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. 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. 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 maintain environmental quality. To protect water resources and ecology such as fish production and wetlands. To protect water resources and ecology such as fish production and wetlands. To determine water availability. To determine water availability. How does bathymetry of the estuary play a part in establishing MFLs? MFLs requires the development of hydrodynamic models. MFLs requires the development of hydrodynamic models. Models require the quantification of present day bathymetry. 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. WHY COLLECT NEW BATHYMETRY? Minimum Flow Levels (MFL) Support Minimum Flow Levels (MFL) studies WHY COLLECT NEW BATHYMETRY? Minimum Flow Levels (MFL) Support Minimum Flow Levels (MFL) studies

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

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

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

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

8. Survey Pattern SANDSEAARL

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

10. GPS Differential Reference Station Boat roves <15 km from reference station Several sites per project 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 Trackline crossing differences TINs show anomalies GIS Editing

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

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

14. EAARL: lidar (waveform-resolving) 43 km 2 /h 25 rasters/sec 25 rasters/sec waveform-resolving ( 1 nsec) waveform-resolving ( 1 nsec) EAARL Lidar Waveform-resolving: Top edge of canopy Lower edge of canopy Ground return Air/sea interface Scattering layer Bottom return Temporal resolution = 1 nsec Relsolve 1.5 cm in water t t I I

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

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

17. 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. 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. Intercomparision between the SANDS and EAARL Measurements

18. 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. 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. Intercomparision between the SANDS and EAARL Measurements

19. Datum Issues Horizontal WGS84(ITRF00 -> WGS84(original) WGS84(ITRF00 -> WGS84(original) WGS84(original) ~ GRS80/NAD83 WGS84(original) ~ GRS80/NAD83Vertical WGS84(ITRF00 -> WGS84(original) WGS84(ITRF00 -> WGS84(original) WGS84(original) -> NAVD88 WGS84(original) -> NAVD88 NAVD88 ~ WGS84(original) – Geoid ht NAVD88 ~ WGS84(original) – Geoid ht Using the GEOID99 model MLW = NAVD88 – (local constant) MLW = NAVD88 – (local constant) Conversion from GPS data to conventional datums NOAA Tidal Benchmark

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