1. Tom Ravens and Jon Allen, Univ. of Alaska Anchorage
Projection of Storm Surge Impacts on the YK Delta Vegetation under Climate Change
Kashunuk R.
10 km
10 km
Tom Ravens and Jon Allen, Univ. of Alaska Anchorage

2. Current vegetation
Projected vegetation, 40 cm SLR
Projected vegetation, 80 cm SLR
Projected vegetation, 120 cm SLR

3. Research Goal: Project YK Delta vegetation change due to storm surges – enhanced by sea level rise
Tasks:
Develop and validate a storm surge and inundation model
Identify a number of representative storms from the past 20 years
Model these storms and their inundation under present climate conditions
Re-model these storms assuming 3 sea level rise scenarios
Compute an inundation index from each model run
Compute an annual inundation index based on inundation indices from selected storms (for each scenario)
Establish the relationship between annual index and vegetation type under present climate
Infer changes in vegetation type under a future climate based on projected changes in annual inundation index

4. Storm surge modeling - course grid model domain
YK Delta

5. Fine-grid model domain and bathymetry and topographic data
Kashunuk River
Hooper Bay

6. Assessment of course-grid (ADCIRC) model at Nome
---- measured water level, modeled water level
2011 storm
Good performance
2005 storm
Marginal performance

7. Assessment of course-grid ADCIRC model performance at the Nome site
Date of storm
Assessment
Nov. 2011
Good
Nov. 2009
Bad (model missed peak of this small storm)
Oct. 2006
Sept. 2005
Marginal - model 0.5 m too low, measured peak at Nome = 2.7 m
Oct. 2004
Oct. 1992
Marginal - model 0.5 m too low, measured peak at Nome = 2.3 m

8. Assessment of course-grid/fine grid model system for coastal water level
2009 storm
Good performance
2011 storm
Marginal performance

9. Reasonable performance
Assessment of course-grid/fine grid model system for coastal flooding extent
2006 storm
Reasonable performance
(over-calculation)
2005 storm
Marginal performance
(under-calculation)

10. Conclusions from model assessment phase
Overall performance of model system was below expectations.
For ecological modeling purposes, the forcing on the ocean boundary of the fine-grid model was adjusted to get good results.
Accurate simulations of storms from 2005, 2006, 2009, and 2011 were obtained.
The 2005, 2009, and 2011 storms were assigned return periods of: 11, <2, and 3.5 years, respectively, based on the return period analysis.

11. Return period calculation – based on surge height and volume
Ordering of storms based on peak surge height at coast near center of domain
Ordering of storms based on peak volume of flooding
2005 storm is 14 year storm
2005 storm is 11 year storm

12. Tabular return period data
Return period based on volume:
Water level and flood volume for different return periods:
Storm
Return period (yr)
1995 Oct
15.25
2004 Oct
11.04
2005 Sept
10.78
1996 Oct
6.03
1992 Oct
5.03
2011 Nov
3.49
1996 Nov
2.00
Return Period (yr)
Water level at Hooper Bay offshore node (m)
Max Instantaneous Surge Volume (108 m3) 2
3.00
7.8 5
3.39
18.0 10
3.65
24.7 20
3.90
31.2 50
4.22
39.5
100
4.46
45.7

13. <2 year storm (2009), 2.5 m 10.8 year storm (2005), 3.7 m
Nov. 2011

14. GMT
AK time

15. Storm Inundation Index (<2 year storm, 2009)
Legend
[m-days]

16. Storm Inundation Index (3.5 year storm, 2011)
Legend
[m-days]

17. Storm Inundation Index (10.8 year storm, 2005)
Legend
[m-days]

18. Annual inundation index – current climate
[based on weighted average of storm indices,
(½ x 2 yr + 1/8 x 8 yr + 1/12 x 12 yr + 1/50 x 50 yr) x 0.729]
Legend
[m-days/yr]

19. Correspondence between annual inundation index and vegetation type under current climate
Legend
[m-days/yr]
Annual
Inundation
index
Legend
[vegetation type]
Vegetation
type

20. Area for developing relationship between annual inundation index and vegetation type
Selected due to local LiDAR coverage and high elevation-vegetation type correlation

21. Relationship between Annual Inundation Index and Vegetation Type
[m-days/yr]
Vegetation Type

22. Slightly brackish-brackish cutoff not clearly defined, thus potentially significant misclassification.
Due to low counts of saline points, brackish-saline cutoff inexact.

23. Current Annual Inundation Index (AII)
Annual Inundation Index, 40 cm SLR
AII (m day / yr)
Annual Inundation Index, 120 cm SLR
Annual Inundation Index, 80 cm SLR

24. Current vegetation
Projected vegetation, 40 cm SLR
Projected vegetation, 80 cm SLR
Projected vegetation, 120 cm SLR

25. Conclusions
Annual inundation index well-correlated with vegetation type.
Calculated annual inundation based on sea level rise scenarios is a reasonable basis for projecting vegetation change in the future.
Significant shifts in vegetation are expected with sea level rise considered.

26. Future Work Finalize work on return period analysis.
Finalize work on storm surge modeling.
Examine the relationship between inundation index and bird/nest abundance.
Model and analyze pond water quality.
Model and analyze geomorphic change.
Real time forecasting of flooding on YK Delta and in Norton Sound for DHS

27. ADAC coastal inundation forecast– big view

28. ADAC coastal inundation forecast

29. Forecast data at a point

30. Collaborators and supporters
Craig Ely, John Terenzi (USGS, Alaska)
Torre Jorgenson (Ecoscience)
Raymond Chapman, Ken Eisses (USACE)
Steven Gray (USGS AK Climate Science Center)
Joel Reynolds, Karen Murphy (Western Alaska Landscape Conservation Cooperative)
Sarah Saalfeld (USFWS)

31. Questions?