Presentation by Joe Long (U.S. Geological Survey) at the XBeach X (10th Year Anniversary) Conference, during Delft Software Days - Edition 2017. Wednesday, 1 November 2017, Delft.

1. RESEARCH AND DECISION
SUPPORT APPLICATIONS OF
XBEACH AT THE USGS
Joseph W. Long
USGS St. Petersburg Coastal and Marine Science Center
With significant contributions from:
Soupy Dalyander, Rangley Mickey, Davina Passeri, Nathaniel Plant,
Chris Sherwood, Hilary Stockdon, and Dave Thompson

2. Extreme erosion during Hurricane Irene
Rodanthe, NC
Long-term cliff erosion
Pacifica, CA
National Assessment of Coastal Change Hazards
Goal: Identify, quantify, and model the
vulnerability of the U.S. shorelines to coastal
change hazards
Ongoing Tasks
 Impacts of severe storms & hurricanes
 Long-term shoreline change
 Coastal vulnerability to sea level rise
Winter nor’easter
South Kingstown Beach, RI

3. Barrier Island Evolution Research
Goal: Understand and predict decadal-scale
evolution of barrier islands.
Ongoing Tasks
 Linking geology, geochronology,
oceanography, and geomorphology
 Test and develop methods in diverse regions
that could aid in decision-making.
 Apply techniques to natural and restored
barrier island systems

4. Video by Dave Thompson
Scientific Studies

5. Participated in Early Testing and Development
• Quantified model error for
Hurricane Ivan at Santa
Rosa Island
• Included sensitivity to
unknown boundary
conditions
McCall, R. T., De Vries, J. V. T., Plant, N. G.,
Van Dongeren, A. R., Roelvink, J. A.,
Thompson, D. M., & Reniers, A. J. H. M.
(2010). Two-dimensional time dependent
hurricane overwash and erosion modeling at
Santa Rosa Island. Coastal Engineering

6. Participated in Early Testing and Development
• Established a parameter
to limit model erosion

7. Sensitivity to Boundary Conditions: Topography
• Sensitivity to initial topographic
elevations was greater than sensitivity to
model settings
Lindemer, C. A., Plant, N. G., Puleo, J. A., Thompson, D. M. & Wamsley, T. V. (2010), Numerical simulation of a low-lying barrier
island's morphologic response to Hurricane Katrina. Coastal Engineering

8. Sherwood, C. R., Long, J. W., Dickhudt, P.
J., Dalyander, P. S., Thompson, D. M., &
Plant, N. G. (2014). Inundation of a barrier
island (Chandeleur Islands, Louisiana,
USA) during a hurricane: Observed
water‐level gradients and modeled seaward
sand transport. Journal of Geophysical
Research: Earth Surface,
Observed
PRE-
storm
Elevations
Observed
POST-
storm
Elevations
Modeled
POST-
storm
Elevations
• At the same location, post-
Isaac elevations modeled
well using observed water
level gradients (ocean-to-
bay followed by bay-to-
ocean)
Sensitivity to Boundary Conditions: Water Levels

9. • ‘Reverse overwash’ (water level
sloping from bay-to-ocean) required
to simulate the observed breaching
Sherwood, C. R., Long, J. W., Dickhudt, P.
J., Dalyander, P. S., Thompson, D. M., &
Plant, N. G. (2014). Inundation of a barrier
island (Chandeleur Islands, Louisiana,
USA) during a hurricane: Observed
water‐level gradients and modeled seaward
sand transport. Journal of Geophysical
Research: Earth Surface,
Sensitivity to Boundary Conditions: Water Levels

10. Process Studies: Wave runup
Stockdon, H. F., Thompson, D. M., Plant, N. G., & Long, J.
W. (2014). Evaluation of wave runup predictions from
numerical and parametric models. Coastal Engineering
• Compared observed wave setup,
incident and infragravity swash to
parameterized and XBeach
predictions
• Underprediction of both swash
components for both 1D and 2D
simulations.
• Recent follow-up by Anne de Beer

11. Observed
post-Gustav
Elevations
Variable
Friction
(no smax)
Constant
Friction
(no smax)
Process Studies: Bed Friction
IR imagery
• Assign bed friction (Chezy
coefficients) based on the
presence/absence of
vegetation in IR imagery
• Post-Gustav elevations
modeled realistically without
activation of sheet flow
limiter
Long, J.W, D. Thompson, P.S. Dalyander (2016),
Combining remotely sensed data and numerical
modeling to investigate the impacts of vegetation
on barrier island erosion, Abstract (MG21A-03)
presented at 2016 Ocean Sciences Meeting,
AGU/ASLO/TOS, New Orleans, LA, 21-27 Feb.

12. Process Studies: Bed Friction
• Applied variable land use
information (NLCD) to
inform bed friction values.
• Skill of modeled post-storm
elevations for Hurricanes
Ivan and Katrina increased
by specifying variable bed
friction values.
Passeri, D.L., Long, J.W, Plant, N.G., Bilskie,
M.V., Hagen, S.C. (2017), The influence of
bottom friction on storm-driven barrier island
morphodynamics, Coastal Engineering (in
revision)
lidar
constant friction
varying friction

13. Process/Parameter Identification: Data Assimilation
constant
bed friction
variable
bed friction
Measured pre
Measured post
Modeled post
• Applied bed friction values to account
for vegetation and houses behind
dunes.
• Simulated Hurricane Ike with reasonable
skill.
• Use this to test data assimilation as a
way to estimate unknown boundary
values.

14. Process/Parameter Identification: Data Assimilation
topographic ensemble
ensemble mean
observed topography
corrected topography
Best guess maximum surge estimate
corrected maximum surge estimate + uncertainty
observed max surge
• XBeach can be used to estimate
unknown forcing or possibly the reverse
of estimating variable bed friction (work
in progress).

15. Decision Support Applications

16. Scenario-Based Simulations for Restoration Support
Chandeleur
Sound
Gulf of
Mexico
N
• Scenario-based analysis developed and
tested for Chandeleur Islands ‘emergency
berm’. Can the characteristics of observed
evolution an potential vulnerabilities be
predicted?
• Compared scenarios to storm-induced
response observed in satellite images.

17. Cold fronts
TS Lee Cold fronts H. Isaac
Storm Scenarios: Chandeleur Islands Emergency Berm
• Scenarios must include a range of storm events (not just tropical storms)

18. August 28, 2012
www.nasa.gov
January 26, 2012
www.nasa.gov
Scenario-Based Simulations for Restoration Support
• Historical wave and water level data
categorized in to bins according to total
water level (surge and wave runup)
magnitude and duration.
• Storms defined as events with total
water level > elevation of base of berm
• Represents both extra-tropical and
tropical storm events
Mickey, R.C., Long,
J.W., Dalyander, P.S.,
Plant, N.G.,
Thompson, D.M.
(2017). A Framework
for Modeling Scenario-
based Barrier Island
Storm Impacts to
Inform Decision-
Making. (in revision).

19. Key outcomes and benefits:
• Efficiently simulates the potential
erosion of restoration projects to a
range of storm events.
• Highlights alongshore varying areas
of a restoration design that are
especially vulnerable and could be
modified to make the project more
sustainable.
Storm Scenarios: Chandeleur Islands Emergency Berm
Mickey, R.C., Long, J.W., Dalyander, P.S., Plant,
N.G., Thompson, D.M. (2017). A Framework for
Modeling Scenario-based Barrier Island Storm
Impacts to Inform Decision-Making. (in revision).

20. Alabama Barrier Island Restoration Study
Interagency effort to investigate viable, sustainable restoration options that protect and
restore the resources of Dauphin Island, including habitat and living coastal and marine
resources, as well as protect the coastal resources of the Mississippi Sound/Mobile Bay
region.
Data Analysis
- Gulf-facing shoreline change
- Estuarine shoreline change
- Habitat mapping
- Sediment budget
Water Quality
Modeling
Structural
Response
Modeling
Habitat Modeling
Hydrodynamic &
Morphodynamic
Modeling
Restoration
Alternatives
Decision Framework
Monitoring & Adaptive
Management
Targeted Data Collection
- bathymetry
- sediment characterization
- waves/currents
- water quality
- habitat distribution

21. Hydrodynamic and Morphological Model
Components:
Storm response
O(days)
Background alongshore
transport
O(years)
Dune recovery
O(years-decades)
Sept 2005 – Post Katrina
Sept 2006 – Baseline

22. Hydrodynamic and Morphological Model
Components:
XBeach
O(days)
Delft3D
O(years)
Empirical Recovery
O(years-decades)
Sept 2005 – Post Katrina
Sept 2006 – Baseline

23. Research and skill
assessments
Application to
regional/national needs
Identify
knowledge gaps
Develop implementation
frameworks

24. Questions?
Joe Long
jwlong@usgs.gov