1. No category

The Changing Landscape of North Carolina
Shoreline Change, Sea level rise, and Storms
Reide Corbett*
*with help from JP Walsh, Ben Horton, Andy Kemp, Jeff Donnelly and many others
Change of
the NC
Estuarine
Coast
Riggs and Ames, 2003
Why is NC
vulnerable to
coastal hazards?
Kemp et al., 2009
• Low, extensive
• Geology
• Dynamic setting
• Humans
Defining the Coast
>12,000 miles of estuarine shoreline
Defining the Coast
…and the Key Processes leading to Change
GIS Data Obtained
• Shoreline position and type
– Marsh
– Swamp forest
– Sediment bank
– Modified with engineered structure
– Miscellaneous
• Line Structures
– Vertical structures (bulkheads)
– Breakwaters
– Groins and jetties
– Sloped structures
– Sills
• Polygon Structures
– Boat ramps
– Bridges
– Piers, floating docks and wharfs
High-Resolution Mapping of the NC Shoreline
Dare County
Example
Interactivity - DENR
http://ims.ncdenr.org/Website/ncshore/viewer.htm
Interactivity – NC Coastal Atlas
http://www.nccoastalatlas.org
How can we analyze this extensive data set…
– General statistics
– Focus by specific regions
– Hot-spot analysis
Wrightsville Beach
Results
Data Highlights
Statewide Estuarine
Shoreline Statistics
Swamp Forest
Marsh
Sediment Bank
Modified
Miles
2,490
8,039
1,189
601
Total
12,319
5%
10%
20%
Swamp
Forest
Marsh
Sediment
Bank
Modified
65%
Hot spot size
(12.5 mile diameter)
Analyzing Estuarine Shoreline Change
in Coastal North Carolina
Partnership with NOAA to
develop a Hazard Vulnerability
Assessment (HVA) index.
Included:
o Shoreline Change
o Inundation
o Social Vulnerability (SoVI)
This was completed in pilot
regions within NC, SC, Ga,
and Fl.
Partnership with NOAA to
develop a Hazard Vulnerability
Assessment (HVA) index.
Included:
o Shoreline Change
o Inundation
o Social Vulnerability (SoVI)
This was completed in pilot
regions within NC, SC, Ga,
and Fl.
So, with time, the shoreline is a
moving boundary…
Need to consider: sea-level rise
B
A
Uncertainty surrounds sea‐level predictions, models need
to be constrained by data. Proxy salt marsh data uniquely
extend the time series.
Study areas – SLR
Salt-marsh proxy sea-level data will be collected from four
study to reflect regional variability
Example from North
Carolina
* Microtidal
* GIA subsidence
* Thick, continuous sequences
of salt-marsh peat
Tump Point, NC
Field team
GlA adjusted sea level in NC
Kemp et al., 2011
•Salt marsh proxy data correlate with local tide gauge records
•Sea level
departed from
stability during the
past 2000 years
+0.6 mm/yr
+2.1
•Changes are
broadly
synchronous with
known climate
deviations –MCA
and LIA
•Acceleration in
late 19th century
stands out in all
records
•20th century sea –
level rise is without
precedent for at
least 2500 years
Sea Level Data
(Instrumental and Paleo)
Sea Level
Modeling
Tropical Cyclone and
Climate Data
and Climate Model Output
Tropical
Cyclone and
Surge Modeling
Future Regional Coastal
Inundation Scenarios
Information Transfer to
Decision Makers
Modeled storm surge for Cat 3 hurricane.
What Might the Future Hold?
Frequency of
hurricanes
may increase
(particularly
intense storms)
From Emanuel, 2013 PNAS
Using IPCC AR5 models
Conclusions
• The coast of NC is extensive and complex.
• It is a dynamic boundary that has changed
throughout geologic history and this change will
continue…
• We must work across institutions/agencies and use
the best available data and empirical relationships to
consider future change.
• Understanding processes driving change and
methods to slow that change are key to future
management.
Thank You…
Funding provided by NC DENR,
APNEP, NOAA, USGS, NSF
•
•
•
•
Methods
Heads-up Digitizing (Geis and Bendell, NCDCM, 2008)
ArcGIS, PC with dual-monitor and digitizing pen
20 Coastal (CAMA) Counties
1:300-500 scale; Up to 20 ft stream width
North
Carolina
•‘Fossil’ foraminifera provide estimates of former sea levels (± 10 cm)
•Age-depth model estimate most likely accumulation history. Reduces error and
estimates age of any sample (Decadal Resolution)
Kemp et al., 2009
When did modern sea-level rise begin?
Proxy and instrumental records agree. Common to all sites.
Salt Marshes and Sea Level
Brigantine, NJ
Distribution intrinsically linked to sea level and the tides
Distinctive pattern of floral zonation (tolerance of frequency
and duration of inundation)
Thick sedimentary sequences are archives of sea-level change
Reconstructing Relative Sea Level
A sea-level indicator is needed to reconstruct RSL
Biological, chemical, or physical feature with a strong
relationship to tidal elevation
Salt-marsh foraminifera are sea-level indicators
Drivers of Spatial Variability in Western North Atlantic
Fingerprints of melt, dynamic ocean circulation
Static Equilibrium: The “fingerprint” of sea-level rise
The Gulf Stream and
Ocean Dynamic SeaLevel Change
Slower Gulf Stream
= more/faster sealevel rise
The GS has…a continuous weakening
trend since about 2004 and this
trend may be responsible for recent
acceleration in local SLR (Ezer et al.,
2013)
Sallenger et al. (2012)
Spatial Variability on the U.S. Atlantic Coast
Lund et al., 2006
Spatial pattern indicates role for Gulf
Stream. Greenland ice melt very
unlikely.
Measured by instruments over
months to years. Is it possible for
multi-century periods?
Yrs BP
0
500
1000
Regional Sea-Level Projections (Wilmington, NC)
Kopp, Horton, Kemp, and Tebaldi, in review
What Might the Future Hold?
N. Atl. Tropical SST
N. Atl. Tropical Cyclones
N. Hem. Mean Temp
From
Coumou and Rahmstorf, 2012
Nature Climate Change
Recent instrumental data points to SST changes driving tropical cyclone activity.
What Might the Future Hold?
N. Atl. Tropical SST
Frequency of
hurricanes
may increase
(particularly
intense storms)
N. Atl. Tropical Cyclones
N. Hem. Mean Temp
Using IPCC AR4 models
“Best Case”
TC downscaling of AR4
scenarios indicates significant
increases in TCs threatening
US eastern seaboard by 2200
AD.
Modern
“Worst Case”
What Might the Future Hold?
Rate of sea-level rise will continue to accelerate
IPCC AR5
The suite of 10,000 synthetic storms generated for the New River Estuary have been used to estimate return
intervals for both storm events and, by running each storm event through SLOSH, to calculate surge statistics
as a function of storm category (Figs. 43 and 44). Results shown for New River Estuary are filtered for events
coming within 125 km of a point along the coast between Wilmington and New River Estuary . The diameter
of this circle is roughly the same as a coastal segment from Myrtle Beach to Cape Lookout. About 15% of the
10,000 east coast storms pass through this region and virtually all of the storms generating at least 0.5m surge
at New River Estuary pass within it. We have chosen to use the radius method to include storms that may
parallel the coast either to the east or west that could still generate surge but which would not intersect a
coastal segment.
Return times for surge levels at New River Estuary under modern climate and sea-level conditions.
Return intervals are: 1m surge -28 years; 2m -240 years; 3m -3750 yrs.
Inundation statistics for the New River Estuary estimated using a suite of 10,000 synthetic storms and the NOAA
SLOSH model to calculate storm surge levels. Return intervals for storms of each category are in the parentheses.