a hydo-flattened elevation during lidar post-processing. DEM elevations within these small areas reflect water surface elevations, not bathymetric elevations.