SLOSH to Evac

1. SLOSH to Evac How it is done……

2. Gloss over process…. • LIDAR is flown to get high res elevation • Contractors create ‘reduced DEM’ • Contractors create SLOSH input data: • Basin polygon containing avg elev as integer • SLOSH input variables with barriers, trees….. • Input basin files given to NHC • NHC runs SLOSH model with many storms • Data put into SLOSH Display Program • Basin MEOWS & MOMs exported to GIS

3. Average Elevation Values for each Grid Square This is essentially what The NHC gets as input For SLOSH model for elevation

4. MOM Values for Category 3 These are the end result values for Cat 3. Notice they are fractional, and not integers. This is because the calculations output less than whole numbers.

5. More on the data…. • The SLOSH basins are unmovable • The shape is based on bathymetry, storms • MEOWS are output (runs for different approaches) • The MOMs have highest possible values • Highest of all the MEOWs for each Category • About a thousand storm sims were run • Wave action is not calculated • Still a 20% variation on possible outcomes

6. …and what about those Averages? • As mentioned, elevation was averaged per Grid square • This reduces the calculation overhead in the SLOSH runs • Precisely why important to run Surge Model (RPC) after: • Higher resolution ‘brings back’ the highs and lows of each Grid • Real world isn’t flat and square-cornered like the Basin Grids • SLOSH Display Program (SDP) still uses the elevation averages for depth calc…but then the resolution is low, with larger areas to be considered. • Elevation and elevation-derived depth calcs all must use the same datum.

7. This is not what the real world is like…… Average Surge Height Average Surge Height Average Surge Height Average Surge Height SLOSH grids actually much bigger

8. Modeling MOM Values • The previous slide demonstrates the surge heights (which are based on average elevation per grid) in MOM basin with square edges • We know that water does not behave like this • How do we get a realistic depiction of surge height with respect to the real terrain underneath? • Interpolation of grid heights • Creates a smooth surface for further topographical processing • Two types exist: Inverse Distance Weighted and Spline • Spline is the best for surfaces that don’t change sharply like water • Spline, by definition has to have the value equal original at centroid • IDW can approximate values (height), but not exactly where needed • The results allow a realistic depiction of inundation of terrain

9. This is LIDAR DEM exaggerated to show relief in flat Florida. This is the Ozona/Palm Harbor portion of Pinellas County.

10. This same area with SLOSH MOMs in their default square basin form. Circled area would be devoid of surge if not interpolated.

11. You can see how the interpolation hugs the terrain as in real life. That is when a model is truly successful.!

12. How the interpolation represents the MOM values Average Elevation for Grid is 20.11 Cat 3 = DRY The surge is not flat and neither is terrain!

13. Let’s Review: • The modeling AFTER the SLOSH model output is refined for real-world topography and zone delineation • Square unrealistic (at higher resolution) basin grids are modeled into smooth ‘water-surface-like’ values • Original centroid & nearby values remain exactly as NHC determined by using Spline, preserving intended results • The smooth surface can then be used for detailed calculation to delineate the interface with terrain

14. The average elevation (green values) can appear to be dramatically different to the adjacent grid, as it can include a very high area and/or very low area. This is another reason there should be a smooth transition offered by the interpolation. Still, with interpolation, the values between any nearby MOM grid varies only by inches to perhaps 2 feet.

15. Create the Surge Zones • The most visible part of this process is the inundation zone delineation • SLOSH (smooth surface) values for each category storm are used in subtracting terrain to get areas that could be inundated by the MOM in category • This is all performed in the raster domain using GIS. The digital elevation model (DEM) from the LIDAR is key in getting high resolution boundaries • In 2010, we used raster cell size of 5x5 feet which can then produce polygons with as little as 5 feet between vertexes (however, a generalization algorithm removes redundant vertexes)

16. Here, you can see individual pixels of DEM raster

17. Results of the modeled SLOSH values with LIDAR-derived terrain Here we actually have surge, whereas if we used raw average value of MOM (99.9), this whole grid would escape inundation

18. Next Steps • The individual Storm Category zones are merged into a single shapefile or geodatabase with field values depicting inundation • Emergency Managers for counties, then use this information to delineate Evacuation Zones • Evacuating by surge zone boundaries is difficult, if not impossible. So, for public safety – zones for evacuation are defined on real-world boundaries: • Some method is used to select street and neighborhood blocks that flood (usually GIS) • Overlaying the Surge Zones on street-derived polygons is the easiest method with some percentage inundation ruleset. Some counties will digitize boundaries. Some may even choose to use Census Blocks, Block groups, zip codes, or even parcels.

19. Evacuation Zone results using Surge Zones

20. Improvements over earlier versions: • New SLOSH basin at higher resolution (smaller squares) • Same Datum used throughout process • Terrain raster (DEM) uses 5ft cells vs 2005 version 9ft (3m) • 1991 SLOSH basin based on USGS interpolated elevation (hypsography) – 2010 version on LIDAR derived 50ft elevation

21. Thank You