U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), Santa Cruz, CA. 2018 raster digital data https://doi.org/10.3133/ofr20111315 U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), Santa Cruz, CA. 2018 Version 4.0 U.S. Geological Survey Open-File Report 2011-1315 https://doi.org/10.3133/ofr20111315 http://pubs.usgs.gov/of/2011/1315 1-m resolution bathymetry collected in Coyote Creek and Alviso Slough in October 2016. Projection = UTM, zone 10 in meters, Horizontal Datum = NAD83 (CORS96), Vertical Datum = MLLW, all units in meters. The surveys extend east from Calaveras Point along Coyote Creek to the railroad bridge, along Alviso Slough to the town of Alviso (just over 7 km), and along the 3.7 km of Guadalupe Slough closest to the San Francisco Bay, California. To monitor bathymetric change as the South Bay Salt Pond Restoration Project progresses (http://www.southbayrestoration.org). Additional information about the field activities from which these data were derived is available online at: https://cmgds.marine.usgs.gov/fan_info.php?fan=2016-678-FA Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 20161012 20161019 ground condition Complete As needed -122.060187436 -121.974560855 37.4706742088 37.4231662547 USGS Metadata Identifier USGS:53640200-34f7-421a-a451-35a5b3ae5351 ISO 19115 Topic Category elevation inlandWaters oceans USGS Thesaurus bathymetry bathymetry measurement digital elevation models interferometric sonar sidescan sonar GPS measurement None U.S. Geological Survey USGS Coastal and Marine Geology Program CMGP Pacific Coastal and Marine Science Center PCMSC Geographic Names Information System (GNIS) State of California San Francisco Bay Alameda County Santa Clara County Alviso Coyote Creek Alviso Slough Guadalupe Slough 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 of the dataset and in products derived from these data. This information is not intended for navigational purposes. USGS Pacific Coastal and Marine Science Center Amy Foxgrover Geographer mailing and physical

2885 Mission Street

Santa Cruz CA 95060 USA (831) 460-7561 (831) 427-4748 afoxgrover@usgs.gov Amy C. Foxgrover Bruce E. Jaffe Gerald T. Hovis Craig A. Martin James R. Hubbard Manoj R. Samant Steve M. Sullivan 2007 Open-File Report 2007-1169 Reston, VA U.S. Geological Survey http://pubs.usgs.gov/of/2007/1169 Applied Microsystems Ltd. 2005 User's manual revision 1.23 T. Soler R.A. Snay 2004 Journal article Journal of Surveying Engineering, v. 130, no. 2 These bathymetric data have not been independently verified for accuracy. All bathymetric values are derived from the same instruments and processing workflow. The raw bathymetry data were filtered in SEA Swath Processor and imported into CARIS HIPS and SIPS for post-processing. Within CARIS a swath angle BASE (Bathymetric with Associated Statistical Error) surface was created at 1 m resolution and the subset editor used to manually eliminate any remaining outliers or artifacts. The average depth within each 1 by 1 m cell was exported as an ASCII text file and imported into Surfer for interpolation using a linear kriging algorithm with a 1-simga nugget of 0.05 m and a 2 by 2 m search radius. The resultant grid was exported to ESRI ArcMap software for display. Uncertainty in the horizontal position of each sounding is a function of the total uncertainty propagated through each of the following component instruments: 1) base station GPS, 2) vessel GPS, 3) inertial motion unit (IMU), 4) water sound velocity model, and 5) beam spreading in the water column. Assuming no systematic errors in the measurement instruments themselves, beam spreading is the dominate source of positional uncertainty. The 1-degree sonar beam of the SWATHplus-M results in horizontal uncertainty ranging from 0.10 m at 10 m slant range, to about 0.45 m at 50 m slant range. After filtering the data to remove obvious outliers, the standard deviation of the remaining sounding elevations was calculated for each 1 m by 1 m cell (each containing 19 soundings on average) in CARIS. The mean of the standard deviation for all cells in the survey is 0.07 m. Additional uncertainty associated with the vertical datum conversion from NAVD88 to MLLW has not been assessed. U.S. Geological Survey, Coastal and Marine Geology Program 2016 raster digital data https://cmgds.marine.usgs.gov/fan_info.php?fan=2016-678-FA online 20161012 20161019 ground condition 2016-678-FA This 2016 field activity collected bathymetric data in San Francisco Bay. Bathymetric surveys were conducted using a 234.5 kHz SEA (Systems Engineering and Assessment Ltd) SWATHplus-M phase-differencing sidescan sonar. The sonar was pole-mounted on the 34-foot USGS mapping vessel R/V Parke Snavely, and affixed to a hull brace. GPS position data were passed through an Applanix Position and Motion Compensation System for Marine Vessels POS/MV inertial measurement unit (IMU) to the sonar hardware and data-collection software. Sonar heads, GPS antennae, and the IMU were surveyed in place to a common reference frame with a Geodimeter 640 Total Station. The R/V Snavely was outfitted with three networked workstations and a navigation computer for use by the captain and survey crew for data collection and initial processing. 2016 An Applanix Position and Motion Compensation System for Marine Vessels (POS/MV) was used to accurately determine the survey vessel's position. The POS/MV utilizes Global Navigation Satellite System (GNSS) data in combination with angular rate and acceleration data from the IMU and heading data from the GPS Azimuth Measurement Systems (GAMS) to produce accurate position and orientation information through a virtual network of base stations. As opposed to receiving high-accuracy Real-Time Kinematic (RTK) corrections, the POS records raw inertial and GNSS data while surveying, which is later refined through post processing to incorporate publicly available GPS data from nearby base stations. During post processing the POS/MV data is run through POSPac software to produce a Smoothed Best Estimate of Trajectory (SBET) file, which is then imported back into Swath Processor to produce high-accuracy positions relative to the WGS84 ellipsoid. The RMS results from our POS/MV surveys show positional errors of less than 5 cm in X, Y, and Z. 2016 Sound velocity measurements were collected continuously with an Applied Micro Systems Micro SV deployed on the transducer frame for real-time sound velocity adjustments at the transducer-water interface. The Micro SV is accurate to +/- 0.03 m/s. In addition, sound velocity profiles (SVP) were collected with an Applied Micro Systems, SvPlus 3472. This instrument provides time-of-flight sound-velocity measurements by using invar rods with a sound-velocity accuracy of +/- 0.06 m/s, pressure measured by a semiconductor bridge strain gauge to an accuracy of 0.15 percent (Full Scale) and temperature measured by thermistor to an accuracy of 0.05 degrees Celsius (Applied Microsystems Ltd., 2005). 2016 GPS data and measurements of vessel motion (heave, pitch, and roll) are combined in the POS/MV hardware to produce a high-precision vessel attitude packet. This packet is transmitted to the Swath Processor acquisition software in post-processing and combined with instantaneous sound velocity measurements at the transducer head before each ping. Up to 20 pings per second are transmitted with each ping consisting of 2048 samples per side (port and starboard). The returned samples are projected to the seafloor using a ray-tracing algorithm working with the previously measured sound velocity profiles in SEA Swath Processor (version 3.12.7). A series of statistical filters are applied to the raw samples that isolate the seafloor returns from other uninteresting targets in the water column. Finally, the processed data are stored line-by-line in both raw (.sxr) and processed (.sxp) trackline files. 2016 The raw bathymetry data were filtered in SEA Swath Processor (version 3.12.7) and imported into CARIS HIPS and SIPS (version 9.0) for post-processing. Within CARIS a swath angle BASE (Bathymetric with Associated Statistical Error) surface was created at 1 m resolution and the subset editor used to manually eliminate any remaining outliers or artifacts. The average depth within each 1 by 1 m cell was exported as an ASCII text file and imported into Surfer (version 10) for interpolation using a linear kriging algorithm with a 1-simga nugget of 0.05 m and a 2 by 2 m search radius. The resultant grid was exported to ESRI ArcMap (version 10.2.2) for display and further analyses. The entire survey was shoaled by 4 cm to account for a combination of biases resulting from changes in the boat instrumentation and configurations that occurred since the initial survey was collected in 2010. 2016 To convert the bathymetry from WGS84 ellipsoid heights to the tidal datum of MLLW the data were first transformed from WGS84(ITRF2000) to the NAD83(CORS96) ellipsoid using a 14-point Helmert transformation described by Soler and Snay (2004) using the command line tool CS2CS in the Proj4 library (http://trac.osgeo.org/proj/). A fixed Geoid09 offset of -32.62 m was then applied to convert the NAD83 ellipsoid heights to orthometric heights NAD83(CORS96)/NAVD88. The orthometric NAVD88 elevations were converted to MLLW using the conversions provided by the CO-OPS division of NOAA for a 2005 bathymetric survey of South San Francisco Bay (Foxgrover and others, 2007). 2016 Edited metadata to add keywords section with USGS persistent identifier as theme keyword. No data were changed. 20201019 U.S. Geological Survey VeeAnn A. Cross Marine Geologist Mailing and Physical

384 Woods Hole Road

Woods Hole MA 02543-1598 508-548-8700 x2251 508-457-2310 vatnipp@usgs.gov raster grid cell 5052 7476 Universal Transverse Mercator 10 0.9996 -123 0.0 500000 0.0 row and column 1.0 1.0 meters North American Datum of 1983 (CORS96) Geodetic Reference System 80 6378137 298.257 Mean Lower Low Water (MLLW) 0.01 meters Attribute values Altitude Elevation relative to MLLW in meters. Values are positive up. USGS Open-File Report: 2011-1315 U.S. Geological Survey, Pacific Coastal and Marine Science Center (PCMSC) Amy Foxgrover mailing and physical address

2885 Mission Street

Santa Cruz CA 95060 US 831-460-7561 831-427-4748 afoxgrover@usgs.gov These data are available in both X,Y,Z text file format and ESRI ASCII Raster format. Both formats are contained in a single zip file (Oct_2016.zip), which also includes CSDGM FGDC-compliant metadata. 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. ESRI ASCII Raster The ASCII file consists of header information containing a set of keywords, followed by cell values in row-major order. The file format is: > ><NCOLS xxx> ><NROWS xxx> ><XLLCENTER xxx | XLLCORNER xxx> ><YLLCENTER xxx | YLLCORNER xxx> ><CELLSIZE xxx> >{NODATA_VALUE xxx} >row 1 >row 2 >. >. >. >row n > where xxx is a number, and the keyword nodata_value is optional and defaults to -9999. Row 1 of the data is at the top of the grid, row 2 is just under row 1 and so on. The nodata_value is the value in the ASCII file to be assigned to those cells whose true value is unknown. In the grid they will be assigned the keyword NODATA. Cell values are delimited by spaces. No carriage returns are necessary at the end of each row in the grid (although they are included in this case). The number of columns in the header is used to determine when a new row begins. The number of cell values is equal to the number of rows times the number of columns. 224 https://doi.org/10.3133/ofr20111315 http://pubs.usgs.gov/of/2011/1315/ No cost 20201019 Amy Foxgrover U.S. Geological Survey, Pacific Coastal and Marine Science Center mailing and physical

2885 Mission Street

Santa Cruz California 95060 USA (831) 460-7561 afoxgrover@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998