humboldt_bath

We performed bathymetric surveys using a shallow-water echo-sounding system (Takekawa et al., 2010, Brand et al., 2012) comprised of an acoustic profiler (Navisound 210; Reson, Inc., Slangerup, Denmark), Leica RTK GPS Viva rover, and laptop computer mounted on a shallow-draft, portable flat-bottom boat (Bass Hunter, Cabelas, Sidney, NE; Figure 7). The RTK GPS obtained high resolution elevations of the water surface (reported precision 10 cm water depth. We recorded twenty depth readings and one GPS location each second along transects spaced 100 m apart perpendicular to the nearby salt marsh. We calibrated the system before use with a bar-check plate and adjusted the sound velocity for salinity and temperature differences. We suspended the bar-check plate below the transducer at a known depth that was verified against the transducer readings. Morro Bay did not have bathymetry data, therefore we downloaded LIDAR data collected by the NOAA California Coastal Conservancy Coastal Topobathy Project: Digital Elevation Model 2009-2011.For bathymetry at Pt. Mugu, we used data collected by the Seafloor Mapping Lab (SFML) at the California State University Monterey Bay (Seafloor Mapping Lab, 2013). Side scan data for Pt. Mugu were acquired using a Swathplus interferometric sonar with an Applanix Position and Orientation System, Marine Vessel (POS MV 320 v.4) system (position accuracy ± 2 m, pitch, roll and heading accuracy ± 0.02°, heave accuracy ± 5% or 5 cm). Bathymetric data were post-processed using CARIS HIPS hydrographic data cleaning system software. Derived products are at 1m resolution and relative to the NAVD88 vertical datum with geoid09. Data acquisition, post-processing, and final products derived from multibeam bathymetry data were handled by the Seafloor Mapping Lab at CSUMB. We synthesized the bathymetry data to create a DEM of the mudflat and subtidal regions at Mad River, San Pablo, Bolinas, Morro, Pt. Mugu, and Newport using ArcGIS 10.2.1 Spatial Analyst (ESRI 2013, Redlands, CA) with exponential ordinary kriging methods (5 x 5 m cell size). We removed portions of bathymetry data that overlapped with elevation surveys conducted on the marsh. In this report we present elevation data as local orthometric heights (NAVD88).

Data and Resources

This dataset has no data

Field Value
accessLevel public
bureauCode {010:00}
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identifier 26cebfb6-0210-4371-b21e-dba9735ba1c9
metadata_type geospatial
modified 2016-03-11
old-spatial {"type": "Polygon", "coordinates": [[[-124.15551, 40.848198], [-124.140335, 40.848198], [-124.140335, 40.865009], [-124.15551, 40.865009], [-124.15551, 40.848198]]]}
publisher Climate Adaptation Science Centers
resource-type Dataset
source_datajson_identifier true
source_hash 6f783d548371563cf98d6cb3b1332a843eca255c
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-124.15551, 40.848198], [-124.140335, 40.848198], [-124.140335, 40.865009], [-124.15551, 40.865009], [-124.15551, 40.848198]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • bathymetry-survey
  • ckan
  • geo
  • geoss
  • humboldt-bay
  • mad-river-slough-marsh
  • national
  • north-america
  • united-states
isopen False
license_id notspecified
license_title License not specified
maintainer USGS Western Ecological Research Center (Point of Contact)
maintainer_email kthorne@usgs.gov
metadata_created 2025-11-22T13:53:45.842412
metadata_modified 2025-11-22T13:53:45.842416
notes We performed bathymetric surveys using a shallow-water echo-sounding system (Takekawa et al., 2010, Brand et al., 2012) comprised of an acoustic profiler (Navisound 210; Reson, Inc., Slangerup, Denmark), Leica RTK GPS Viva rover, and laptop computer mounted on a shallow-draft, portable flat-bottom boat (Bass Hunter, Cabelas, Sidney, NE; Figure 7). The RTK GPS obtained high resolution elevations of the water surface (reported precision 10 cm water depth. We recorded twenty depth readings and one GPS location each second along transects spaced 100 m apart perpendicular to the nearby salt marsh. We calibrated the system before use with a bar-check plate and adjusted the sound velocity for salinity and temperature differences. We suspended the bar-check plate below the transducer at a known depth that was verified against the transducer readings. Morro Bay did not have bathymetry data, therefore we downloaded LIDAR data collected by the NOAA California Coastal Conservancy Coastal Topobathy Project: Digital Elevation Model 2009-2011.For bathymetry at Pt. Mugu, we used data collected by the Seafloor Mapping Lab (SFML) at the California State University Monterey Bay (Seafloor Mapping Lab, 2013). Side scan data for Pt. Mugu were acquired using a Swathplus interferometric sonar with an Applanix Position and Orientation System, Marine Vessel (POS MV 320 v.4) system (position accuracy ± 2 m, pitch, roll and heading accuracy ± 0.02°, heave accuracy ± 5% or 5 cm). Bathymetric data were post-processed using CARIS HIPS hydrographic data cleaning system software. Derived products are at 1m resolution and relative to the NAVD88 vertical datum with geoid09. Data acquisition, post-processing, and final products derived from multibeam bathymetry data were handled by the Seafloor Mapping Lab at CSUMB. We synthesized the bathymetry data to create a DEM of the mudflat and subtidal regions at Mad River, San Pablo, Bolinas, Morro, Pt. Mugu, and Newport using ArcGIS 10.2.1 Spatial Analyst (ESRI 2013, Redlands, CA) with exponential ordinary kriging methods (5 x 5 m cell size). We removed portions of bathymetry data that overlapped with elevation surveys conducted on the marsh. In this report we present elevation data as local orthometric heights (NAVD88).
num_resources 0
num_tags 11
title humboldt_bath