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Please note: this presentation has not received Director’s approval and is subject to revision.

Please note: this presentation has not received Director’s approval and is subject to revision. High-Resolution Bathymetric Mapping of the Estero Bay and Caloosahatchee Estuaries. Mark Hansen and Gina Peery – USGS Wayne Wright - NASA. WHY COLLECT NEW BATHYMETRY?

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  1. Please note: this presentation has not received Director’s approval and is subject to revision.

  2. High-Resolution Bathymetric Mapping of the Estero Bay and Caloosahatchee Estuaries Mark Hansen and Gina Peery – USGS Wayne Wright - NASA

  3. WHY COLLECT NEW BATHYMETRY? Support Minimum Flow Levels (MFL) studies What are MFLs? • Flow or level of ground or surface water at which further withdrawals of water would be significantly harmful to the water resources or ecology of the area. Why are MFLs being established? • To maintain environmental quality. • To protect water resources and ecology such as fish production and wetlands. • To determine water availability. How does bathymetry of the estuary play a part in establishing MFLs? • MFLs requires the development of hydrodynamic models. • Models require the quantification of present day bathymetry. • Present data is > 50 years old, and changes over time. • FL Statute directs the District to the use best information available.

  4. Survey Area Charlotte Harbor Matalatcha Pass Caloosahatchee River Estero Bay Offshore

  5. USGS Boat and NASA Airborne Systems SANDS (sonar) EAARL (lidar) Utilizes the best of both systems USGS survey boat - offshore NASA lidar aircraft

  6. SANDS EAARL DISADVANTAGES ADVANTAGES • R & D funded • Precision GPS based • +/- 15cm random error • Shallow water (>0.5m) • Swath coverage • Topo and bathy data • Fast • Depth limited (< 2.5 sechi disk) • Clarity limited • Limited airspace • R & D funded • Precision GPS based • +/- 8cm random error • Shallow to deep water (>0.3m) • Narrow footprint • Unaffected by clarity • Single beam sonar • Limited by waves

  7. Reference Station Position DeterminationSANDS and EAARL GPS Processing Tools OPUS (NOAA) SCOUT (Scripps) Control Spreadsheet GIPSY (JPL)

  8. Survey Pattern SANDS EAARL

  9. USGS Shallow And Nearshore Depth System (SANDS) GPS NAVSTAR Constellation Ship GPS GPS Reference Station Nav/Logging Computer Pitch/Roll Sensor Fathometer

  10. GPS Differential Reference Station • Boat roves <15 km from reference station • Several sites per project <15 km

  11. Quality Assurance/Quality Control • Adhere to known GPS limitiations • Roving distance, atmospheric conditions, #sv’s • Strict control on GPS data processing GIS Editing Trackline crossing differences TINs show anomalies

  12. NASA Experimental Advanced Airborne Research Lidar (EAARL) EAARL: airborne contributions (spatial) • Precision navigation • and position • Precision attitude • and heading • Digital photographic • camera

  13. 1 m 1 m 240 m EAARL Lidar EAARL: lidar (basic characteristics) Green laser (532 nm) High pulse rate (3000 Hz) Low power (70 mJ/pulse) Shallow depth range (0.5 – 15 m) Small footprint (15 cm) Raster scanning (25 rasters/sec) 1 x 1 m sample spacing

  14. EAARL: lidar (waveform-resolving) Top edge of canopy Lower edge of canopy Ground return Air/sea interface Scattering layer Bottom return EAARL Lidar Waveform-resolving: Temporal resolution = 1 nsec Relsolve 1.5 cm in water t I t I • 43 km2/h • 25 rasters/sec • waveform-resolving (1 nsec)

  15. EAARL Data Lidar data before false turbidity returns have been filtered out. Lidar data after false turbidity returns have been filtered out.

  16. Red lines - EARRL Blue lines- SANDS Black line- intercomparison region Light green – shallow water Deep blue – deeper water Yellow – boat track EAARL/SANDS Intercomparision Area

  17. Intercomparision between the SANDS and EAARL Measurements • 2309 comparisions. • EAARL data is with 3m of SANDS • data points. • Overestimation between -27 and • -27.5m due to the surface return • pulse becoming convolved • with the bottom return pulse. • Will be corrected in the final • data set.

  18. Intercomparision between the SANDS and EAARL Measurements • 2309 comparisions. • EAARL data is with 3m of SANDS • data points. • Overestimation between -27 and • -27.5m due to the surface return • pulse becoming convolved • with the bottom return pulse. • Will be corrected in the final • data set.

  19. Datum Issues Conversion from GPS data to conventional datums Horizontal • WGS84(ITRF00 -> WGS84(original) • WGS84(original) ~ GRS80/NAD83 Vertical • WGS84(ITRF00 -> WGS84(original) • WGS84(original) -> NAVD88 • NAVD88 ~ WGS84(original) – Geoid ht Using the GEOID99 model • MLW = NAVD88 – (local constant) NOAA Tidal Benchmark

  20. Final Products • Tabular XYZ data • Contoured data • Grids • USGS quadrangle style maps

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