This document discusses applying geospatial visualization techniques to improve hurricane surge risk awareness and emergency management. It summarizes the capabilities and limitations of storm surge models, and demonstrates how to downscale and visualize surge model outputs to analyze potential flooding impacts at local facilities. Visualization of surge inundation at high spatial resolution can help emergency planners better communicate risk, but there are challenges around model accuracy and uncertainties that come with downscaling large-scale hydrodynamic models.

1. APPLIED GEOVISUALIZATION FOR
HURRICANE SURGE RISK AWARENESS &
EMERGENCY MANAGEMENT
George McLeod Tom Allen Keith VanGraafeiland
Old Dominion University East Carolina University CSA, International

2. Purpose
• Identify potentials and limitations of storm
surge models in GIS at a variety of scales
– Local emergency management
– Risk awareness
• Critique existing and prototype visual products
– Downscaling SLOSH models
– Online and 3D digital globe
– Desktop GIS and planimetric vizualization
• Demo use cases and future developments

3. Importance of Communication
John Englander
Author of High Tide on Main Street
Rear Admiral (Ret) David Titley
Penn State University

4. • Norfolk, VA is one of
most vulnerable areas in
US to SLR
• Land is subsiding
• Significant Population
and Military assets

6. Sandy was forecast to move slowly and have a larger/wider wind/rain field than Irene.
The width of the storm was more significant that the location of the eye.

7. • NWS most likely scenario at the time of Sandy’s
impact on Hampton Roads:
Category: 1
Direction:North bearing, parallel to coast, turning
NW over DELAWARE/New Jersey
Speed: 14 mph currently
Tide: The storm was be positioned offshore of
VA/NC during two tidal cycles. Tides were affected
by the full moon which occurred
on Oct 29/30. High tide was
approx. 1-2ft > normal.
Rainfall: 4-6 inches may
be expected
Mon 9:24 AM
Mon 9:43 PM

8. NWS Hurricane Center Forecast Model
• Category I storm, eye approaches from the South, parallel to coast, passing ODU to the east
and turning WNW over the DELMARVA peninsula

9. All active models
• MODELS are EXTREMELY VARIED. All agree that the eye of Sandy will remain offshore past the
Carolinas , but most agree that she will eventually make a NW turn into the Mid-Atlantic states near or
north of Virginia

12. Vertical Datum variation may
add to the layman’s confusion

13. http://www.broward.org/REGULATION/ENGINEERING/FLOODZONEMAPS/Pages/AboutVerticalDatum.aspx

16. SLOSH Model Interface

17. SLOSH Inputs
Spatial meteorological inputs
• Lat/Lon of storm eye
• Central atmospheric
pressure
• Radius of the maximum
winds (RMW)
• Storm track and speed
• Topography and
bathymetry
Parameters NOT used
• Surface speed
• Astronomical tides
• Waves
• Flooding
• Surface roughness

18. SLOSH Output – Sandy
• Predicts a worst case base surge of approximately 5.9 feet,
+ 2 feet for potential rain and full moon = 7.9 feet

19. Storm Surge Generalizations & Limitations
Here are several gross generalizations that can be drawn from the SLOSH
runs:
1 More intense storms cause higher surges.
2 Highest surges usually occur to the right of the storm track
(traveling with the storm) at approximately the radius of
maximum wind.
3 Fast moving storms cause high surges along open coast and low
values in sheltered bays and estuaries. Slow moving
storms usually result in greater flooding inside bays and
estuaries, with smaller values along the open coast.
4 Larger storms (greater radius of maximum wind) affect longer
stretches of the coastline.
5 Certain locations may find that storms from one direction cause
major problems, while the same storm from a different
direction causes little flooding.
6 Slosh Surge model states an accuracy of +- 20% even when all
input data are 100% accurate (category, tide, direction, speed)
7 Model does not account for rainfall totals, local wave effects, or
spring/neap tidal phases
**Modeled output errors are cumulative, LiDAR +- 2 ft accuracy.

20. Lateral Flood Encroachment

21. Facility Flooding – Analysis of Depth

22. Facility Building Vulnerability
Map represents most likely predicted
conditions based on storm track and
intensity as of 12 noon, Aug. 26.
CONDITIONS MAY VARY WIDELY FROM
THIS MAP AS STORM DETAILS CHANGE.

23. Facility Building Vulnerability
Building Max Predicted Water Depth at base
Rogers East Annex 4 ft
Ctr. for Quantitative Fisheries Ecology 3 ft
Dragas Hall 2 ft
Facilities Management 2 ft
Foundation House 2 ft
Gresham Main 2 ft
Kornblau Alumni Center 2 ft
Parking Garage E 2 ft
Rogers Main 2 ft
Visual Arts Builidng 2 ft
Ainslie Football Complex 1 ft
Art Studio Building 1 ft
Constant Hall 1 ft
Diehn Fine and Performing Arts 1 ft
Kaufman Hall 1 ft
Koch Hall 1 ft
Mechanical Room 1 ft
Powhatan Apartment 1 ft
Powhatan Sports Complex 1 ft
President's Residence 1 ft
Sailing Center 1 ft
Webb University Center 1 ft
Whitehurst Hall 1 ft

24. ODU Main Campus Flooding, 6.5 ft surge + 1 ft rain + .5 ft tide

25. ODU Main Campus Flooding, 6.5 ft surge + 1 ft rain + .5 ft tide

26. Easterly View Campus Flooding, 6.5 ft surge + 1 ft rain + .5 ft tide

27. Kaufman Mall Flooding

30. Future Challenges
1. Improving accuracy and effectiveness of storm
surge products, post-event model validation
2. Enhancing hazard awareness using
cybercartography and visualization
3. Improving coastal relief models/DEMs
4. Expanding Emergency Mgt. adoption of GIS

31. “Pushing the Button…”
• You can visualize and simulate many things in GIS, but
should you?
• It is possible to downscale hydrodynamic models
to finer spatial resolution.
+ Coarse numerical grid scale can be “carefully” post-processed
– GIS enables powerful maps but also potentially cascading errors
and miscommunication
• 3D, animated, and interactive cartography could improve
analytic risk assessment and risk communication (vs.
static maps.)
– Engage map readers
– Show dynamics and enhance comprehension
– Increase awareness and vigilance
– Meet user preferences for graphics

32. Fine Resolution Surge Maps
LiDAR DEMs and Geovisualization
•SLOSH and ADCIRC surge maps are desirable at finer
resolution than computational numerical feasibility permits
• Use improved LiDAR DEM elevations
• Develop a SLOSH MOM inundation model
• Enforce hydro-connectivity with water source layers
• E.g., flow modeling and cost distance weighting
• Vertical datum conversions, tidal prism and waves in
future versions

33. http://www.theshiftofconsciousness.info/humour4.html
What’s next? We “learn to swim”