Gerald A. Hatcher Andrew W. Stevens Peter Dal Ferro 20230808 comma-delimited text data release DOI:10.5066/10.5066/P92U1KPY Pacific Coastal and Marine Science Center, Santa Cruz, California U.S. Geological Survey https://doi.org/10.5066/P92U1KPY Andrew W. Stevens Gerald A. Hatcher Peter Dal Ferro Peter Dartnell Jonathan A. Warrick Nicholas Cohn Hans R. Moritz 2023 data release DOI:10.5066/P92U1KPY Pacific Coastal and Marine Science Center, Santa Cruz, CA U.S. Geological Survey Suggested Citation: Suggested Citation: Stevens, A.W., Hatcher, G.A., Dal Ferro, P., Warrick, J.A., Cohn, N., and Moritz, H.R., 2023, Digital seafloor images, sediment grain size, bathymetry, and water velocity data from the lower Columbia River, Washington and Oregon, 2021: U.S. Geological Survey data release, https://doi.org/10.5066/P92U1KPY. https://doi.org/10.5066/P92U1KPY This dataset contains surface sediment grain diameter measurements from in situ seafloor images collected in the lower Columbia River, Washington and Oregon, in 2021. Surface sediment grain diameters were derived from manual measurements (or "point counts") in a subset of images used to calibrate and validate an automated image processing algorithm to determine surface sediment grain size distributions. For each calibration and validation image that was selected, the long and short axis of 100 grains were manually measured. The grain diameter measurements are provided in comma-separated (.csv) format and compressed into separate .zip archives for images used for calibration and validation of the automated image processing technique. Growth of subaqueous sand dunes commonly causes shoaling in engineered river channels that necessitates costly dredging to maintain adequate depths for navigation. The factors that result in sand wave growth are theoretically understood from laboratory experiments, but the capacity to predict sand wave geometries in field settings is limited due to temporal and spatial variability in hydrodynamics and sediment grain size. Detailed measurements of sand wave geometries, hydrodynamics, and grain size are therefore needed to test and improve numerical models and inform efficient management strategies in navigation channels. This data release presents surface sediment grain size distributions, bathymetry and seafloor acoustic backscatter, and water velocity data acquired at four sites with subaqueous sand dunes in the lower Columbia River, Washington and Oregon, between June 4 and June 9, 2021. The four sites were located between 65 km and 127 km upstream from the ocean inlet along a gradient of relative tidal and fluvial influence. The survey was performed during peak annual river discharge when sediment transport processes were likely active. High resolution digital images were collected at each site with an underwater camera system that was repeatedly lowered to the seabed along a series of 1 km-long transects oriented along the main navigation channel and spaced about 60 m apart. The grain size distributions of the seabed images were estimated using an automated image processing technique and tested with observed grain size distributions derived from manual measurements on a subset of 16 images. Swath bathymetry and seafloor acoustic backscatter data were collected repeatedly at each site using a 234.5 kHz phase-differencing sidescan sonar to characterize sand wave geometry and bathymetric change resulting from sand wave migration. Current velocity data were collected from an underway survey vessel equipped with a downward looking 600 kHz ADCP along transects oriented both along- and across the main navigation channel. Combined, these data provide a comprehensive characterization of mobile subaqueous sand dunes that can be used to improve predictions of dune growth in complicated field settings and inform efficient sediment management practices in the lower Columbia River. Additional information about the field activity or activities from which these data were derived is available online at: https://cmgds.marine.usgs.gov/fan_info.php?fan=2021-621-FA Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 20210605 20210608 ground condition at time data were collected Complete None planned -123.442574 -122.762951 46.250242 45.712673 USGS Metadata Identifier USGS:76755b8a-f71d-4713-88b2-16f88e07df68 ISO 19115 Topic Category geoscientificInformation Data Categories for Marine Planning Substrate USGS Thesaurus ocean processes sediment transport grain-size analysis Marine Realms Information Bank (MRIB) keywords sediment Global Positioning System (GPS) observations None U.S. Geological Survey USGS Coastal and Marine Hazards and Resources Program CMHRP Pacific Coastal and Marine Science Center PCMSC Geographic Names Information System (GNIS) Columbia River State of Washington State of Oregon None USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator(s) of the dataset and in products derived from these data. U.S. Geological Survey, Pacific Coastal and Marine Science Center PCMSC Science Data Coordinator mailing and physical

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Santa Cruz CA 95060 831-427-4747 pcmsc_data@usgs.gov point_count_example.png Image of sediment showing manual measurements of long and short axis of sediment grains and derived cumulative size distribution from grain diameter measurements PNG MATLAB Version: 9.13.0.2080170 (R2022b) Update 1 Jonathan A. Warrick David M. Rubin Peter Ruggiero Jodi N. Harney Amy E. Draut Daniel Buscombe 2009 Warrick, J.A., Rubin, D.M., Ruggiero, P., Harney, J.N., Draut, A.E., and Buscombe, D., 2009, Cobble cam: grain-size measurements of sand to boulder from digital photographs and autocorrelation analyses, Earth Surface Processes and Landforms, v. 34, pp. 1811-1821. https://doi.org/10.1002/esp.1877 Data fall within expected ranges. No formal logical accuracy tests were conducted. Dataset is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. The locations of each seafloor image collected were determined using an Applanix POSMV Wavemaster operating in DGNSS mode. Manufacturer reported accuracy of the horizontal positions while operating in DGNSS mode is between 0.5 and 2 m depending on the quality of the DGNSS corrections received (https://www.applanix.com/downloads/products/specs/posmv/POS-MV-WaveMaster-II.pdf). Additional uncertainty in the horizontal positions of the images due to instrument layback, or non-vertical wire angle between surface vessel and camera at the seafloor, is unknown but assumed to be minimal because of the weight of the camera and slow speed of the vessel relative to the ambient currents during image acquisition. High resolution spatial surveys were performed between June 5 and 8, 2021 to quantify surface sediment grain size distributions of mobile subaqueous dunes at four sites in the lower Columbia River, Washington and Oregon. At each site, digital images of the sediment surface were collected with an underwater camera system that was repeatedly lowered to the seabed along a series of 1 km-long transects oriented along the main navigation channel and spaced about 60 m apart. The camera consisted of a FLIR Blackfly BFS-PGE-50S5 camera and 50 mm lens in a waterproof housing that resulted in a field of view of approximately 17 mm and a resolution of 0.00657 mm per pixel when the housing window was flush with the sediment surface. An ethernet cable between the survey vessel and camera provided power to the camera and allowed for real-time viewing of the seafloor imagery on a computer during acquisition. The locations of each seafloor image were determined using an Applanix POSMV Wavemaster global navigation satellite system receiver operating in DGNSS mode. 20210608 Imagery were inspected to remove images that were not suitable for analysis, including blurry images and replicate images. A subset of 15 calibration images and 16 validation images were identified from the overall data set. Manual point counts were performed on both calibration and validation images by manually measuring the long and short axis of 100 grains in the images following methods described in Warrick and others (2009). Briefly, a 10 x 10 grid was digitally overlaid on the image and, for grains underlying the grid intersection points, both the longest exposed length and shortest exposed length were measured in pixels using a line-drawing tool. If there was no distinguishable grain under the grid intersection point, the nearest clearly visible grain was measured. 20221213 Results from each point count measurement were tabulated in comma-separated text files, organized by calibration and validation groups, and zipped for distribution. 20230315 Point 0.000001 0.000001 Decimal degrees WGS_1984 WGS_1984 6378137.0 298.257223563 Attribute Table Table containing attribute information associated with the dataset Producer defined start_x X coordinate of starting point of a grain diameter measurement producer defined 4.5 2437.7 pixels start_y Y coordinate of starting point of a grain diameter measurement producer defined 5.3 2047.7 pixels end_x X coordinate of ending point of a grain diameter measurement producer defined 15.8 2443.3 pixels end_y Y coordinate of ending point of a grain diameter measurement producer defined 9.5 2027.8 pixels grain_len_pix Diameter of sediment grain producer defined 11.0 740.5 pixels The first line of the csv file is a header line. U.S. Geological Survey U.S. Geological Survey - CMGDS mailing and physical

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Santa Cruz CA 95060 1-831-427-4747 pcmsc_data@usgs.gov The manual grain size measurements from point counts of calibration and validation images are available in comma-separated text files. The measurements used for calibration (point_counts_calibration.zip) and validation (point_counts_validation.zip) of the automated image processing technique were compressed in separate zip files. The files containing the manual grain diameter measurements were named with the same name as the original image appended with either "_short.csv" or "_long.csv" to denote whether measurements were made on the long or short axis of the grains in the image. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. PNG MATLAB Version: 9.13.0.2080170 (R2022b) Zipped files containing manual grain diameter measurements on images used for validation of the image processing technique. WinZip, 7zip, Peazip or pkUnzip 0.0512 https://doi.org/10.5066/P92U1KPY Data and metadata can be downloaded using the Network_Resource_Name link and scrolling down to the Sediment Properties section. PNG MATLAB Version: 9.13.0.2080170 (R2022b) Zipped files containing manual grain diameter measurements on images used for calibration of the image processing technique. WinZip, 7zip, Peazip or pkUnzip 0.0485 https://doi.org/10.5066/P92U1KPY Data and metadata can be downloaded using the Network_Resource_Name link and scrolling down to the Sediment Properties section. None. 20230808 U.S. Geological Survey, Pacific Coastal and Marine Science Center PCMSC Science Data Coordinator mailing and physical

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Santa Cruz CA 95060 831-427-4747 pcmsc_data@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998