Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tide Prediction GIS Model for Willapa Bay
1. Mapping Predicted Tidal Exposure Durations Using a LIDAR-Based MLLW Referenced Terrain Model for Treatment and Control of Spartina alterniflora in Willapa Bay, Washington Coastal GeoTools Conference Myrtle Beach, South Carolina March 7-10, 2005 Keven Bennett [email_address] Teresa Alcock [email_address] Miranda Wecker mwecker@willapabay.org University of Washington Olympic Natural Resources Center Willapa Bay Washington State
2. ONRC campus in Forks, WA University of Washington Olympic Natural Resources Center GIS Created by the Washington State Legislature Administered by the University of Washington Providing research and education to support ecologically sustainable forest and marine resources management. Vancouver Island, BC Canada Washington State
3. Photo by Fritzi Grevstad Nearly 1/3 of all viable fish and wildlife tide-flat habitat in Willapa Bay is infested with Spartina alterniflora . The bay supports shellfish and fin fisheries as well as the Willapa National Wildlife Refuge. At risk: biological diversity, the local economy… University of Washington Olympic Natural Resources Center GIS
4. Methods used to control the infestation: Chemical Mechanical Biological University of Washington Olympic Natural Resources Center GIS We use GIS for: Bay-wide planning Site-specific planning Communication among stakeholders And the public
5. University of Washington Olympic Natural Resources Center GIS Providing spatially explicit tide prediction maps for chemical treatment applications Shows when, where and for how long plants will be exposed for treatments Minimize treatment impact Optimize treatment efficacy
6. University of Washington Olympic Natural Resources Center GIS Determining appropriate areas and times for chemical applications Factors to consider: Plant growth Properties of Chemicals Tides
7. University of Washington Olympic Natural Resources Center GIS Chemical Properties Different chemicals need different minimum exposure times Leaves must be dry a certain amount of time to give the herbicide time to affect the plant Plant Growth Early season plants very short, treatment of plant low on tideflats more difficult Late season plants much taller, treatment of plants low on tideflats much easier Plant Growth and Chemical Properties
8. University of Washington Olympic Natural Resources Center GIS No fixed tide pattern Treatable areas change daily Tides vary across the bay Tidal timing variation can be greater than 1 hour Water level variation can be greater than 3 feet at any given time Several different tide tables in use Historical approximate fit with local knowledge No common tidal yardstick consistent with NOAA NOS tide prediction sites in Willapa Bay Tides
9. University of Washington Olympic Natural Resources Center GIS Change vertical datum of LIDAR derived terrain model Terrain model datum is NAVD88 NOAA NOS Tide Prediction stations datum is MLLW (Mean Lower Lowest Water) Adjust terrain model elevations to MLLW This way, we can “flood” the terrain model using “water” whose surface is interpolated from NOAA NOS tide prediction stations. Using a Common Elevation Datum to Model Tidal Prediction and Base Terrain Data
10. University of Washington Olympic Natural Resources Center GIS Referencing the Base Terrain Data Tide Datums vary from location to location Only 4 stations in Willapa Bay have NAVD88 elevations relative local MLLW datum (NOS/NGS Leveling Data Points)
11. Referencing the Base Terrain Data University of Washington Olympic Natural Resources Center GIS We interpolated a correction grid based on those 4 stations, which we then used to adjust the LIDAR-derived terrain model.
12. University of Washington Olympic Natural Resources Center GIS Nobeltec's Tides & Currents (T&C) software was found to be consistent with the NOAA NOS Tide Prediction Stations available online. Query each station for minimum water level for the desired exposure duration on each day The software also tells us when the desired event begins at each station Gathering Tide Prediction Data
13. University of Washington Olympic Natural Resources Center GIS 1. Water Levels queried in T&C are saved to tables and integrated with points corresponding to the location of each station Processing and Analyzing the Tide Prediction and Terrain Data 4. “Flood” the terrain model with the “water surface” 3. Overlay grid of Spartina heights onto the terrain model 2. These points are used to interpolate a “water surface” Anything 18" above the water surface is exposed and treatable for the desired duration.
14. University of Washington Olympic Natural Resources Center GIS 1. Capture a water line with a time and location at each point using GPS Each point on the water line is a point where the water's surface intersects the terrain. Validating the data 3. We assign this error value to each GPS point, then interpolate an error grid and adjust the terrain model. 2. Compare the terrain model at each location with a "surface“ representing the tide at each time. Any difference is an error.
16. Making this work possible: US Fish and Wildlife Service – Willapa National Wildlife Refuge Willapa Bay-Grays Harbor Oyster Growers Association Coastal Resources Alliance Pacific County Washington State University Pacific Coast Shellfish Growers Association University of Washington Pacific Conservation District Washington State Department of Natural Resources Washington State Department of Agriculture Special Thanks to: Charlie Stenvall, Jim Assenberg, Kim Patten, Mark Scott, Kyle Murphy, Lester Mehrer, David Finlayson, Wendy Brown Visit the Spartina website at www.onrc.washington.edu University of Washington Olympic Natural Resources Center GIS