South Florida Coastal Storm Surge and Mapping Study

Transcription

1 South Florida Coastal Storm Surge and Mapping Study Presented by Christopher Bender, Ph.D., P.E., D.CE June 2, 2015

2 Presentation Overview FEMA risk studies outline Overview South Florida surge study Work completed and project status Study methodology DEM and Mesh development Land Cover Data Analysis Site Reconnaissance Model Validation Questions?

3 FEMA Region IV Coastal Flood Risk Studies in Florida

4 SFL Coastal Surge Study Extent

5 Approach Storm Surge SWEL

6 Ongoing Efforts Model Mesh Development Developed seamless topographic and bathymetric data surface (Digital Elevation Model [DEM]) Developed SWAN+ADCIRC mesh Complete field reconnaissance study to investigate important coastal features Completed tasks in parallel Land Cover Data Analysis Field Reconnaissance Effort Model Validation

7 Seamless Topographic and Bathymetric Data Surface (DEM) Development

8 Bathymetric Data Coverage

9 SWAN+ADCIRC Model Mesh Development SWAN+ADCIRC model Finite element model Uses unstructured, triangulated mesh Node spacing set to accurately represent topography/bathymetry Applies feature arcs to represent elevated or depressed features (e.g., roads or channels)

10 SWAN+ ADCIRC Model Mesh Development SWAN+ADCIRC Model Mesh ~150 ft spacing TTSurge Model Grid ~0.5 nautical mile spacing

11 SWAN+ADCIRC Mesh Martin County

12 SWAN+ADCIRC Mesh Martin County

13 SWAN+ADCIRC Mesh Martin County; Stuart

14 North Fork St. Lucie River St. Lucie River South Fork St. Lucie River SWAN+ADCIRC Mesh Martin County; Stuart

15 Field Reconnaissance Effort; Document Coastal Features Model Mesh Development Developed seamless topographic and bathymetric data surface (Digital Elevation Model [DEM]) Developed SWAN+ADCIRC mesh Complete field reconnaissance study to investigate important coastal features Completed tasks in parallel Land Cover Data Analysis Field Reconnaissance Effort Model Validation

16 Land Classification Data Need large-coverage data sets to provide consistent and comprehensive land cover data NOAA, EPA, USGS work together to develop Coastal Change Analysis Program (C-CAP) data 25 categories of land cover emphasis given to more detailed, up-to-date wetland information than currently available in other national land cover products

17 Land Classification Data C-CAP Class No. C-CAP Land Cover Classification NLCD Class No. % Land Class in Study Area 0 Background - 1 Unclassified - 2 High Intensity Developed Medium Intensity Developed Low Intensity Developed Open Spaces Developed Cultivated Land Pasture/Hay Grassland Deciduous Forest Evergreen Forest Mixed Forest Scrub/Shrub Palustrine Forested Wetland Palustrine Scrub/Shrub Wetland 15 Palustrine Emergent Wetland Estuarine Forested Wetland Estuarine Scrub/Shrub Wetland Estuarine Emergent Wetland Unconsolidated Shore Bare Land Water Palustrine Aquatic Bed Estuarine Aquatic Bed Tundra - 25 Snow/Ice 12 -

18 Land Classification Data Working to improve methods to quantify land cover effects on storm surge Team member UCF Lidar-based assessment of vegetation field-based measurement of vegetation features Provide sensitivity study for validation models

19 Field Reconnaissance Effort; Document Coastal Features Model Mesh Development Developed seamless topographic and bathymetric data surface (Digital Elevation Model [DEM]) Developed SWAN+ADCIRC mesh Complete field reconnaissance study to investigate important coastal features Completed tasks in parallel Land Cover Data Analysis Field Reconnaissance Effort Model Validation

20 Field Reconnaissance Effort; Document Coastal Features Field reconnaissance completed at 89 locations Sites categorized into five classes 1. surge conveyance pathways and four classes of raised features; 2. other man-made embankments (roads, railroads, and bridge approaches); 3. flood protection and other hydraulic control structures; 4. natural topographic features (including dunes); 5. shoreline features (shoals, breakwaters, jetties, groins, beach nourishments)

21 Field Reconnaissance Effort; Visit representative sites Examine features and review plan for mesh geometry

22 Field Reconnaissance Effort; Create Google Earth dataset to catalog locations, notes, and photos Apply this data during mesh refinement stage

23 Field Reconnaissance Effort; Document Coastal Features Model Mesh Development Developed seamless topographic and bathymetric data surface (Digital Elevation Model [DEM]) Developed SWAN+ADCIRC mesh Complete field reconnaissance study to investigate important coastal features Completed tasks in parallel Land Cover Data Analysis Field Reconnaissance Effort Model Validation

24 Model Validation Effort; Select historical storms with significant surge and available measured data (water level and waves) Review historical tracks and data

25 Model Validation Effort; Select historical storms with significant surge and available measured data (water level and waves) Review historical tracks and data

26 Model Validation Effort; Select 5 hurricanes Betsy (1965) David (1979) Andrew (1992) Georges (1998) Wilma (2005)

27 Model Validation Effort; Select 5 hurricanes Betsy (1965) David (1979) Andrew (1992) Georges (1998) Wilma (2005)

28 Summary DEM and model mesh developed with best available data Include features that alter storm surge Challenging topographic and bathymetric features in study area Efforts to obtain best available land classification data to characterize features within the study area Apply recently developed Lidar-based techniques Major field reconnaissance study catalog major surge altering features and ensure proper mesh representation Model validation is the next phase and then production runs will develop % annual chance WSE s

29 THANK YOU