Application of the Beach-fx Economic Model in St. Johns County, Florida



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Application of the Beach-fx Economic Model in St. Johns County, Florida Jason Engle, P.E. Jacksonville District USACE US Army Corps of Engineers

Beach-fx Introduction St. Johns County Study Area Overview of Economic Data Requirements Details of Engineering Input Development Future Work

Beach-FX Overview Developed by the US Army Engineer Coastal Hydraulics Lab and the Institute for Water Resources (IWR) Economic storm damage model for sandy coastlines PC-based, GIS compatible Only approved/certified economic model for Federal Coastal Storm Damage Reduction studies

Beach-FX Overview Merges engineering and economic data Predicted storm response Database of damage elements Simulates project lifecycles 50-years, 300 lifecycles Outputs Average annual costs with/without project Alternative evaluation/optimization

Why Common Context for Local/Regional/National Prioritization of Projects Previous models locally-developed Inconsistent model assumptions Inadequate coastal processes Varying levels detail economic input

Study Area SOUTH PONTE VEDRA VILANO BEACH ST. AUGUSTINE INLET MATANZAS INLET SUMMER HAVEN FLAGLER COUNTY

Beach-fx Development Formulation of input data Economic Engineering Calibration Without-project simulations Alternative evaluation

Economic Inputs Geographic hierarchy Profiles, reaches, lots, damage elements Damage elements: anything of economic value Roads Buildings Pools Dune walkovers

Economic Inputs Reach/Lot/DE Attributes Armor status Armor rebuild cost/time Armor failure threshold Structure type Construction type Foundation type # Floors Dimensions XY coordinates Elevation Structure replacement $ Contents replacement $ GIS structure database has value beyond Beach-fx

Beach-fx Engineering Inputs Plausible storms Representative beach profiles Shore response database: storm induced profile changes

Historical Storms Tropical Storms/Hurricanes Derived from NOAA HURDAT database 1887-1999 Water levels: HURDAT Waves: FCFP, WIS, SPM method St. Johns: 46 tropical storms/hurricanes Extra-tropical (Nor easters) NASA GISS Extra-tropical Storm Tracks (1961-1998) Water levels: NOS gage data Wave data: FCFP, WIS St. Johns: 48 storms

Plausible Storms Potential water levels occurring during passage of Tropical storms 3 Tide ranges: spring, neap, mean 4 tide stages: high, mid-falling, low, mid-rising 12 static water surface elevations 12 elevations x 46 storms 552 tropical storms + 48 nor easters Total of 600 plausible storms Used for both St. Johns and Flagler Counties

Representative Profiles Analysis of historical profile data Regions with similar profile dimensions 30 20 10 Representative Profile (P5) Dune averaged profile aligned at 15 ft. Foreshore slope averaged profile aligned at 2 ft. Offshore averaged profile aligned at -25 ft. Within segment, averages taken through three sections St. Johns: 15 representative profiles Elevation (ft, NAVD88) 0-10 -20-30 -40-500 0 500 1000 1500 2000 2500 3000 3500 4000 Distance Offshore (ft)

Simplified Profile Upland elevation Dune height Width Slope Berm Height Width Foreshore slope

Shore Response Profiles Starting with representative profile Range of possible future profiles Increments between a max/min profile St. Johns: 229 response profiles 25.00 20.00 15.00 10.00 5.00 0.00-400.00-300.00-200.00-100.00 0.00 100.00 200.00

Shore Responses SBEACH run for every profile/storm combination St. Johns: 600 storms x 229 profiles = 137,400 SBEACH runs SBEACH batch-run tool 30 batch runs Shore Response Database (SRD)

Shore Response Database SRD: database of storm-induced changes Berm width dune height dune width SBEACH calibrated for performance based on these three parameters

Beach-fx Calibration Goal: average erosion of many lifecycles = measured historical erosion Two model parameters Storm erosion: berm width recovery factor (~90%) Background erosion: applied erosion rate (ft/yr) Calibration not as time consuming as on engineering models like SBEACH, GENESIS

Summary GIS D.E. database a somewhat daunting task, but a valuable data set that can easily be integrated into a local/regional/state GIS databases. Engineering input data larger, but analysis is not more complicated use familiar engineering models. Coastal processes model are run outside of Beachfx, any improved/new models can easily be substituted in the future.

Future Work St. Johns County Beach-fx Complete without-project model runs Alternative evaluation/optimization Sensitivity testing of input variables First floor elevation Statistical assignment of D.E. variables

Jason Engle, P.E. jason.a.engle@usace.army.mil