Hurricane Sandy Impacts on Coastal Wetland Resilience

Open-File Report 2018–1142

U.S. Department of the Interior

U.S. Geological Survey
Cover. Salt marsh dominated by Spartina alterniflora at Fire Island National Seashore, Long Island, 

New York, about two weeks after passage of Hurricane Sandy. Photograph by James Lynch, National 

Park Service, Northeast Coastal and Barrier Network, Washington, D.C., November 13, 2012.
Hurricane Sandy Impacts 

on Coastal Wetland Resilience

By Donald R. Cahoon, Jennifer H. Olker, Alice G. Yeates, Glenn R. Guntenspergen, 

James B. Grace, Susan C. Adamowicz, Shimon Anisfeld, Andrew H. Baldwin, 

Nels Barrett, Leah Beckett, Alice Benzecry, Linda K. Blum, David M. Burdick, 

William Crouch, Marci Cole Ekberg, Sarah Fernald, Kristin Wilson Grimes, 

Joseph Grzyb, Ellen Kracauer Hartig, Danielle A. Kreeger, Marit Larson, 

Scott Lerberg, James C. Lynch, Nicole Maher, Martha Maxwell-Doyle, 

Laura R. Mitchell, Jordan Mora, Victoria O’Neill, Angela Padeletti, Diann Prosser, 

Tracy Quirk, Kenneth B. Raposa, William G. Reay, Drexel Siok, Christopher Snow, 

Adam Starke, Lorie Staver, J. Court Stevenson, and Vincent Turner

Open-File Report 2018–1142

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Acting Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2019

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Suggested citation:

Cahoon, D.R., Olker, J.H., Yeates, A.G., Guntenspergen, G.R., Grace, J.B., Adamowicz, S.C., Anisfeld, S., Baldwin, A.H., 

Barrett, N., Beckett, L., Benzecry, A., Blum, L.K., Burdick, D.M., Crouch, W., Ekberg, M.C., Fernald, S., Grimes, K.W., 

Grzyb, J., Hartig, E.K., Kreeger, D.A., Larson, M., Lerberg, S., Lynch, J.C., Maher, N., Maxwell-Doyle, M., Mitchell, 

L.R., Mora, J., O’Neill, V., Padeletti, A., Prosser, D., Quirk, T., Raposa, K.B., Reay, W.G., Siok, D., Snow, C., Starke, A., 

Staver, L., Stevenson, J.C., and Turner, V., 2019, Hurricane Sandy impacts on coastal wetland resilience: U.S. Geological Survey Open-File Report 2018–1142, 117 p., https://doi.org/10.3133/ofr20181142.

ISSN 2331–1258 (online)
iii

Acknowledgments

Requests for individual SET – MH datasets, and associated metadata, used in this report should 

be made to the authors and their institutions provided in the authors’ list [see below] and the 

people listed in the acknowledgements that provided data but opted not to be an author [see 

below]. USGS datasets will be available in late 2019 in Science Base https://www.sciencebase.gov/catalog/.

We wish to acknowledge the following people and institutions that provided data in support of 

this project (names presented alphabetically):

Robert R. Christian, East Carolina University, Greenville, North Carolina

Patricia Delgado, Jug Bay Wetlands Sanctuary, Anne Arundel County, Maryland

Lyndie Dice-Hunton, Delaware Department of Natural Resources and Environmental Control, 

Delaware Coastal Programs, Dover, Delaware

R. Michael Erwin, U.S. Geological Survey (USGS), Emeritus

Anne Giblin, Hap Garritt, Karen Sundberg, and Samantha Bond of the Plum Island Estuary LongTerm Ecological Research site, Massachusetts (funded by National Science Foundation [NSF] 

Plum Island Ecosystems – Long Term Ecological Research [PIE-LTER] 1637630 and 1238212)

Lora Harris, University of Maryland Center for Environmental Science, Chesapeake Biological 

Laboratory, Solomons, Maryland

Kelly Hines Leo, New York Habitat Restoration Coordinator, New England and Interstate Water 

Pollution Control Commission, New York State Department of Environmental Conservation, 

Long Island Sound Study, East Setauket, New York

Patrick Megonigal, Adam Langley, and Thomas Mozdzer of the Smithsonian Global Change 

Research Wetland [funded by the NSF- Long Term Research in Environmental Biology [LTREB] 

Program (DEB-1557009), Department of Energy-Terrestrial Ecosystem Science [TES] Program 

(DE-FG02-97ER62458), USGS (G10AC00675), and the Smithsonian Institution].

Geoffrey Sanders, National Park Service, Washington, D.C.

R. Scott Warren, Connecticut College, New London, Connecticut

Patricia Wiberg, University of Virginia, Charlottesville, Virginia

U.S. Fish and Wildlife Service staff in the northeast United States, including

Nathan Bush, U.S. Fish and Wildlife Service, Northeast Regional Office, Hadley, Massachusetts

Paul Castelli, Edwin B. Forsythe National Wildlife Refuge, Oceanville, New Jersey

John Gallegos and Geralynn Mireles, Back Bay National Wildlife Refuge, Virginia Beach, Virginia

Ben Gaspar, Rhode Island National Wildlife Refuge Complex, Charlestown, Rhode Island

Curt Kessler and Monica Williams, Long Island National Wildlife Refuge Complex, Shirley, 

New York
iv

We wish to acknowledge the following organizations for their funding and logistical support:

Shimon Anisfeld thanks the U.S. Environmental Protection Agency and Connecticut Sea Grant 

for funding to install and monitor surface elevation table (SET) stations.

Andrew Baldwin—Work was funded by a grant from the Department of Energy’s National Institute for Climatic Change Research awarded to Andrew Baldwin (P.I.), Michael Kearney, David 

Tilley, and Jeffrey Cornwell; award number TUL-543-06/07.

Alice Benzecry gratefully acknowledges the support of Fairleigh Dickinson University and 

Meadowlands Environmental Research Institute (MERI) for funding to install and monitor SET 

stations. http://meri.njmeadowlands.gov/projects/sea-level-rise-measurements/.

Linda Blum - SET and marker horizon (MH) data collection is based upon work supported by the 

NSF under Grants No. BSR-8702333-06, DEB-9211772, DEB-9411974, DEB-0080381, DEB0621014 and DEB-1237733. The Virginia Coast Reserve of the Nature Conservancy provided 

access to study sites. Database citation for this dataset is Blum and others (2017).

David Burdick gratefully acknowledges the support of Great Bay National Estuarine Research 

Reserve (NERR) and Wells NERR, the New Hampshire Coastal Program of the New Hampshire 

Department of Environmental Services, and National Oceanic and Atmospheric Administration 

(NOAA), Coastal Zone Management (CZM).

Marci Cole Ekberg - The Save the Bay SET stations in Rhode Island were funded by a grant from 

the NOAA Restoration Center.

Sarah Fernald - SET stations in the Tivoli Bays were installed with NOAA funding from the 

Hudson River National Estuarine Research Reserve Operations Grant #16, NOAA grant 

NA07NOS4200118.

Kristin Grimes - SET stations at Wells NERR funded by NOAA NA14NOS4200036.

Nicole Maher - The Nature Conservancy in New York acknowledges the generous financial support for this work from the Zegar Family Foundation and the Pritchard Charitable Trust.

Angela Padeletti—Partnership for the Delaware Estuary (http://www.delawareestuary.org/

science-and-research/wetlands/): Mid-Atlantic Coastal Wetland Assessment, Site Specific 

Intensive Monitoring Database: Surface Elevation Tables & Marker Horizons [2011–16]. Previous and continued data collection supported by U.S. EPA Region 2; U.S. EPA Region 3; U.S. 

EPA HQ; DNREC Wetland Assessment; Barnegat Bay Partnership; New Jersey Coastal Zone.

Kenneth Raposa—Financial support was provided in part by a grant under the Federal Coastal 

Zone Management Act, administered by the Office of Ocean and Coastal Management, 

NOAA, Silver Spring, Maryland.

William Reay—Maintenance and monitoring of Chesapeake Bay National Estuarine Research 

Reserve (CBNERR) SET-MH stations are supported, in part, by NERR operational awards from 

the Office of Ocean and Coastal Management, NOAA.

Lorie Staver—Financial support was provided by the Maryland Port Authority, Port of Baltimore; 

and the Maryland Environmental Service.

We wish to acknowledge the following people for assistance in field data collection and management, and in report preparation:

Jessie Buckner, Barnegat Bay Partnership, Toms River, N.J., assisted in data management and 

collection. Melanie Mills, Academy of Natural Sciences, Philadelphia, Pa., assisted in data collection and management. We thank Kristi Nixon, Natural Resources Research Institute, University of Minnesota Duluth, for GIS assistance. Ellen Kracauer Hartig thanks New York City Parks 
v

partners Rebecca Boger of Brooklyn College, City University of New York (CUNY), for providing 

funding for installing additional stations and Alice Benzecry of Fairleigh Dickinson University and 

her students who assisted with monitoring. Jenny Allen and Amanda Garzio-Hadzick assisted 

in the field at the Chesapeake Bay National Estuarine Research Reserve in Maryland. We thank 

Toni Mikula and Kate O’Brien at Rachel Carson National Wildlife Refuge (NWR), and Curtis 

George at Bombay Hook NWR for their support. Shimon Anisfeld thanks Troy Hill for assistance 

in monitoring SET-MH stations. In New England, Roelof Boumans, Larry Ward, and Chris Peter 

assisted in field work. Shannon Beliew, U.S. Geological Survey, Patuxent Wildlife Research 

Center, updated the map figures for publication.
vi

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................2

Study Area and SET-MH Stations ......................................................................................................3

Objectives...............................................................................................................................................3

Inventory and Distribution of SET-MH Stations Along the Atlantic Coast............................................3

Data Formatting and Analyses.....................................................................................................................6

Location and Distribution of Stations .........................................................................................................7

Metadata Summary.......................................................................................................................................8

Hurricane Sandy Effects on Coastal Marsh Elevation Change..............................................................8

Introduction.....................................................................................................................................................8

Physical Characteristics of the Storm...............................................................................................8

Hypotheses ..........................................................................................................................................10

Methods.........................................................................................................................................................10

Eligible SET-MH Stations ...................................................................................................................10

Elevation Response Variable ............................................................................................................12

Predictor Variables ............................................................................................................................13

Variables Representing Storm Exposure and Intensity ...............................................................13

Distance to Storm Landfall.......................................................................................................13

Exposure to Storm Surge (Within or Outside Surge Zone) .................................................13

Geomorphic Setting...................................................................................................................13

Position Relative to Storm Landfall.........................................................................................13

Additional Variables to Account for Unexplained Variance........................................................14

Coefficient of Variation .............................................................................................................14

Rate of Change...........................................................................................................................14

Correlation Between Predictor Variables..............................................................................14

Structural Equation Model ................................................................................................................14

Model Building ...........................................................................................................................14

Model Assessment....................................................................................................................14

Spatial Autocorrelation.............................................................................................................14

Statistical Programs and Packages Used ......................................................................................16

Results ...........................................................................................................................................................16

Correlation Between Predictor Variables.......................................................................................16

Distribution of SET-MH Stations Used in Effects Analysis...........................................................16

Deviation from Expected Surface Elevation Change Model .......................................................16

Storm Surge Submodel......................................................................................................................21

Structural Equation Model Selected for Interpretation ...............................................................24

Discussion.....................................................................................................................................................25

Spatial Variation in Storm Impacts ..................................................................................................25

Implications for Marsh Resilience...................................................................................................28

Factors to Consider in Development of a Strategic Monitoring Framework ....................................29

Methods.........................................................................................................................................................29

Spatial Analysis ..................................................................................................................................29
vii

Incorporating Risk—Data Sources and Application .............................................................................30

Results ...........................................................................................................................................................31

Spatial Distribution of SET-MH Stations ........................................................................................31

SET Station Distribution Within a Subregion .......................................................................33

Incorporating Risk...............................................................................................................................33

Risk of Hurricane Strikes and Storm Surge by Subregion..................................................34

Discussion.....................................................................................................................................................34

Conclusions...................................................................................................................................................50

References Cited..........................................................................................................................................50

Glossary.........................................................................................................................................................55

Appendix 1. The Surface Elevation Table-Marker Horizon Method ................................................59

Appendix 2. SET-MH Metadata Spreadsheet......................................................................................63

Appendix 3. Best Model Summaries...................................................................................................117

Figures

1. A, Map showing Hurricane Sandy track and intensity, as well as locations of

moored National Oceanic and Atmospheric Administration (NOAA) National Data

Buoy Center buoys recording wave height and period. B, Nighttime image of

Hurricane Sandy captured 16–18 hours before landfall by the Visible Infrared

Imaging Radiometer Suite on the National Aeronautics and Space Administration

(NASA)/NOAA Suomi National Polar-orbiting Partnership satellite, a composite of

several satellite passes. C, NASA Aqua satellite image of Hurricane Sandy,

October 29, 2012, 2:20 p.m. EDT ..................................................................................................4

2. Map of study region between Maine and Virginia (inclusive) indicating 

10 subregions and the general locations of surface elevation table-marker horizon

station clusters..............................................................................................................................6

3. Preferred Reporting Items for Systemic Reviews and Meta-Analyses flow diagram

detailing the omission of surface elevation table-marker horizon records from the

inventory and the Hurricane Sandy effects analysis..............................................................9

4. Schematic diagram of initial structural equation model illustrating the hypothetical

pathways between predictor variables and response variables .......................................11

5. Graph showing mean surface elevation change from July 2005 to September 2013

at the U.S. Geological Survey Blackwater 7D.1 surface elevation table (Cambridge,

Md)................................................................................................................................................12

6. Graph showing frequency distribution of number of days between Hurricane Sandy

(October 30, 2012) and the poststorm surface elevation table measurement for

each eligible station ...................................................................................................................12

7. Graphs showing bivariate relations between predictor variables in the eligible total

surface elevation dataset..........................................................................................................17

8. Maps of study region showing storm track, wind swaths, and stations with eligible

surface elevation table data in each category: A, position relative to landfall, B,

geomorphic setting, and C, storm surge.................................................................................18

9. Graph of model prediction versus response for the best deviation from expected 

surface elevation model (15e) ..................................................................................................21

10. Graph of poststorm deviation from expected surface elevation change along the

distance to storm landfall gradient .........................................................................................21
viii

11. Graphs showing frequency distribution of A, poststorm residual distance from

expected and B, prestorm mean residual distance using all eligible surface

elevation table data....................................................................................................................22

12. Graphs showing frequency distribution of poststorm residual distance from

expected for eligible surface elevation table stations to the A, left and B, right of

landfall ..........................................................................................................................................23

13. Graph showing storm surge presence or absence along the distance from landfall

gradient ........................................................................................................................................25

14. Graphs showing frequency distribution of poststorm residual distance from

expected for eligible surface elevation table stations with storm surge A, present

and B, absent...............................................................................................................................26

15. Schematic diagram of revised surface elevation model .....................................................27

16. Map of study region between Maine and Virginia (inclusive) indicating area of

estuarine emergent marsh per hexagon (40 square kilometers or 4,000 hectares)........30

17. Maps of study region between Maine and Virginia (inclusive) indicating A, number

of surface elevation table-marker horizon (SET-MH) stations per hexagon 

(40 square kilometers or 4,000 hectares [ha]), and B, number of SETs per 

1,000 ha estuarine emergent marsh in each hexagon..........................................................32

18. Map of dominant broad geomorphic setting of marsh patches (estuarine emergent

marsh) in each hexagon (40 square kilometers) across the study region (Virginia to

Maine, inclusive).........................................................................................................................35

19. Maps showing percent of estuarine emergent marsh patch area by broad

geomorphic settings in each hexagon (40 square kilometers) across several

subregions with mixed geomorphic settings (Long Island, southern New England,

and Cape Cod/Casco Bay), with A, percent estuarine marsh, and B, percent

back-barrier lagoon....................................................................................................................36

20. Maps of study region between Maine and Virginia (inclusive) indicating A, the

number of surface elevation table-marker horizon (SET-MH) stations owned by

Federal agencies per hexagon (40 square kilometers), 664 SETs in 107 hexagons;

and B, hexagons with publicly owned marsh (by states, National Park Service, or

U.S. Fish and Wildlife Service) .................................................................................................37

21. Map showing hurricane return period (based on National Hurricane Center

hurricane strike dataset from 1900–2009 for U.S. coastal counties) for the study

region (Virginia to Maine, inclusive) with hexagon (40 square kilometers) sampling

grid and hexagons with surface elevation table-marker horizon stations indicated......38

22. Map showing predicted worst-case scenario storm surge footprints by hurricane

storm strength, from the Federal Emergency Management Agency Coastal Flood

Loss Atlas SLOSH (Sea, Lake, and Overland Surges from Hurricanes) model

maximum of maximums for the study region (Virginia to Maine, inclusive) with

hexagon (40 square kilometers) sampling grid and hexagons with surface elevation

table-marker horizon stations indicated.................................................................................39

23. Map showing northern portion of study area predicted worst-case scenario

storm surge footprints by hurricane storm strength, from the Federal Emergency

Management Agency Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland

Surges from Hurricanes) model maximum of maximums for Cape Cod/Casco Bay

and coastal Maine subregions with hexagon (40 square kilometers) sampling grid

and hexagons with surface elevation table-marker horizon stations indicated..............40
ix

24. Map showing central portion of study area predicted worst-case scenario 

storm surge footprints by hurricane storm strength, from the Federal Emergency 

Management Agency Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland 

Surges from Hurricanes) model maximum of maximums for Cape Cod/Casco Bay, 

southern New England, Long Island, and part of coastal New Jersey subregions 

with hexagon (40 square kilometers) sampling grid and hexagons with surface 

elevation table-marker horizon stations indicated ...............................................................41

25. Map showing southern portion of study area predicted worst-case scenario

storm surge footprints by hurricane storm strength, from the Federal Emergency

Management Agency Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland

Surges from Hurricanes) model maximum of maximums for coastal Virginia,

eastern and western Chesapeake Bay, coastal Delmarva, Delaware Bay, and

coastal New Jersey subregions with hexagon (40 square kilometers) sampling grid

and hexagons with surface elevation table-marker horizon stations indicated..............42

26. Map showing coastal Maine subregion predicted worst-case scenario storm surge

footprints by hurricane storm strength, from the Federal Emergency Management

Agency Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges from

Hurricanes) model maximum of maximums with hexagon (40 square kilometers)

sampling grid and hexagons with surface elevation table-marker horizon stations

indicated.......................................................................................................................................43

27. Map showing Cape Cod/Casco Bay subregion (and neighboring areas) predicted

worst-case scenario storm surge footprints by hurricane storm strength, from the

Federal Emergency Management Agency Coastal Flood Loss Atlas SLOSH (Sea,

Lake, and Overland Surges from Hurricanes) model maximum of maximums with

hexagon (40 square kilometers) sampling grid and hexagons with surface elevation

table-marker horizon stations indicated.................................................................................44

28. Map showing southern New England subregion (and neighboring areas) predicted

worst-case scenario storm surge footprints by hurricane storm strength, from the

Federal Emergency Management Agency Coastal Flood Loss Atlas SLOSH (Sea,

Lake, and Overland Surges from Hurricanes) model maximum of maximums with

hexagon (40 square kilometers) sampling grid and hexagons with surface elevation

table-marker horizon stations indicated.................................................................................45

29. Map showing Long Island subregion (and neighboring areas) predicted worst-case

scenario storm surge footprints by hurricane storm strength, from the Federal

Emergency Management Agency Coastal Flood Loss Atlas SLOSH (Sea, Lake, and

Overland Surges from Hurricanes) model maximum of maximums with hexagon 

(40 square kilometers) sampling grid and hexagons with surface elevation

table-marker horizon stations indicated.................................................................................46

30. Map showing coastal New Jersey subregion (and neighboring areas) predicted

worst-case scenario storm surge footprints by hurricane storm strength, from the

Federal Emergency Management Agency Coastal Flood Loss Atlas SLOSH (Sea,

Lake, and Overland Surges from Hurricanes) model maximum of maximums with

hexagon (40 square kilometers) sampling grid and hexagons with surface elevation

table-marker horizon stations indicated.................................................................................47

31. Map showing Delaware Bay subregion (and neighboring areas) predicted

worst-case scenario storm surge footprints by hurricane storm strength, from the

Federal Emergency Management Agency Coastal Flood Loss Atlas SLOSH (Sea,

Lake, and Overland Surges from Hurricanes) model maximum of maximums with

hexagon (40 square kilometers) sampling grid and hexagons with surface elevation

table-marker horizon stations indicated.................................................................................48
x

32. Map showing coastal Virginia and eastern/western Chesapeake Bay subregions 

(and neighboring areas) predicted worst-case scenario storm surge footprints by 

hurricane storm strength, from the Federal Emergency Management Agency Coastal 

Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges from Hurricanes) model 

maximum of maximums with hexagon (40 square kilometers) sampling grid and 

hexagons with surface elevation table-marker horizon stations indicated .....................49

Tables

1. Geomorphic settings of coastal wetlands in the mid-Atlantic coast of the 

United States .................................................................................................................................7

2. Subregion names and boundaries.............................................................................................7

3. Five hypothetical examples of surface elevation table survey times and 

exclusion of data from analyses based on season of prestorm and poststorm 

measurements.............................................................................................................................11

4. Number of surface elevation table stations used in analyses and distance to storm

landfall (minimum, maximum, and range) for each unique geomorphic and

geographic location category ..................................................................................................13

5. Models used to determine deviation from expected surface elevation change,

measured as the residual distance of poststorm elevation change..................................15

6. Storm surge submodels.............................................................................................................16

7. Results from variance inflation factor analysis assessing the colinearity between

predictor variables in the deviation from expected surface elevation model and the

storm surge submodel ...............................................................................................................16

8. Comparing distance from storm landfall curves (linear and quadratic) in the

deviation from expected surface elevation model and storm surge submodel using

Akaike’s Information Criterion, AICc .......................................................................................19

9. Deviation from expected surface elevation change models ranked by corrected

Akaike’s Information Criteria (AICc) ........................................................................................20

10. Effective sample sizes for all top models................................................................................21

11. Summary information for stations with a deviation from expected elevation change

greater than ±5 millimeters .......................................................................................................24

12. Storm surge models ranked by corrected Akaike’s Information Criteria (AICc)..............24

13. Summary of the spatial distribution of surface elevation table-marker horizon

(SET-MH) stations, hexagons (with estuarine emergent marsh [E2EM]), hexagons

(with E2EM marsh) with SET-MH stations, mean minimum distance between

hexagons with SETs, and Global Moran’s I (measure of clustering) across 10

subregions between Maine and Virginia (inclusive) ............................................................31

14. Summary of the spatial distribution of estuarine emergent marsh patches and

surface elevation table-marker horizon stations within marsh patches among 10

subregions between Maine and Virginia (inclusive) ............................................................33

15. Summary of the spatial distribution of surface elevation table-marker horizon

stations, estuarine emergent marsh patches, and geomorphic settings among 10

subregions between Maine and Virginia (inclusive) ............................................................34
xi

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

yard (yd) 0.9144 meter (m)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2)

acre 0.004047 square kilometer (km2)

square foot (ft2) 929.0 square centimeter (cm2)

square foot (ft2) 0.09290 square meter (m2)

square inch (in2) 6.452 square centimeter (cm2)

section (640 acres or 

1 square mile)

259.0 square hectometer (hm2)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2)

Flow rate

foot per second (ft/s) 0.3048 meter per second (m/s)

foot per minute (ft/min) 0.3048 meter per minute (m/min)

foot per hour (ft/h) 0.3048 meter per hour (m/h) 

foot per day (ft/d) 0.3048 meter per day (m/d)

foot per year (ft/yr) 0.3048 meter per year (m/yr)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

cubic foot per second 

per square mile 

([ft3/s]/mi2)

0.01093 cubic meter per second 

per square kilometer 

([m3/s]/km2)

cubic foot per day (ft3/d) 0.02832 cubic meter per day (m3/d)

inch per hour (in/h) 0.0254 meter per hour (m/h)

inch per year (in/yr) 25.4 millimeter per year (mm/yr)

mile per hour (mi/h) 1.609 kilometer per hour (km/h) 

knot (1 nautical mi/h) 1.151 mile per hour (mi/h)

Pressure

atmosphere, standard (atm) 101.3 kilopascal (kPa)

bar 100 kilopascal (kPa)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F = (1.8 × °C) + 32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C = (°F − 32) / 1.8.
xii

Abbreviations

AIC Akaike’s Information Criterion

FEMA Federal Emergency Management Agency

NOAA National Oceanic and Atmospheric Administration

NWI National Wetlands Inventory

NWR National Wildlife Refuge

SET-MH surface elevation table-marker horizon

USGS U.S. Geological Survey
Hurricane Sandy Impacts on Coastal Wetland Resilience

By Donald R. Cahoon1, Jennifer H. Olker2, Alice G. Yeates2, Glenn R. Guntenspergen1, James B. Grace1, Susan 

C. Adamowicz3, Shimon Anisfeld4, Andrew H. Baldwin5, Nels Barrett6, Leah Beckett5, Alice Benzecry7, Linda 

K. Blum8, David M. Burdick9, William Crouch10, Marci Cole Ekberg11, Sarah Fernald12, Kristin Wilson Grimes13, 

Joseph Grzyb14, Ellen Kracauer Hartig15, Danielle A. Kreeger16, Marit Larson15, Scott Lerberg17, James C. 

Lynch18, Nicole Maher19, Martha Maxwell-Doyle20, Laura R. Mitchell21, Jordan Mora22, Victoria O’Neill23, 

Angela Padeletti16, Diann Prosser1, Tracy Quirk24, Kenneth B. Raposa25, William G. Reay17, Drexel Siok26, 

Christopher Snow27, Adam Starke19, Lorie Staver28, J. Court Stevenson28, and Vincent Turner29

Abstract

The goal of this research was to evaluate the impacts 

of Hurricane Sandy on surface elevation trends in estuarine 

marshes located across the northeast region of the United 

States from Virginia to Maine using data from an opportunistic 

(in other words, not strategic) and collaborative network (from 

here on, an opportunistic network) of surface elevation tablemarker horizon (SET-MH) stations. First, we built a database of metadata for 965 individual stations from 96 unique 

geographical locations that included the location, geomorphic 

setting, and wetland type for each SET-MH station. The 

dominant estuarine settings included in the analyses were 

back-barrier lagoonal marshes and emergent marshes along 

embayments and tidal tributaries. We then calculated prestorm 

elevation trends to compare to poststorm elevation measurements to determine the storm impact on each station trend. We 

hypothesized that the effect of Hurricane Sandy on marsh elevation trends would differ by position relative to landfall (right 

or left) and distance from landfall in southern New Jersey, as 

both of these variables influence the presence or absence of 

storm surge as a result of the physical characteristics of tropical cyclones (in other words, strongest winds typically occur 

to the right of landfall). Storm surge was spatially less extensive and less deep (~1 meter [m]) in marshes located to the 

left (in other words, south) of landfall compared to marshes 

1

U.S. Geological Survey.

2

University of Minnesota, Duluth, Minn.

3

U.S. Fish & Wildlife Service, Rachel Carson National Wildlife Refuge, 

Wells, Maine.

4

Yale University, School of Forestry & Environmental Studies, New Haven, 

Conn.

5

University of Maryland, College Park, Md.

6

Natural Resources Conservation Service, Amherst, Mass.

7

Fairleigh Dickinson University, Teaneck, N.J.

8

University of Virginia, Charlottesville, Va.

9

Jackson Estuarine Laboratory, University of New Hampshire, Durham, 

N.H.

10U.S. Fish and Wildlife Service, Eastern Virginia Rivers National Wildlife 

Refuge Complex, Warsaw, Va.

11Save the Bay, Narragansett, R.I.

12New York State, Department of Environmental Conservation, Hudson 

River National Estuarine Research Reserve, Staatsburg, N.Y.

13Wells National Estuarine Research Reserve, Wells, Maine; Center for 

Marine and Environmental Studies, University of the Virgin Islands, St. 

Thomas, V.I.

14Meadowlands Environmental Research Institute, Lyndhurst, N.J.

15New York City Department of Parks & Recreation, New York, N.Y.

16Partnership for the Delaware Estuary, Wilmington, Del.

17Chesapeake Bay National Estuarine Research Reserve, Gloucester Point, 

Va.

18National Park Service, Northeast Coastal and Barrier Network, Washington, D.C.

19 The Nature Conservancy, Cold Spring Harbor, N.Y.

20Barnegat Bay Partnership, Toms River, N.J.

21U.S. Fish and Wildlife Service Northeast Region, Bombay Hook National 

Wildlife Refuge, Smyrna, Del.

22Waquoit Bay National Estuarine Research Reserve, Waquoit, Mass.

23New England and Interstate Water Pollution Control Commission, New 

York State Department of Environmental Conservation, Long Island Sound 

Study, East Setauket, N.Y.

24Academy of Natural Sciences of Drexel University, Philadelphia, Pa.

25Narragansett Bay National Estuarine Research Reserve, Prudence Island, 

R.I.

26Delaware Department of Natural Resources and Environmental Control, 

Delaware Coastal Programs, Dover, Del.

27Chesapeake Bay National Estuarine Research Reserve in Maryland, Maryland Department of Natural Resources, Annapolis, Md.

28University of Maryland Center for Environmental Science, Horn Point 

Laboratory, Cambridge, Md.

29Edwin B. Forsythe National Wildlife Refuge, Oceanville, N.J.
2 Hurricane Sandy Impacts on Coastal Wetland Resilience

located to the right (in other words, north) of landfall where 

storm surge covered a larger area and was deeper (3–4 m). 

About 63 percent of 223 eligible stations had a poststorm 

trend that was similar to the prestorm trend (in other words, 

less than ±5 millimeters [mm]), indicating little storm impact 

on elevation trends at those sites. The remaining 37 percent 

of stations exhibited significant poststorm deviations from 

the prestorm trend (in other words, greater than ±5 mm). Of 

these, stations located to the left of landfall had a significant 

and greater deviation in their elevation trend, and the deviation 

was more likely to be positive (elevation gain) compared to 

marshes located to the right of landfall, which had a significant deviation in their elevation trend that was more likely to 

be negative (elevation loss). This finding is directly related 

to storm surge impacts on marsh sediment deposition, where 

deep storm surge (3–4 m) results in sediment deposition in 

habitats inland of coastal marshes but less so in the marshes 

themselves. Substrate compaction by the storm surge overburden may have contributed to elevation loss, but this was 

not measured because sufficient marker horizon data were not 

available for analysis. In contrast, to the left of landfall the 

wind-driven flooding of sediment laden water pushed into the 

headwaters of rivers and small bays with an ~1 m surge, and 

resulted in more prevalent sediment deposition on the marsh 

surfaces and elevation gain. In general, the findings support 

previous research showing that the physical characteristics 

of the storm (for example, wind speed, storm surge height, 

impact angle of landfall) combined with the local wetland conditions (for example, marsh productivity, groundwater level, 

tide height) are important factors determining a storm’s impact 

on soil elevation, and that the soil elevation response can vary 

widely among multiple wetland sites impacted by the same 

storm and among different storms for the same wetland site. 

The final objective of this project was to create a framework using metadata from the opportunistic network of SETMH stations that could be used to develop a strategic monitoring network designed to address specific climate change 

impacts and related phenomena identified by land managers 

and stakeholders. We evaluated the spatial distribution and 

density of SET-MH stations in relation to geographic coverage, marsh setting, availability of public land, and historical 

storm surge footprints and hurricane return intervals in order 

to identify gaps in our understanding of risk and our ability 

to assess it. Analyses revealed that the general geographic 

coverage of SET-MH stations is limited given the low percentage of marsh patches with stations, low density of stations, 

the clumped distribution of stations, and the often limited and 

uneven distribution of stations in wetlands with a high historical frequency of hurricane strikes and storm surge impacts. 

These findings can be used by managers and planners to 

inform the creation of a strategic monitoring network that can, 

in turn, inform management and adaptation plans for coastal 

resources in the region. Final plan designs will need to consider financial and infrastructural support required for station 

maintenance, as well as data collection and management over 

the long term.

Introduction

On October 29, 2012, Hurricane Sandy made landfall 

as a large (1,611 kilometers [km] diameter) post-tropical 

cyclone near Brigantine, New Jersey, with maximum sustained 

winds of 130 kilometers per hour (km/h) (70 knots [kn]) and 

minimum pressure of 94.5 kilopascals (kPa) (945 millibars 

[mb]; Blake and others, 2013). The storm affected, in varying 

degrees, the entire Atlantic seaboard of the United States from 

Florida to Maine (Blake and others, 2013; Valle-Levinson 

and others, 2013). Understanding the ecological and physical 

impacts of hurricanes on coastal wetlands and their interaction 

with local conditions is important for identifying resilience of 

these marsh communities. In light of the projected increase 

in the frequency of intense storms and in storm intensity 

(Knutson and others, 2010; Bender and others, 2010; Peduzzi 

and others, 2012; Emanuel, 2013; Horton and others, 2011, 

2014), the physical (for example, storm surge, sediment deposition) and chemical (for example, salinity, pollutants) impacts 

associated with hurricanes need to be understood to efficiently 

and effectively protect and restore these critical habitats. Some 

of the potential long-term impacts of low-frequency, highmagnitude storm events such as Hurricane Sandy on marsh 

surface elevation include sediment deposition and erosion, 

storm surge-related soil compaction, and altered community 

dynamics, which includes mortality of existing vegetation or 

promotion of growth through increased availability of nutrients from newly deposited sediment (Cahoon and others, 

1995a; Cahoon, 2006). Death of wetland vegetation can lead 

to loss of elevation by increased root zone decomposition and 

erosion, whereas increased root growth can lead to elevation 

gain by root zone expansion (Cahoon and others, 2003). The 

goal of this study was to evaluate Hurricane Sandy’s shortterm impacts on marsh surface elevations within 1 year after 

the storm. 

To assess the impacts of Hurricane Sandy on marsh 

surface elevation dynamics, we evaluated elevation and accretion data collected with the surface elevation table-marker 

horizon (SET-MH) method (Cahoon and others, 1995a) 

throughout marshes of the northeastern region of the United 

States both before and after the storm. The SET-MH method 

directly measures both surface elevation change (SET) and 

vertical accretion (MH). These two measurements can be 

used to calculate subsurface process influences on elevation 

change, namely shallow subsidence or shallow expansion (for 

example, root zone expansion from enhanced root growth; 

Cahoon and others, 1995b, 2002a,b; Callaway and others, 

2013). A more detailed description of the SET device and the 

marker horizon method, including photographs and a diagram, 

is provided in appendix 1. Previous research using the SETMH method has shown that hurricanes are powerful agents of 

geomorphic change (Cahoon, 2006), resulting in both positive 

and negative changes in elevation trajectories through impacts 

on both the surface and subsurface soil processes controlling 

marsh surface elevation. The physical characteristics of the 

storm (for example, wind speed, storm surge height, impact 
Inventory and Distribution of SET-MH Stations Along the Atlantic Coast 3

angle of landfall) combined with the local wetland conditions 

(for example, marsh productivity, groundwater level, elevation 

relative to the tide, tide height) are important factors determining a storm’s impact on marsh soil elevation. In addition, 

the soil elevation response can vary widely among multiple 

wetland sites impacted by the same storm and among different 

storms for the same wetland site (Cahoon, 2006). Thus, findings should not be extrapolated from one wetland to another 

for any given storm, or from one storm to another for any 

given wetland. However, using a large number of SET-MH 

stations across a large geographic area that spans a variety of 

wetland settings, as well as storm exposures, and intensities 

can improve our understanding of wetland vulnerability to 

severe storm effects on marsh surface elevation change.

Study Area and SET-MH Stations

The study area includes estuarine tidal wetlands along 

the northeastern coast of the United States from Virginia to 

Maine, an area that spans the track of the storm as it turned 

north towards the U.S. coast (fig. 1) and includes the areas of 

greatest storm surge impacts. High-resolution wetland surface 

elevation change and accretion data were collected from Virginia to Maine (fig. 2), both before and after the storm, using 

the SET-MH method. These SET-MH stations were installed 

during the past two decades independently by the U.S. Geological Survey (USGS), a number of other Federal and nonFederal agencies, nongovernmental organizations (NGOs), 

and academic institutions to investigate or monitor elevation 

dynamics in coastal wetlands. The SET-MH method originally 

consisted of an SET device attached to a pipe benchmark 

driven 3–6 meters (m) into the substrate (appendix 1, fig. 1.1; 

Cahoon and others, 2002a) and typically was used to address 

hypothesis-driven research questions. Later, the Rod SET with 

deep and shallow benchmarks (10–25 m and <1 m, respectively) was developed to provide greater flexibility in addressing research questions (appendix 1, fig. 1.1; Cahoon and 

others, 2002b). Although the SET-MH method continues to be 

used to address research questions, over time it has been used 

increasingly to monitor long-term elevation change relative to 

local sea-level trends, especially in National parks and wildlife 

refuges. Overall, 60 percent of SET stations in the northeastregion inventory were located on Federal lands. Hence, SET 

stations are located in wetlands best suited to address specific 

research questions or monitor the habitat sustainability at a 

specific wetland. Thus, the collection of stations represents 

an opportunistic regional network, not a strategically planned 

regional network, to assess storm impacts. Nevertheless, data 

from this opportunistic network enabled large spatial-scale 

assessments of storm impacts and wetland responses along a 

gradient of impact intensity by quantifying the overall change 

in marsh surface elevation. 

Objectives

The objectives of this project were to

1. Build a database of metadata for SET-MH stations in 

the coastal wetlands of the northeastern United States, 

including location, geomorphic setting, and wetland 

type;

2. Analyze elevation and accretion data and related 

environmental data collected from within the path of 

Hurricane Sandy to assess coastal wetland responses to 

this storm;

3. Use assessments of coastal wetland responses to estimate 

the impact of Hurricane Sandy on marsh sustainability 

and the potential impact of similar future storms; and

4. Use the database to develop a framework that could support the development of a strategic monitoring network 

of SET-MH stations in the northeastern United States to 

assess impacts of storms on coastal wetlands.

Inventory and Distribution of SET-MH 

Stations Along the Atlantic Coast

The initial step in this project was to collate known surface elevation table-marker horizon (SET-MH) stations in the 

northeastern United States by contacting and requesting information from organizations and scientists working in the area. 

Important activities included (1) contacting all investigators 

to collect poststorm elevation (SET) and accretion (MH) data, 

which were gathered in marshes throughout the northeastern 

region in the weeks and months immediately following the 

storm; and (2) developing a preliminary spreadsheet to collect 

metadata (for example, location, setting, wetland type, and so 

forth) and sending it to each network investigator to fill out. 

In the first months of this project, the SET-MH metadata 

spreadsheet developed immediately following the storm was 

updated to match a similar SET-MH spreadsheet developed 

by the National Oceanic and Atmospheric Administration 

(NOAA) for its Sentinel Site Cooperatives and the North- and 

South Atlantic Landscape Conservation Cooperatives. In this 

way, SET-MH metadata will be available in the same format 

for the entire east coast of the United States, parts of the U.S. 

gulf coast, and the five pilot sites in NOAA’s Sentinel Site 

Cooperative to assist in development of plans for a strategic 

SET-MH network for these parts of the country. The updated 

spreadsheet was distributed to SET colleagues in the northeastern United States. Significant efforts were made to ensure 

that all known SET practitioners and SET-MH stations were 

included in the requests for information. These data were collated into an inventory of SET-MH stations along the Atlantic 

coast from Virginia to Maine inclusive (objective 1). Additionally, metadata were submitted for several stations from NOAA 
NORTH ATLANTIC

OCEAN

GULF

OF

MEXICO

CARIBBEAN SEA

MEXICO

BELIZE

HONDURAS

NICARAGUA

CUBA

JAMAICA

THE BAHAMAS

HAITI

DOMINICAN

REPUBLIC

PUERTO RICO

LESSER

ANTILLES

UNITED

STATES

Oct. 31, 2012

Oct. 22, 2012

44025

44065

41001

90° 80° 70° 60°

40°30°20°

Status, MaxWind, Record

Tropical stormHurricane—Catagory 1Hurricane—Catagory 2Hurricane—Catagory 3Post-tropicalNOAA NDBC buoy

EXPLANATION

Map image is the intellectual property of Esri and is used herein under license. Copyright © 2019 Esri and its licensors. All rights reserved.Storm track: NOAA, AOML HRD 0 250

500

500

1,000

MILES

0 KILOMETERS

A

Figure 1. A, Hurricane Sandy track and intensity, as well as locations of moored National Oceanic and Atmospheric Administration (NOAA) Nationabuoys recording wave height and period (adapted from Sopkin and others, 2014). B, Nighttime image of Hurricane Sandy captured 16–18 hours before Infrared Imaging Radiometer Suite (VIIRS) on the National Aeronautics and Space Administration (NASA)/NOAA Suomi National Polar-orbiting Partneof several satellite passes (image provided by University of Wisconsin-Madison). C, NASA Aqua satellite image of Hurricane Sandy, October 29, 2012, both images accessed at https://www.nasa.gov/mission_pages/hurricanes/archives/2012/h2012_Sandy.html#11).
B

C

Figure 1. A, Hurricane Sandy track and intensity, as well as locations of moored National Oceanic and Atmospheric Administration (NOAA) Nationabuoys recording wave height and period (adapted from Sopkin and others, 2014). B, Nighttime image of Hurricane Sandy captured 16–18 hours before Infrared Imaging Radiometer Suite (VIIRS) on the National Aeronautics and Space Administration (NASA)/NOAA Suomi National Polar-orbiting Partneof several satellite passes (image provided by University of Wisconsin-Madison). C, NASA Aqua satellite image of Hurricane Sandy, October 29, 2012, both images accessed at https://www.nasa.gov/mission_pages/hurricanes/archives/2012/h2012_Sandy.html#11).—Continued
6 Hurricane Sandy Impacts on Coastal Wetland Resilience

75° 70°

45°

40°

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ATLANTIC OCEAN

ME

NH

VT

MA

RI CT

NY

NJ PA

DE

MD

VA

NC

WV

DC

General SET locations

Subregion

Coastal Maine

CapeCod/CascoBay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

EXPLANATION

Map image is the intellectual property of Esri and is used herein under license. 

Copyright © 2019 Esri and its licensors. All rights reserved.

0 90 180 MILES

0 150 300 KILOMETERS

Figure 2. Study region between Maine and Virginia (inclusive) indicating 10 subregions and the general locations of surface elevation 

table-marker horizon (SET-MH) station clusters (965 stations in total).

sites in North Carolina and USGS sites in Canada that are outside the prescribed study area and were subsequently removed 

from the inventory.

Data Formatting and Analyses

All metadata received were subjected to a quality control/

quality assurance process. These practices included contacting 

SET practitioners with follow-up questions and identification 

of potential errors in datasets (for example, incorrect coordinates, outliers in data, labelling errors, to name only a few). 

Once formatted, SET-MH stations were identified as appropriate for inclusion in the inventory (objective 1). The Preferred 

Reporting Items for Systematic Reviews and Meta-Analyses 

(PRISMA) approach (Moher and others, 2009) was used for 

identifying, screening, and determining eligibility of sites 

based on the following criteria:

1. Within study area for monitoring network (Virginia to 

Maine),

2. The original pipe SET or deep rod SET method was used 

(shallow SET benchmark method was excluded),

3. Estuarine emergent marsh habitats (freshwater tidal 

marshes, forested, and highly managed sites excluded), 

and

4. SET-MH station was functional (not damaged).

An explanation of the criteria and the exclusions are 

provided below.
Location and Distribution of Stations 7

Location and Distribution of Stations

For all SET-MH stations included in the inventory, we 

verified geographic location and assessed geomorphic setting with high resolution aerial photography following the 

broad setting and subsetting classification scheme in Cahoon 

and others (2009). See table 1 for more details. Furthermore, 

the study area between Maine and Virginia (inclusive) was 

partitioned into ten subregions (fig. 2): (1) coastal Maine, 

(2) Cape Cod and Casco Bay, (3) southern New England, 

(4) Long Island, (5) coastal New Jersey, (6) Delaware Bay, 

(7) Coastal Delmarva, (8) eastern Chesapeake Bay, (9) western 

Chesapeake Bay, and (10) coastal Virginia. These subregions 

were based on major tidal systems as defined in Conway 

and Droege (2006). The boundaries of the subregions are 

described in table 2. A hexagon sampling grid (40 square kilometers [km2

]) was used to partition the subregions into smaller 

units, to aid assessment, and to graphically represent marsh 

and SET-MH information at a scale appropriate for the large 

study area (Weist and others, 2016). This tessellated hexagon 

sampling design (Stevens and Olsen, 2004) can be used for 

comparison across subregions with uniform-sized sample units 

(fig. 2). 

A preliminary evaluation of the database revealed a 

majority of stations occurred in estuarine emergent marsh settings. Thus, hexagons were limited to locations that contained 

the estuarine emergent marsh setting identified using National 

Wetlands Inventory (NWI) estuarine emergent marsh data 

(NWI code E2EM) acquired in 2010 from the U.S. Fish and 

Wildlife Service (http://www.fws.gov/Wetlands/NWI/). NWI 

emergent marsh polygons were assigned unique marsh patch 

identification, and adjacent polygons within a 50-m buffer 

were considered the same patch (Wiest and others, 2016) and 

given a single identification. We assigned the estuarine emergent marsh identified by NWI to one of two possible geomorphic settings: estuarine marsh or back-barrier lagoonal marsh 

(Cahoon and others, 2009). For each marsh patch, marsh area 

(in hectares [ha]) was calculated (ArcMap 10.1) and the primary broad geomorphic setting assigned using high resolution 

aerial photography. When a patch included two or more broad 

geomorphic settings, the dominant broad setting was used. 

Table 1. Geomorphic settings of coastal wetlands in the 

mid-Atlantic coast of the United States (Cahoon and others, 2009).

Geomorphic setting Description

Open coast Areas sheltered from waves and 

currents as a result of coastal 

topography or bathymetry

Back-barrier lagoon marsh Occupies fill within transgressive 

back-barrier lagoons 

Back-barrier: lagoonal side of a 

marine barrier

Lagoonal fill: occupies fill in a backbarrier lagoon

Transgressive marsh: transgressive 

marshes bordering uplands in a 

back-barrier lagoon

Estuarine embayment Shallow coastal embayment with 

some river discharge, frequently a 

drowned river valley

Saline fringe marsh: transgressive 

marshes bordering uplands at the 

lower end of estuaries

Stream channel wetlands: occupy 

estuarine-alluvial channels rather 

than open coast

Estuarine brackish marshes Located in vicinity of turbidity 

maxima zone

Meander: expansive marsh with 

meandering channels

Fringing: transgressive marshes 

bordering uplands

Island: island within estuarine channel

Tidal fresh marsh Located above turbidity maxima 

zone; developed in drowned river 

valley as it filled with sediment

Non-tidal brackish marsh Transgressive marshes bordering 

uplands in estuaries with restricted 

tidal signal

Table 2. Subregion names and boundaries (see fig. 2 for map).

Subregion Boundaries

Coastal Maine Lubec, Maine, to north of Casco Bay, 

Maine

Cape Cod, Casco Bay Casco Bay, Maine, to Cape Cod, Massachusetts—including north side of 

U.S. Route 6 Mid-Cape Highway

Southern New England South of Cape Cod, Massachusetts—

including south side of U.S. Route 6 

Mid-Cape Highway, Nantucket 

Island, Martha’s Vineyard Island to 

Hudson River, New York, including 

Bronx, New York

Long Island Long Island, New York, including 

Queens, New York

Coastal New Jersey New Jersey Meadowlands to Cape 

May, New Jersey (oceanside), 

including Staten Island, New York

Delaware Bay Cape May, New Jersey (bayside), to 

Lewes, Delaware (bayside)

Coastal Delmarva Delmarva Peninsula oceanside from 

Lewes, Delaware, to Fisherman’s 

Island National Wildlife Refuge, 

Virginia

Eastern Chesapeake Bay Chesapeake Bay coastline east of 

Susquehanna River mouth

Western Chesapeake Bay Chesapeake Bay coastline west of 

Susquehanna River mouth

Coastal Virginia Virginia Beach, Virginia, oceanside to 

North Carolina border
8 Hurricane Sandy Impacts on Coastal Wetland Resilience

Metadata Summary

Metadata were received for 1,230 SET-MH stations. 

These metadata were collected from colleagues across 

10 states (from Virginia to Maine) from NOAA National 

Estuarine Research Reserves; U.S. Fish and Wildlife Service national wildlife refuges; National Park Service parks, 

seashores, and recreation areas; State Wildlife Management 

Areas; National Science Foundation Long Term Ecological Research Network sites; the Long Island Sound Study; 

Partnership for the Delaware Estuary/Barnegat Bay Partnership-Mid-Atlantic Coastal Wetlands Assessment; the New 

York City Department of Parks and Recreation; The Nature 

Conservancy; Save the Bay-Narragansett Bay; and private 

and academic organizations. This SET-MH inventory (appendix 2) resides at the University of Minnesota Duluth. Of the 

1,230 SET-MH records, 85 were duplicates, and 180 did not 

meet the criteria described above and were removed from 

the inventory (fig. 3). Shallow SET stations were excluded 

because they were not commonly used in the region and not 

well represented in the dataset, limiting their value for testing 

regional hypotheses. But more importantly, they measure 

elevation change relative only to the depth of the root zone. In 

contrast, both the pipe SET and the Rod SET were used commonly throughout the region. They measure elevation change 

to a depth of several tens of meters, thereby measuring both 

root zone and deeper compaction processes in the substrate. 

Excluding shallow SET stations reduced confounding effects 

related to their methodological difference in elevation measurements and their limited spatial coverage. Freshwater tidal 

marsh settings were excluded because they contained only 

30 stations within four geographical locations and all the 

locations were skewed geographically to the left of Hurricane 

Sandy landfall. Forested wetland settings were less represented with SET-MH stations than tidal freshwater marsh. 

Thus, data from these two habitats were not well suited for 

testing regional hypotheses of storm impacts. SET-MH records 

were excluded if they were established for experiments: fertilization, exclusion fences, burn, restoration, saltwater addition, elevated carbon dioxide, marsh plugging, and vegetation 

removal treatments. The inventory of SET-MH stations used 

in this study presently includes 965 individual stations (fig. 3) 

in 96 unique geographical locations, based on general area 

descriptions provided by SET practitioners. 

Hurricane Sandy Effects on Coastal 

Marsh Elevation Change

Introduction

The next step in the project was to evaluate the impact 

of Hurricane Sandy on the elevation trajectories of coastal 

marshes located across the northeast United States within the 

area of storm influence (for example, wind field and storm 

surge). This analysis requires an understanding of both the 

physical characteristics of the storm and the nature of coastal 

landforms in the northeast United States it impacted. Some 

fundamental physical characteristics of tropical cyclones in the 

northern hemisphere include elevated wind speeds that push 

and pile up seawater as the storm advances over the ocean and 

counterclockwise winds. The latter characteristic means that a 

storm’s physical impacts are typically greater in the northeast 

quadrant (in other words, the upper right quadrant relative 

to storm direction) caused by winds blowing onshore when 

the storm makes landfall. In contrast, winds in the northwest 

quadrant are blowing offshore at the time of landfall. Yet, 

every storm is unique in terms of its wind speed, size (storm 

diameter), rate of forward motion, amount of rainfall, timing 

of landfall relative to tide height, angle of approach to the 

shore, and the local nearshore bathymetry and coastal geomorphology at the point of landfall (Resio and Westerink, 2008). 

This unique set of physical characteristics determines the 

intensity and duration of a storm’s impact on coastal landforms it encounters. 

Physical Characteristics of the Storm

On October 28, 2012, Hurricane Sandy travelled north 

on a track parallel to the Atlantic coast of the United States, 

with the strongest winds on its western side (fig. 1B; and see 

fig. 7 in Blake and others, 2013). When the hurricane reached 

the mid-Atlantic region (National Aeronautics and Space 

Administration, 2013; fig. 1A,B) it combined with a cold front 

moving from the northwest. The storm turned to the northwest 

and made landfall on October 29, 2012, as a post-tropical 

cyclone near Brigantine, New Jersey, (fig. 1A) with maximum 

sustained winds of 130 km/h (70 kn; Blake and others, 2013). 

As a result of this turn, coastal habitats located to the right of 

the landfall point continued to be inundated by winds of the 

northeast quadrant pushing water ashore. In contrast, coastal 

habitats located to the left of the landfall point experienced 

strong winds out of the northwest shifting to out of the southwest during storm passage (fig. 1B,C), thereby limiting the 

extent and depth of storm surge in this region (Dennison and 

others, 2012). 

The major impacts of Hurricane Sandy on coastal 

environments were related to the effects of storm surge and 
Hurricane Sandy Effects on Coastal Marsh Elevation Change 9

Identification

Records in 

Chesapeake Bay 

NOAA sentinel 

site inventory

Records in 

Long Island 

Sound Study 

inventory

Records in

the NPS

inventory

Records in 

U.S. Fish and 

Wildlife Service 

inventory

Additional records 

from collaborators

Total (n=1,230)

(n=363) (n=74) (n=130) (n=402) (n=261)

Screening

Records

screened

(n=1,230)

SET-MH 

stations included 

in inventory

(n=965)

Data not provided

Insufficient data record (n=420)

Treatment applied (n=28)

Unidentified reasons (n=34)

Records excluded

Duplicate record (n=85)

Outside study area (n=53)

Outside target community (n=120)

SET damaged or discontinued (n=7)

Total (n=265)

Eligibility

Data assessed 

for eligibility

(n=483)

Data excluded

Treatment applied (n=80)

Insufficient pre-Sandy data (n=156)

Insufficient post-Sandy data (n=22)

Inconsistent trend in pre-Sandy data (n=1)

Post-Sandy outlier (n=1)

Included

SET-MH

stations included

in Hurricane Sandy

effects analysis

(n=223)

Figure 3. Preferred Reporting Items for Systemic Reviews and MetaAnalyses flow diagram detailing the omission of surface elevation tablemarker horizon (SET-MH) records from the inventory and the Hurricane 

Sandy effects analysis. Records are removed from the tally as you move 

down the flow diagram and the list within each box.

(NOAA, National Oceanic and Atmospheric Administration; NPS, National Park Service; n=number of SET-MH stations)
10 Hurricane Sandy Impacts on Coastal Wetland Resilience

associated coastal flooding (Blake and others, 2013; ValleLevinson and others, 2013). Several factors contributed to the 

creation of record high storm surge and coastal inundations in 

the New Jersey, New York, and Connecticut region north of 

landfall. The storm was very large with the extent (diameter) 

of tropical-storm-force winds growing to about 1,611 km prior 

to landfall (Blake and others, 2013). In addition, Hurricane 

Sandy made landfall at high tide and at an angle closer to 

perpendicular to the New Jersey shore than any hurricane in 

the historical record (Hall and Sobel, 2013). The return period 

for a storm of Hurricane Sandy’s intensity with this angle of 

approach is 714 years (Hall and Sobel, 2013). These factors, 

combined with the configuration of the New Jersey–New 

York–Connecticut shoreline and New York Bight bathymetry, 

caused the storm surge to rise up to 3.86 m in the vicinity of 

New York City (Blake and others, 2013). A record storm tide 

(the combination of the storm surge and astronomical tide) of 

4.28 m was recorded at the Battery in New York City (Blake 

and others, 2013). Historical increases in sea level and mean 

flood heights contributed to the record high storm surge and 

storm tide heights at New York City generated by Hurricane 

Sandy (Kemp and Horton, 2013; Talke and others, 2014; 

Kemp and others, 2017; Reed and others, 2015). Another 

contributing factor was the three-fold decrease in the return 

period for a storm of Hurricane Sandy’s flood height during 

the past two centuries (Lin and others, 2016). Consequently, 

the inundations above ground level (in other words, upland 

surfaces) for parts of this region of the coast were as much 

as 3 m (Blake and others, 2013) during Hurricane Sandy. In 

contrast, the peak in storm surge height to the left of landfall 

in the coastal bays of the Delmarva Peninsula behind Fenwick 

and Assateague barrier islands was only ~1.2 m (Dennison and 

others, 2012).

Hypotheses

We hypothesized that differences in physical drivers of 

storm surge extent and duration on either side of a storm’s 

point of landfall could differentially influence the coastal 

marsh processes related to sediment deposition, sediment 

erosion, soil compaction (from storm surge water overburden), and ultimately marsh elevation change (Cahoon, 2006). 

Based on our understanding of the physical characteristics of 

Hurricane Sandy, we used existing knowledge to develop a 

hypothetical structural equation model (SEM) describing the 

processes driving post-storm deviation from expected surface 

elevation change in millimeters (fig. 4). Structural equation 

modeling is a methodology to address questions about complex systems; it is best understood as a framework for quantitative analysis that uses statistical techniques, rather than a 

statistical method itself, and permits the evaluation of networks of direct and indirect effects (Grace and others, 2012). 

The SEM approach used in this study examines both direct 

and indirect influences on deviation from expected change. 

Variables representing storm exposure and intensity (for 

example, distance from landfall and position relative to storm 

landfall [left or right]), and geomorphic setting are predicted to 

directly influence both presence of storm surge and deviation 

from expected change. Additional variables that may account 

for unexplained variance (for example, the rate and variation 

in prestorm surface elevation change) are not predicted to 

influence storm surge exposure and are therefore included only 

as possible direct effects on deviation from expected change. 

Methods

Eligible SET-MH Stations

Although the SET-MH inventory contains 965 stations 

(fig. 2), after determining eligibility for inclusion in our analyses (see description below; eligible stations include SET=223 

and MH=107), only the SET elevation data were included in 

our analysis of Hurricane Sandy effects. Accretion data had 

an inadequate level of replication for inclusion because a 

large number of stations with eligible SET data were missing 

marker-horizon data (55) or had insufficient prestorm (160) 

or poststorm data (93). Without including the accretion data, 

it was not possible to calculate shallow subsidence at the stations, so this variable is not addressed in this report.

Of the 965 stations eligible for inclusion in the SET-MH 

inventory, data were not provided for 482 stations owing to 

insufficient data record (420), experimental treatment applied 

(28), or unidentified reasons (34). Eligibility for analysis of the 

remaining 483 stations was determined using a stepwise exclusion process. Station data (fig. 3) were excluded by criteria 

in the following order: experimental treatment applied (80), 

insufficient prestorm data (156), insufficient poststorm data 

(22), inconsistent trend in prestorm data (1), and a poststorm 

residual distance outlier (1). In some cases, data were not provided if the provider knew a site was ineligible for assessment; 

however, a reason was not always given. In order to minimize 

seasonal variation, we chose one eligible season per SET 

(either winter/spring or summer/autumn) and only included 

data from within that season in an analysis. A season was 

eligible if it had at least one measurement within 1 year poststorm and had ≥ 3years of prestorm data (table 3). Poststorm 

data were ineligible if there was no poststorm measurement in 

an eligible season (≥ 3 years in prestorm record) within 1 year 

following Hurricane Sandy (October 2012-October 2013). 

Measurement season was consistent within a specific station 

but varied among stations.
Methods 11

Deviation from expected 

surface elevation change

Storm surge

(present/absent)

Distance from landfall

Geomorphic

setting

(Estuarine/BBL)

Position relative

to storm landfall

(left/right)

Coefficient of

variation in

prestorm data

Rate of prestorm

surface elevation

change

Figure 4. Initial structural equation model illustrating the hypothetical pathways between predictor variables and response variables. 

Predictors include distance to landfall, geomorphic setting (estuarine or back-barrier lagoon [BBL]), position relative to landfall (left or 

right), coefficient of variation in prestorm data, and rate of prestorm elevation change. Exposure to storm surge is both a predictor and a 

response variable.

Table 3. Five hypothetical examples of surface elevation table (SET) survey times and exclusion of data from analyses based on 

season of prestorm and poststorm measurements. All data were included when the prestorm and poststorm measurements were 

recorded in the same season and there was a minimum of 3 years prestorm data (a). A subset of the data was included when prestorm 

measurements were recorded in multiple seasons and at least one season had ≥3 years of prestorm data and a poststorm record 

(b–c). A SET was excluded from analysis when prestorm and poststorm measurements were recorded in different seasons (d) or when 

prestorm and poststorm measurements were recorded in the same season, yet the number of years in the prestorm record was <3 (e).

[≥, greater than or equal to; <, less than; —, no data]

Data used 

in analyses

Number of years with 

prestorm measurements

Poststorm 

measurement season (x) Season used 

in analyses

Winter/Spring Summer/Autumn Winter/Spring Summer/Autumn

(a) All data 0 ≥3 — x Summer/Autumn

(b) Subset ≥3 ≥1 x — Winter/Spring

(c) Subset <3 ≥3 x x Summer/Autumn

(d) Excluded ≥3 0 — x Neither

(e) Excluded 0 <3 — x Neither
12 Hurricane Sandy Impacts on Coastal Wetland Resilience

Deviation from expected = 21.09 mm

0

−5

5

10

15

20

25

30

35

Mean surface elevation change, in millimeters

Jul 05

Oct 05

Aug 06Nov 06

Sep 07

Aug 08Nov 09Nov 10Aug 11

Sep 13

Measurement date

EXPLANATION

Prestorm regression

● Prestorm data

Poststorm measurement

Deviation from expected 

surface elevation change

Figure 5. Mean surface elevation change from July 2005 to September 2013 at the U.S. Geological Survey Blackwater 7D.1 surface 

elevation table (Cambridge, Md). Regression was calculated from prestorm data. The poststorm measurement had a deviation from 

expected surface elevation change of 21.09 millimeters (mm).

Elevation Response Variable

Deviation from the expected surface elevation change 

trend poststorm was used as the measure of Hurricane Sandy 

effect on marsh surface elevation. We measured the deviation 

from expected change at each station as the residual distance 

of the poststorm mean from the regression line predicted by 

the prestorm means (fig. 5) using a distance to line R function 

developed by Bourke (2015). Prestorm trends were calculated from measurements made within the same season as the 

poststorm measurement (fig. 5, table 3) and poststorm measurements were made within the year following storm passage 

(between November 6, 2012, and October 30, 2013, fig. 6). 

Total surface elevation change is the mean change in pin 

height since baseline for each SET, in order to accommodate 

different numbers of pins among some SETs. 

Days since Hurricane Sandy

0 100 200 300 400

Frequency

0

20

40

60

80

Figure 6. Frequency distribution of number of days between 

Hurricane Sandy (October 30, 2012) and the poststorm surface 

elevation table measurement for each eligible station.
Methods 13

Predictor Variables 

The predictor variables fall into two categories: (1) variables representing storm exposure and intensity, and (2) variables that may account for additional variance in the deviation 

from expected surface elevation change poststorm. 

Variables Representing Storm Exposure and 

Intensity 

Distance to Storm Landfall

We calculated the distance from SET station to storm 

landfall (39.4°N, 74.4°W; Blake and others, 2013) using the 

sp package in R version 3.3.1 (Pebesma and Bivand, 2005; 

Bivand and others, 2013; R Core Team, 2016). Distance was 

calculated in kilometers and was scaled prior to analysis to 

increase similarity with the magnitude of other predictors 

(dist. = distance to landfall/1,000).

Exposure to Storm Surge (Within or Outside 

Surge Zone)

Storm surge area was obtained from the Hurricane Sandy 

Impact Analysis–Federal Emergency Management Agency 

(FEMA) Modeling Task Force (MOTF; 2015a). As highresolution data did not cover the entire study region, we used 

the Medium and Low Resolution Storm Surge Extent (Interim 

30-meter Storm Surge Extent 110112) in ArcGIS 10.1 to 

assign a storm surge category (present/absent). Stations that 

were assigned to the storm-surge-absent category were visually examined and were reassigned if they met at least one of 

the following criteria. If the station was

1. on the open water side of the storm surge boundary 

(n=4 SET); 

2. within 1 m of the storm surge boundary (n=2 SET);

3. within a small pocket of absent space within the storm 

surge boundary, artifacts derived from a minimum mapping unit of 30 m (n=6 SET);

4. on a small island where the adjacent mainland was 

within the storm surge boundary (n=12 SET); or

5. within the high-resolution storm surge boundary 

(n=12 SET).

Stations exposed to (present) and those not exposed to 

(absent) the storm surge were assigned a 1 or 0, respectively, 

during analysis.

Geomorphic Setting

Stations were assigned to one of two potential geomorphic settings: (1) estuarine marsh and (2) back-barrier lagoonal 

marsh (Cahoon and others, 2009). Stations within estuaries 

that flowed into back-barrier lagoons were included in the latter category, as the barrier island was likely to influence storm 

surge timing and severity. Stations within estuaries and those 

within back-barrier lagoons were assigned a 1 or 0, respectively, during analysis.

Position Relative to Storm Landfall

Position relative to landfall was assigned as those to 

the left (south) or those to the right (north) of storm landfall 

(39.4°N, 74.4°W; Blake and others, 2013). Stations to the left 

or right were assigned a 1 or 0, respectively, during analysis. 

This variable represents a complex array of processes. Different physical characteristics between the two positions include, 

but are not restricted to, wind intensity and direction, movement of water and surge retention time, geomorphic setting, 

and differences in underlying parent material which may have 

implications for sediment transport and trapping (table 4; 

Stevenson and others, 1988).

Table 4. Number of surface elevation table (SET) stations used in analyses and distance to storm landfall (minimum, maximum, and 

range) for each unique geomorphic and geographic location category. Categories based on geomorphic setting (back-barrier lagoon, 

estuarine) and position relative to landfall (left or right).

[na, not applicable]

Data Descriptor

Back-barrier lagoon Estuarine

Total

Left of landfall Right of landfall Left of landfall Right of landfall

SET Number of SET stations 26 90 78 29 223

SET Minimum distance (kilometers) 154.47 8.04 89.97 152.34 na

SET Maximum distance (kilometers) 249.03 557.14 298.90 303.91 na

SET Range distance (kilometers) 94.56 549.10 208.93 151.57 na
14 Hurricane Sandy Impacts on Coastal Wetland Resilience

Additional Variables to Account for Unexplained 

Variance

Coefficient of Variation

Coefficient of variation (CV) of the residual distance 

from the prestorm elevation trend line was calculated using 

the formula CV = (Standard deviation*100)/mean residual 

distance of prestorm measurements per SET. This metric indicates the natural long-term variation at the site. 

Rate of Change

Rate of change in the prestorm record (millimeters per 

year [mm/year]) was calculated for elevation data. To calculate 

rate of change, we used mean difference in pin height from 

the first pin measurement (28–36 pin measurements) to fit a 

regression line through multi-year surveys (≥3 years) within 

the same season using R version 3.3.1 (R Core Team, 2016). 

This metric was used to calculate the deviation from expected 

poststorm measurement for each SET station and as an indication of long-term trends in marsh elevation change. 

Correlation Between Predictor Variables

We used generalized variance inflation factor analysis 

(VIF) to assess the co-linearity between predictor variables 

using the car package in R version 3.3.1 (Zuur and others, 

2009; Fox and Weisberg, 2011; R Core Team, 2016). Variables with a VIF>3 are generally considered to have high 

co-linearity. Additionally, we generated bivariate plots to 

visualize correlations between predictor variables.

Structural Equation Model

The deviation from expected elevation change model and 

storm surge submodel in figure 4 (hypothetical model) were 

analyzed separately. We used a piecewise approach to model 

estimation and evaluation rather than relying on an assessment of covariance relations (Grace and others, 2012). This 

approach allowed us to choose from a broader array of tools 

for evaluating each endogenous (response) node. Corrected 

Akaike’s Information Criterion (Burnham and Anderson, 

2002) was used for comparing candidate models chosen for 

interpretation. 

Model Building

We hypothesized there would be a nonlinear positive 

response between distance to storm landfall and both response 

variables (deviation from expected and presence of storm 

surge) where the effect would plateau beyond the region of 

influence. We therefore allowed for base models to accommodate a quadratic distance curve.

To determine the best model of deviation from the 

expected elevation change, a logical subset of all possible 

models was assessed. All candidate models included distance 

to storm landfall, and predictor variables were added to this 

base model in a stepwise fashion. Model complexity increased 

with each additional predictor until all main effects were 

included in a full model. Variable addition was based on the 

degree of correlation between the residuals from the previous model and the remaining predictor variables. Interactions 

between distance to storm landfall and all other variables, and 

between geomorphic setting and all other variables were then 

considered and added to the full model. For simplicity, models 

included only one interaction, and the interaction terms were 

always retained as a main effect. The main effects were examined in each interaction model, and the variable with the greatest P value was removed from the subsequent model. This 

process was repeated on the simplified model and continued 

until all main effects were either present in an interaction or 

had a P value of <0.05. A total of 46 models were included in 

the deviation from expected surface elevation list (table 5). 

All storm surge submodels included distance to storm 

landfall. Position relative to landfall and geomorphic setting 

were included as main effects and in interaction with the distance variable. No models included both categorical predictor 

variables. A total of five models were included in the storm 

surge submodel list (table 6).

Model Assessment

Model assessment ensured a consideration of all possible linkages, with evaluations based on Akaike’s Information Criterion with a correction for finite sample sizes (AICc; 

Burnham and Anderson, 2002). Candidate models for each 

response variable were ranked using their AICc value. The 

difference in AICc from the lowest AICc value (AICcmin) was 

calculated for each candidate model (ΔAICc=AICci-AICcmin) 

and models with ΔAICc<2 were considered equivalent (Burnham and Anderson, 2002). The simplest model with the lowest 

AICc within this top model list was considered the best model, 

and its parameter estimates were examined and interpreted. 

Models were compared using the AICcmodavg package in 

R version 3.3.1 (Mazerolle, 2016; R Core Team, 2016).

Spatial Autocorrelation

Spatial autocorrelation occurs when the residuals of 

data points that are spatially close together are not independent (Bivand and others, 2013). We used Moran’s I to 

statistically test for residual spatial autocorrelation in the 

deviation from expected response variable using the spdep 

package in R version 3.3.1 (Bivand and Piras, 2015; R 

Core Team, 2016). Spatial autocorrelation was assessed 

on links between seven neighboring pairs (k=7). Weights 
Methods 15

Table 5. Models used to determine deviation from expected surface elevation change, measured as the residual distance of poststorm 

elevation change. Number of models=46. Predictors include distance to storm landfall (kilometers/1,000; distance) as a quadratic curve, 

rate of prestorm elevation change (millimeters/year), position relative to landfall, exposure to storm surge, coefficient of variation 

(millimeters), and geomorphic setting. Models with the same number include the same interaction term, indicated by an asterisk.

[—, no data]

Model Distance 

+ distance2

Rate of 

prestorm change

Position relative 

to landfall

Storm 

surge

Coefficient 

of variation

Geomorphic 

setting

1b x — — — — —

2 x x — — — —

3 x x x — — —

4 x x x x — —

5 x x x x x —

6 x x x x x x

7a x x* x x x x*

7b x x* x x — x*

7c x x* — — — x*

7d x x* x — — x*

8a x x x x* x x*

8b x x x x* — x*

8c x — x x* — x*

8d x — — x* — x*

9a x x x x x* x*

9b x — x x x* x*

9c x — x — x* x*

9d x — — — x* x*

10a x* x x x x x*

10b x* x x x — x*

10c x* x — x — x*

10d x* x — — — x*

10e x* — — — — x*

11a x x x* x x x*

11b x x x* x — x*

11c x x x* — — x*

11d x — x* — — x*

12a x* x x x x* x

12b x* x x x x* —

12c x* — x x x* —

12d x* — x — x* —

12e x* — — — x* —

13a x* x* x x x x

13b x* x* x x x —

13c x* x* x x — —

13d x* x* x — — —

13e x* x* — — — —

14a x* x x x* x x

14b x* x x x* x

14c x* x x x* — —

14d x* — x x* — —

15a x* x x* x x x

15b x* x x* — x x

15c x* x x* — x —

15d x* x x* — — —

15e x* — x* — — —
16 Hurricane Sandy Impacts on Coastal Wetland Resilience

were standardized by row, where weights were divided 

by the row sum (style=W). Since spatial autocorrelation was detected, we calculated the effective sample size 

(neff = n / (1 + absolute Moran’s I statistic estimate)) and 

adjusted the AICc values for all top models, adjusted AICc 

values AICcadj = (AIC + ((2K(K + 1))/neff – K – 1)) and 

adjusted summary statistics for predictors in the best deviation 

from expected model and storm surge submodel.

Statistical Programs and Packages Used

All analyses were conducted and graphics were created 

using R version 3.3.1 (R Core Team, 2016) and ArcGIS 10.4. 

The following R packages were used during data formatting: reshape2 (Wickham, 2007), plyr (Wickham, 2014), and 

data.table (Dowle and others, 2015).

Results

Correlation Between Predictor Variables

The VIF values, using eligible SET data, were less than 

three for all predictors in both the deviation from expected and 

storm surge models (table 7). SETs with eligible surface elevation data were graphed in bivariate plots showing the relations 

between pairs of predictor variables (fig. 7): distance to storm 

landfall (fig. 7A–C), geomorphic setting (fig. 7C, E, F), position relative to storm landfall (fig. 7C), rate of prestorm elevation change (fig. 7A, D, E), and coefficient of variation (CV) in 

prestorm data (fig. 7B, D, F). SET stations within back-barrier 

lagoonal settings to the right of landfall had a much greater 

range in distance from landfall, where this category contained 

both the closest and furthest away SET stations, compared 

to stations to the left of landfall and in estuarine settings 

(fig. 7C). Similarly, the range in CV in the prestorm elevation 

change trend was greater in the back-barrier lagoonal setting 

compared to the estuarine setting (fig. 7F). The other bivariate 

comparisons revealed no important relations (fig. 7A, B, D, E).

Distribution of SET-MH Stations Used in Effects 

Analysis

A number of factors contribute to the distribution of sampling in large spatial datasets, resulting in uneven dispersion of 

replicates among geographic and geomorphic settings. In this 

study some of these spatial factors include the opportunistic 

nature of the SET-MH network, the distribution of geomorphic 

settings along the east coast from Virginia to Maine, and the 

location of Hurricane Sandy landfall (fig. 8). The distribution 

of eligible SET stations between geomorphic settings, position relative to storm landfall, and distance from storm landfall 

(table 4 and fig. 8C) show that the majority of stations within 

back-barrier lagoonal marsh (BBL) were located to the right of 

landfall (78 percent), and the majority of stations within estuarine marsh were located to the left of landfall (73 percent). 

SET stations occur from 8 km to as much as 557 km from the 

storm landfall (table 4).

Deviation from Expected Surface Elevation 

Change Model

The model with a quadratic curve had the lowest AICc 

value (1,758.71) for predicting the relation between deviation 

from expected surface elevation change and distance from 

storm landfall. The model with a linear curve was greater than 

two points from this AICcmin model (ΔAICc = 21.34; table 8). 

Therefore, the quadratic distance curve was included in all 

deviation from expected elevation models. 

Three of 46 models had a ΔAICc less than 2 from the 

AICcmin model (table 9) for predicting the deviation from 

expected surface elevation change. The simplest model was 

Table 6. Storm surge submodels. Predictors include distance 

to storm landfall (kilometers/1,000; distance), geomorphic setting, 

and position relative to landfall.

[—, no data; *, indicates a two-way interaction between variables]

Model Distance Geomorphic 

setting

Position 

relative to 

landfall

1a x — —

2 x x —

3 x — x

4 x* x* —

5 x* — x*

Table 7. Results from variance inflation factor (VIF) analysis 

assessing the colinearity between predictor variables in the 

deviation from expected surface elevation model and the storm 

surge submodel. VIF>3 indicates high colinearity.

[>, greater than; na, not applicable]

Predictor

Variance inflation 

factor values

Surface 

elevation 

model

Storm 

surge 

submodel

Distance from storm landfall 2.16 2.02

Geomorphic setting 1.66 2.21

Position relative to storm landfall 1.75 2.13

Exposure to storm surge 2.18 na

Rate of pre-Sandy elevation change 1.09 na

Coefficient of variation in pre-Sandy record 1.04 na
Results 17

0 100 200 300 400 500 600

0

−10

10

20

30

40

50

Distance to storm landfall, in kilometers

Rate of prestorm elevation change,

in millimeters per year

A

0 100 200 300 400 500 600

Distance to storm landfall, in kilometers

20

0

40

60

80

100

120

140

160

CV in prestorm elevation change, in millimeters 

B

BBL.left BBL.right Estuarine.left Estuarine.right

0

100

200

300

400

500

600

Geomorphic setting and position from landfall

Distance to storm landfall, in kilometers

C

0 20 40 60 80 100 120 140 160

0

10

−10

20

30

40

50

CV in prestorm elevation change, in millimeters

Rate of prestorm elevation change, 

in millimeters per year

D

BBL Estuarine

0

10

−10

20

30

40

50

Geomorphic setting

Rate of prestorm elevation change,

in millimeters per year 

E

BBL Estuarine

20

0

40

60

80

100

120

140

160

Geomorphic setting

CV in prestorm elevation change,

in millimeters 

F

EXPLANATION

95-percent confidence 

interval

95-percent confidence 

interval

75th percentile

50th percentile (median)

25th percentile

EXPLANATION

95-percent confidence 

interval

95-percent confidence 

interval

75th percentile

50th percentile (median)

25th percentile

EXPLANATION

95-percent confidence 

interval

95-percent confidence 

interval

75th percentile

50th percentile (median)

25th percentile

Figure 7. Bivariate relations between predictor variables in the eligible total surface elevation dataset. Relations between distance 

from storm landfall and A, rate of prestorm surface elevation change, B, coefficient of variation (CV) in prestorm surface elevation 

change, and C, geomorphic setting and position relative to landfall categories. Relations between D, CV in prestorm surface elevation 

change and rate of prestorm surface elevation change, and between geomorphic setting and E, rate of prestorm surface elevation 

change, and F, CV in prestorm surface elevation change. Geomorphic setting categories include back-barrier lagoonal marsh (BBL) and 

estuarine marsh (Estuarine). Position categories include left and right of landfall.
18 Hurricane Sandy Impacts on Coastal Wetland Resilience

76° 74° 72° 70°

44°

42°

40°

38°

SET Station Locations—

Position relative to landfall

Left

Right

Hurricane Sandy 

storm track

Wind swaths

EXPLANATION

Map image is the intellectual property of Esri and is used herein under license. 

Copyright © 2019 Esri and its licensors. All rights reserved.

0 50 100 MILES

0 90 180 KILOMETERS

ATLANTIC

OCEAN

ME

NH VT

NY

MA

CT RI

PA

NJ

DE

MD

DC

VA

A

76° 74° 72° 70°

44°

42°

40°

38°

SET Station Locations—

Geomorphic setting

Back-barrier lagoon

Estuarine

Hurricane Sandy 

storm track

Wind swaths

EXPLANATION

0 50 100 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 90 180 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

ATLANTIC

OCEAN

ME

NH VT

NY

MA

CT RI

PA

NJ

DE

MD

DC

VA

B

Figure 8. Study region showing storm track, wind swaths (34 and 64 knots), and stations with eligible surface elevation table (SET)

data in each category: A, position relative to landfall (left or right), B, geomorphic setting, and C, storm surge. Storm track and wind 

swath shapefiles from the National Oceanic and Atmospheric Administration (2014).
Results 19

76° 74° 72° 70°

44°

42°

40°

38°

SET Station Locations—

Storm surge exposure

No Surge

Surge

Hurricane Sandy 

storm track

Wind swaths

EXPLANATION

0 50 100 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 90 180 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

ATLANTIC

OCEAN

ME

NH VT

NY

MA

CT RI

PA

NJ

DE

MD

DC

VA

C

Figure 8. Study region showing storm track, wind swaths (34 and 64 knots), and stations with eligible surface elevation table (SET) 

data in each category: A, position relative to landfall (left or right), B, geomorphic setting, and C, storm surge. Storm track and wind 

swath shapefiles from the National Oceanic and Atmospheric Administration (2014).—Continued

Table 8. Comparing distance from storm landfall curves (linear and quadratic) in the deviation from expected surface elevation model 

and storm surge submodel using Akaike’s Information Criterion, AICc.

[Δ, change in]

Response Predictor AICc ΔAICc Weight

Deviation from expected elevation change Distance + distance2 1,758.71 0 1

Distance 1,780.05 21.34 0

Storm surge Distance 145.04 0 0.62

Distance + distance2 145.98 0.94 1

model 15e, which consisted of an interaction between distance 

from and position relative to landfall with no other predictors (table 5). See table 3.1 in appendix 3 for model summary 

information and figure 9 for model predicted versus response 

plot. Model 15e was determined to be the best model available for predicting deviation from expected surface elevation 

change following Hurricane Sandy.

As deviation from the expected surface elevation change 

trend was spatially autocorrelated (P<0.001, SD=7.89), we 

calculated effective sample size and used this to calculate 

an adjusted AICc value for the three top models (table 10). 

Although the ΔAICc based on the adjusted values (ΔAICc for 

model 15c=0.625 and model 15e=0.633) differed from the 

unadjusted values (ΔAICc=0.67 and 0.681, respectively), the 

order did not change. 

Parameter estimates from model 15e (best model) 

indicate that within 200 km from storm landfall there was a 

greater negative deviation from the expected elevation change 

trend (elevation loss) and a greater effect of distance to landfall in stations to the right of landfall than to the left (fig. 10; 

table 3.1 in appendix 3). 

Owing to yearly variation among surveys, we expected 

that poststorm measurements would exhibit some deviation 

from the expected change trend, irrespective of hurricane 

influence. Prestorm mean residual distance and poststorm 

residual distance from the prestorm trend line were less than 

or equal to ±5 mm for 89.7 percent and 62.8 percent of eligible SET stations, respectively, indicating greater variation 

in the residual distance (in other words, exceeding ±5 mm) 

poststorm (fig. 11). Of the 223 eligible SET stations, there 

were 125 stations (56.1 percent) with a deviation greater than 

expected (elevation gain) and 98 stations (43.9 percent) with 

a deviation less than expected (elevation loss; fig. 11A). Based 

on these distributions, we suggest that a deviation of greater 
20 Hurricane Sandy Impacts on Coastal Wetland Resilience

Table 9. Deviation from expected surface elevation change models ranked by corrected Akaike’s Information Criteria (AICc). Models 

with small AICc values are considered higher quality, and models with an AICc difference of less than 2 (ΔAICc<2) are considered 

equivalent (shaded blue). Of these equivalent models, the simplest model is indicated by an * and considered the best (model 15e). 

Model details are listed in table 4. The number of estimated parameters (K) indicates model complexity and is used to calculate AICc. 

Weights indicate the normalized model likelihoods (sum to 1).

[Δ, change in]

Model K AICc ΔAICc AICc weight Cumulative weight Log Likelihood

15d 7 1,749.13 0 0.27 0.27 −867.3

15c 8 1,749.65 0.52 0.21 0.48 −866.49

*15e 6 1,749.78 0.65 0.19 0.67 −868.69

7d 7 1,751.33 2.2 0.09 0.76 −868.4

15b 9 1,751.41 2.28 0.09 0.85 −866.28

7c 8 1,752.78 3.65 0.04 0.89 −868.06

15a 10 1,753.54 4.41 0.03 0.92 −866.25

7b 9 1,754.04 4.91 0.02 0.94 −867.6

7a 10 1,755.86 6.73 0.01 0.95 −867.41

14c 8 1,757.5 8.37 0 0.96 −870.41

14d 7 1,757.79 8.66 0 0.96 −871.63

10d 7 1,757.88 8.75 0 0.96 −871.68

2 5 1,758.2 9.07 0 0.96 −873.96

3 6 1,758.5 9.37 0 0.97 −873.05

12c 8 1,758.63 9.5 0 0.97 −870.98

10c 8 1,758.68 9.55 0 0.97 −871

12d 7 1,758.72 9.59 0 0.97 −872.1

14b 9 1,758.79 9.66 0 0.98 −869.97

4 7 1,758.86 9.73 0 0.98 −872.17

10e 6 1,758.87 9.74 0 0.98 −873.24

12b 9 1,758.94 9.81 0 0.98 −870.05

1b 4 1,759.17 10.04 0 0.98 −875.49

13e 6 1,759.38 10.25 0 0.99 −873.5

12e 6 1,759.38 10.25 0 0.99 −873.5

13d 7 1,759.67 10.54 0 0.99 −872.57

10b 9 1,759.8 10.67 0 0.99 −870.48

13c 8 1,760.04 10.91 0 0.99 −871.68

5 8 1,760.14 11.01 0 0.99 −871.73

11d 7 1,760.42 11.29 0 0.99 −872.95

10a 10 1,760.59 11.46 0 0.99 −869.77

14a 10 1,760.6 11.47 0 0.99 −869.78

11c 8 1,760.78 11.65 0 1 −872.05

12a 10 1,761.06 11.93 0 1 −870.01

13b 9 1,761.18 12.05 0 1 −871.17

11b 9 1,762.09 12.96 0 1 −871.62

8c 8 1,762.19 13.06 0 1 −872.76

6 9 1,762.28 13.15 0 1 −871.72

8b 9 1,762.5 13.37 0 1 −871.83

13a 10 1,763.33 14.2 0 1 −871.14

9c 8 1,763.68 14.55 0 1 −873.5

11a 10 1,763.77 14.64 0 1 −871.37

8a 10 1,763.85 14.72 0 1 −871.41

8d 7 1,763.87 14.74 0 1 −874.68

9b 9 1,763.89 14.76 0 1 −872.52

9d 7 1,763.95 14.82 0 1 −874.71

9a 10 1,764.4 15.27 0 1 −871.68
Results 21

−25 −20 −15 −10 −5 0 5 10

−60

−80

−40

−20

0

20

40

60

80

Predicted from mod15e

Poststorm residual distance, in millimeters

Figure 9. Model prediction versus response for the best 

deviation from expected surface elevation model (15e).

0.0 0.1 0.2 0.3 0.4 0.5 0.6

−60

−80

−40

−20

0

20

40

60

80

Distance to storm landfall, in kilometers/1,000

Poststorm residual distance, in millimeters

EXPLANATION

● Right

Left

No deviation from 

expected change

Figure 10. Poststorm deviation from expected surface 

elevation change along the distance to storm landfall gradient 

(kilometers/1,000). Lines are parameter estimates, from the best 

model (model 15e), for stations to the right (closed circle, solid 

line) and left (open circle, dashed line) of storm landfall. Dotted 

grey line indicates no deviation from expected change. Only 

eligible surface elevation data are displayed and used in analysis 

(223 surface elevation table stations).

Table 10. Effective sample sizes (neff) for all top models. Of 

these equivalent models the simplest model is indicated by an * 

and considered the best (model 15e). Model details are listed in 

table 4. K=number of estimated parameters, and n=223 surface 

elevation tables stations.

[AICcadj, corrected Akaike’s Information Criteria; Δ, change in]

Model K neff AICcadj ΔAICcadj

Deviation from expected surface elevation

15d 7 169 1,749.31 0

15c 8 170 1,749.89 0.58

*15e 6 170 1,749.90 0.60

Storm surge submodel

3 3 156 95.41 0

5 4 156 96.71 1.31

than 5 mm from expected is more likely to indicate an effect of 

Hurricane Sandy on the rate of elevation change than a deviation of less than 5 mm. If we look at the stations with a greater 

than 5 mm deviation from expected, we find that stations to 

the left of landfall were more likely to experience a greater 

than expected elevation change (27 stations; 77.1 percent) than 

a less than expected change (8 stations; 22.9 percent; fig. 12A; 

table 11). This trend was also evident in the range and mean 

deviation from expected values exhibited to the left of landfall 

(range=−28.8 to 60.0 mm; mean loss=−15.9±3.6 mm; mean 

gain=18.0±2.4 mm; table 11). This suggests elevation gain 

was more prevalent than elevation loss in stations located to 

the left of landfall. To the right of landfall, the proportion of 

stations with greater than expected change was similar to those 

with less than expected change (28 stations (58.3 percent) and 

20 stations (41.7 percent), respectively; fig. 12B; table 11). 

Stations to the right tended to experience greater elevation loss 

(range=−69.4 to 43.8 mm; mean loss=−19.7±4.8 mm; mean 

gain=10.9±1.6 mm; table 11).

Stations with the greatest elevation loss were located 

to the right of landfall, whereas stations that experienced the 

greatest elevation gain were to the left of landfall (fig. 12, 

table 11). The range in deviation from the expected elevation 

change trend was greater to the right of landfall than to the 

left (113.2 and 88.8 mm, respectively; table 11). To the right 

of landfall there were greater negative values (elevation loss) 

than to the left (minimum=−69.4 and −28.8 mm, respectively), 

and the maximum positive value (elevation gain) was lower 

to the right than to the left of landfall (maximum=43.8 and 

60.0 mm, respectively; fig. 12).

Storm Surge Submodel

To predict the relation between storm surge and distance 

from storm landfall, the model that assumed a linear relation between response and predictor variables had the lowest 

AICc value (145.04). Even though the model containing the 

quadratic relation had a ΔAICc less than two (ΔAICc=0.94; 

table 8), the linear relation was included in all storm surge 

submodels.

Two of five models had a ΔAICc less than two from the 

AICcmin model (table 12) for predicting presence of storm 

surge. The simplest model was submodel 3, which consisted 

of distance from, and position relative to, landfall with no 

interaction (table 6). See table 3.2 in appendix 3 for model 

summary information. Submodel 3 was therefore considered 

the best model available for predicting storm surge presence 

during Hurricane Sandy.

We calculated effective sample size and used this to 

calculate an adjusted AICc value for the two models with 
22 Hurricane Sandy Impacts on Coastal Wetland Resilience

Poststorm (n = 223)

Poststorm residual distance, in millimeters

Frequency

−80 −60 −40 −20 0 20 40 60 80

0

20

40

60

80

A

Prestorm mean (n = 223)

Prestorm mean absolute residual distance, in millimeters

Frequency

0 10 20 30 40 50

0

50

100

150

200

250

B

Figure 11. Frequency distribution of A, poststorm residual distance from expected (millimeters, ±) and B, prestorm mean residual 

distance (millimeters, absolute) using all eligible surface elevation table data.

(n, number of surface elevation table-marker horizon stations)
Results 23

Left of landfall (n = 104)

Poststorm residual distance, in millimeters

Frequency

−80 −60 −40 −20 0 20 40 60

0

10

20

30

40

50

A

Right of landfall (n = 119)

Poststorm residual distance, in millimeters

−80 −60 −40 −20 0 20 40 60

Frequency

0

10

20

30

40

50

B

Figure 12. Frequency distribution of poststorm residual distance from expected for eligible surface elevation table stations to the A, 

left and B, right of landfall.

(n, number of surface elevation table-marker horizon stations)
24 Hurricane Sandy Impacts on Coastal Wetland Resilience

Table 11. Summary information for stations with a deviation from expected elevation change greater than ±5 millimeters. Number of 

stations (n) with elevation gain and loss in each position relative to landfall category (all stations, left, right) and presence or absence of 

storm surge, along with the maximum value, mean, and standard error (SE) are included.

Position Direction of 

elevation effect

n 

(percent)

Maximum deviation 

(in millimeters)

Mean ± SE 

(in millimeters)

All

Gain 55 (66.3) 60.0 14.4±1.5

Loss 28 (33.7) −69.4 −18.6±3.6

Left

Gain 27 (77.1) 60.0 18.0±2.4

Loss 8 (22.9) −28.8 −15.9±3.6

Right

Gain 28 (58.3) 43.8 10.9±1.6

Loss 20 (41.7) −69.4 −19.7±4.8

Storm surge

Gain 103 (58.9) 60.0 7.9±1.0

Loss 72 (41.1) −69.4 −7.5±1.7

No storm surge

Gain 22 (45.8) 20.4 4.3±1.1

Loss 26 (54.2) −11.5 −2.5±0.6

Table 12. Storm surge models ranked by corrected Akaike’s Information Criteria (AICc). Models with small AICc values are considered 

higher quality, and models with an AICc difference of less than 2 (ΔAICc<2) are considered equivalent (shaded). Of these equivalent 

models the simplest model is indicated by an * and considered the best (model 3). Model details are listed in table 5. Number of 

estimated parameters (K) indicates model complexity. Weights indicate the normalized model likelihoods (sum to 1).

[Δ, change in]

Model K AICc ΔAICc AICc weight Cumulative weight Log likelihood

3* 3 95.36 0 0.65 0.65 −44.62

5 4 96.63 1.27 0.35 1 −44.22

2 3 138.21 42.86 0 1 −66.05

4 4 139.65 44.29 0 1 −65.73

1a 2 145.04 49.68 0 1 −70.49

the lowest AICc value (table 10). The ΔAICc based on the 

adjusted sample size (ΔAICc=1.31) was greater than the unadjusted value (ΔAICc=1.27); however, the order did not change 

(tables 10 and 12). 

Based on submodel 3 (best model), the probability 

that a station was exposed to the storm surge was predicted 

to decrease with increasing distance from landfall (fig. 13; 

table 3.2 in appendix 3). Submodel 3 also predicted a shorter 

distance of influence to the left of landfall than to the right 

(fig. 13; table 3.2 in appendix 3). 

The omission of storm surge from the best deviationfrom-expected-change model may reflect the variation in 

direction (loss or gain) more than the magnitude of the effect. 

There were a greater number of eligible SET stations with 

storm surge present than absent (175 and 48 respectively; 

fig. 14). The deviation from the expected elevation change 

trend had both greater positive (elevation gain) and negative 

(elevation loss) values and greater mean values at stations 

exposed to the Hurricane Sandy storm surge (range=−69.4 to 

60.0 mm, mean gain=7.9±1.0 mm, mean loss=−7.5±1.7 mm) 

than those outside storm surge influence (range=−11.5 to 

20.4 mm, mean gain=4.3±1.1 mm, mean loss=−2.5±0.6 mm, 

table 11). There were a greater percentage of stations within 

the ±5 mm deviation from the expected change trend in areas 

that storm surge was absent from than present (77.1 percent 

and 58.9 percent, respectively; fig. 14). This suggests that even 

though storm surge tended to increase the magnitude of deviation from expected it had a complex influence on marsh surface elevation change, resulting in both loss and gain, which 

may explain the absence of this effect in model selection. 

Structural Equation Model Selected for 

Interpretation

We used the best deviation-from-expected surface 

elevation change model and storm surge submodel to create 

a revised SEM (fig. 15; compare to initial model in fig. 4). 

Distance from landfall (−0.71) and position relative to landfall 

(−0.16) were found to explain the likelihood of storm surge 

presence in the SET data. Observed storm surge presence or 

absence, however, did not help explain deviation from the 

expected surface elevation change trend. Rather, deviation 

from expected elevation change was explained by the interaction between distance from landfall and position relative to 

landfall (see for example, figs. 10 and 12). Furthermore, geomorphic setting, coefficient of variation in prestorm elevation 
Discussion 25

trend, and rate of prestorm elevation trend had no significant 

effect on the deviation from the expected elevation change.

Discussion

Spatial Variation in Storm Impacts

Understanding the impact of Hurricane Sandy on coastal 

wetland elevation change requires knowledge of both the 

physical characteristics of the storm and its interaction with 

coastal landforms it encounters. Our analyses indicate there 

are important landform differences in coastal geomorphology 

and wetland setting on either side of the point of landfall at 

Brigantine, New Jersey. To the right of landfall the predominant wetland type is back-barrier marsh, whereas to the left 

of it is predominantly estuarine marsh along tidal tributaries 

of Delaware Bay and Chesapeake Bay. Hurricane Sandy’s 

physical characteristics meant that storm surge area was more 

extensive right of the landfall in the northeast quadrant of the 

storm than left of the landfall where winds switched from out 

of the northwest to out of the southwest during storm approach 

and passage (Dennison and others, 2012; Middleton, 2016; see 

fig. 1). This difference in surge dynamics resulted in important differences in wetland impacts to the right and left of the 

landfall point. The smaller surge area to the left of landfall 

indicates a shorter distance of surge influence there compared 

to the right of landfall (fig. 13). To the left of landfall, elevation gain was more prevalent than elevation loss, and the 

greatest elevation gains for the northeast region were found 

in these stations. To the right of landfall, stations were located 

closer to landfall. These stations experienced the greatest 

elevation loss and range in deviation from expected, and the 

maximum elevation gains were lower than stations to the left. 

These effects appear to be the result of the interaction between 

distance from, and position relative to, landfall as shown in the 

causal model (fig. 15). This finding is supported by a remotesensing study of Hurricane Sandy’s storm surge impact on salt 

marsh condition (Rangoonwala and others, 2016), where salt 

marshes located within 20 km right (north) of landfall experienced high surge persistence and high salt marsh condition 

change compared to marshes further north of the storm track. 

0.0 0.1 0.2 0.3 0.4 0.5 0.6

0

1

Distance to storm landfall, in kilometers/1,000

Storm surge presence or absence

EXPLANATION

● Right

Left

Figure 13. Storm surge presence (1) or absence (0) along the distance from landfall gradient. Lines are parameter estimates, from the 

best submodel (submodel 3), for stations to the right (closed circle, solid line) and left (open circle, dashed line) of storm landfall. Data 

and models are based on eligible surface elevation data (223 surface elevation table stations). Points are randomly placed along the 

vertical axis for visibility of overlapping points.
26 Hurricane Sandy Impacts on Coastal Wetland Resilience

Surge present (n = 175)

Poststorm residual distance, in millimeters

Frequency

−80 −60 −40 −20 0 20 40 60

0

10

20

30

40

50

60

A

Surge absent (n = 48)

Poststorm residual distance, in millimeters

Frequency

−80 −60 −40 −20 0 20 40 60

0

10

20

30

40

50

60

B

Figure 14. Frequency distribution of poststorm residual distance from expected for eligible surface elevation table stations with storm 

surge A, present and B, absent.

(n, number of surface elevation table-marker horizon stations)
Discussion 27

Deviation from expected 

surface elevation change

Storm surge

(present/absent)

Distance from landfall

Geomorphic

setting

(Estuarine/BBL)

Position relative

to storm landfall

(left/right)

Coefficient of

variation in

prestorm data

Rate of prestorm

surface elevation

change

−0.71

−0.16

R2

 = 0.45

R2

 = 0.16

±0.40

Figure 15. Revised surface elevation model. Solid lines represent pathways among predictors present in the best deviation from 

expected model (model 15e) and storm surge submodel (submodel 3). Dashed lines represent hypothesized pathways that were not 

present in the best models. The standardized regression coefficients are reported for noninteracting predictors, and the combined 

effect is reported for the interaction between predictors.

(R, residual; BBL, back-barrier lagoon)

Rapid assessment of Hurricane Sandy impacts based on 

qualitative visual observations made in the weeks immediately 

following the storm revealed low levels of impacts to coastal 

marshes in general across the northeast region (American 

Littoral Society, 2012; Grubel and others, 2012; Dennison and 

others, 2012). For example, along the shores of New Jersey, 

Long Island Sound, and New York Harbor-Raritan-Jamaica 

Bays, 14–17 percent of marshes experienced moderate levels 

of damage, whereas 54–64 percent of marshes experienced 

low levels of damage (American Littoral Society, 2012). Only 

a few marshes exhibited high levels of impacts (for example, 

Little Egg Harbor). Typically, wrack deposits were visible 

at the marsh upland edge in many back-bay marsh areas but 

not in the marsh itself. Marsh-edge erosion was observed in 

some locations (for example, Barnegat Bay marshes located 

at the point of landfall; Martha Maxwell-Doyle, Barnegat Bay 

Partnership, oral commun., May 18, 2017), but no quantitative 

data were available to evaluate its extent across the region. A 

geographic information system (GIS) analysis of Hurricane 

Sandy impacts to coastal wetlands of New Jersey revealed 

that salt marshes were impacted by either erosion or sediment deposition (Hauser and others, 2015). Although such 

visual observations can be useful, they also can be misleading because they do not account for the storm’s influence on 

subsurface processes such as shallow subsidence or shallow 

expansion (for example, root zone expansion from enhanced 

root growth or dilation water storage), which can vary widely 

among sites and storms and are often the dominant control on 

elevation change (Cahoon, 2006). For example, compaction 

by storm surge, when it occurred, ranged from 3 to 33 mm in a 

recent review of major storm impacts (Cahoon, 2006). 

In an empirical, quantitative evaluation of three marshes 

in Delaware Bay left of landfall and three marshes in Barnegat 

Bay right of landfall where SET-MH sampling stations had 

been established 1.5 years prior to Hurricane Sandy, Quirk 

(2016) found little evidence of widespread wrack, sediment 

deposition, or vegetation removal on the marsh surface. Over 

the poststorm period, surface accretion/erosion was within 

the range of variability prior to the storm in all six marshes. 

Surface elevation change over the poststorm period was 

within the range of variability of prestorm trends for four of 

the six marshes, with one of the remaining marshes exhibiting 

significant shallow expansion and the other significant shallow 

subsidence. Similar storm surge effects on sediment deposition 
28 Hurricane Sandy Impacts on Coastal Wetland Resilience

processes were observed in 1989 by Gardner and others (1991, 

1992) in a South Carolina salt marsh impacted by Hurricane 

Hugo, a category 4 storm whose approach was perpendicular 

to the shore. Mud was deposited in the forest located inland 

of the salt marsh, but not in the marsh itself (Gardner and 

others, 1991). They hypothesized that the 3- to 4-m-deep 

surge protected the marsh surface from wind, wave action, 

and currents. Quirk (2016) also hypothesized that much of the 

material carried by Hurricane Sandy flood waters passed over 

the marsh and was deposited along areas of taller structure 

than marsh grass, such as the upland-forest edge. Indeed, 

recent investigations using large-scale experimental flumes 

demonstrate that vegetated marsh surfaces effectively attenuated waves and prevented erosion of the marsh surface during 

storm surge flooding (Moller and others, 2014; Rupprecht and 

others, 2017). See Leonardi and others (2018) for a review of 

the interaction between storm surge and salt marsh vegetation 

as it relates to surface sedimentation and erosion. 

These observations may explain why surface elevation gain was lower and surface elevation loss more likely in 

marshes located right of landfall, where storm surge was more 

extensive and strongest during Hurricane Sandy. It is likely 

there were fewer opportunities for sediment deposition on 

the marsh surface and more opportunities for compaction of 

the marsh substrate by the overburden of the 3- to 4-m storm 

surge compared to marshes located left of landfall. It may also 

provide insight into why marsh surface elevation gain was 

more prevalent in the marshes to the left of landfall, where the 

surge was less extensive and less deep, such as Chesapeake 

Bay. In Chesapeake Bay, Dennison and others (2012) reported 

that winds during Hurricane Sandy started from the northwest 

as the storm approached the mid-Atlantic (blowing water to 

the south, out of the bay) and transitioned to the southwest as 

the eye of the storm passed inland north of Chesapeake Bay 

(fig. 1). The wind shift to the southwest blew water from the 

west side to the east side of Chesapeake Bay, causing winddriven flooding on the east shore. Thus, deviation from the 

expected poststorm elevation trend was greater on the east 

side than the west side of the Chesapeake Bay (5.4±1.7 mm 

versus 0.7±0.9 mm). Poststorm field observations by Cahoon 

at Blackwater National Wildlife Refuge (NWR; east side) 

revealed storm-related sediment deposits on some brackish 

marsh surfaces along the Blackwater River that flows into 

Fishing Bay on the east shore of Chesapeake Bay. Apparently, 

sediment-laden water pushed up into the headwaters of rivers 

and small bays along the east shore of the bay associated with 

the ~1 m surge resulted in more prevalent sediment deposition 

and elevation gain in those marshes. 

These results are consistent with the physical characteristics of Hurricane Sandy, but the range of variation in 

poststorm residual distance from predicted surface elevation 

change both left and right of the storm (fig. 12), and in the 

presence and absence of storm surge (fig. 14), indicates that 

a combination of factors beyond just the physics of the storm 

influenced wetland responses. Some of these factors likely 

include sediment supply, wetland productivity and integrity, 

wetland elevation relative to mean sea level, and the degree of 

hydrologic alterations by human activities. 

Implications for Marsh Resilience

The long-term impacts on marsh resilience of a highmagnitude, low-frequency event like Hurricane Sandy are 

variable and may appear incongruous with such a physically 

powerful event. For example, although we do not know the 

impact of Hurricane Hugo on marsh surface elevation change 

throughout the entire coastline it affected, that storm had no 

long-term impact on salt marsh integrity at North Inlet in 

South Carolina (Gardner and others, 1991, 1992). Similarly, 

Rachlin and others (2017) report that species composition 

of vascular flora of salt marshes in New Jersey, New York, 

and Connecticut showed a high degree of stability (in other 

words, little change) following Hurricane Sandy. Longenecker 

and others (2018) report that vegetation cover and composition were similar before and after Hurricane Sandy in tidal 

marsh at Edwin B. Forsythe NWR in New Jersey, which is 

located at the point of landfall. In addition, Wang and others 

(2017) report a very complex pattern of accretion and erosion of marsh surfaces for salt marshes across Jamaica Bay, 

but eroded marsh surfaces recovered from the sediment loss 

after 1 year. Quirk (2016) hypothesized that Hurricane Sandy 

impacts on marsh surface accretion and elevation change will 

have little influence on longer-term elevation trends as well. 

Given the degree of spatial variation we found in Hurricane 

Sandy surge effects on marsh elevation change, the implications for marsh resilience to future storms also will vary 

spatially across the northeastern United States. 

Our analyses provide inferences for storm impacts in the 

short-term (1-year poststorm). Namely, those stations located 

left of landfall, compared to those on the right, experienced 

a greater deviation from expected elevation change, and the 

deviation was more likely to be positive (elevation gain). 

Stations to the right of landfall experienced smaller maximum 

deviations from expected, and the deviations were more likely 

to be negative (elevation loss). Although long-term inferences 

(>1 year poststorm) cannot be drawn from our analyses, it is 

clear that the more prevalent gain in elevation in the marshes 

located left of storm landfall more likely resulted in gains 

in elevation capital (marsh elevation in relation to mean sea 

level; Reed, 2002; Cahoon and Guntenspergen, 2010) for 

those marshes. In contrast, the predominance of elevation 

loss in marshes to the right of landfall in the barrier island 

systems of northern New Jersey, New York, and Connecticut 

likely indicates those marshes lost elevation capital. Another 

potential factor contributing to elevation loss in the northern 

marshes to the right of landfall is that they are all built on 

underlying coarse-grained parent materials deposited during 

and immediately after the last glaciation. This has implications 

for sediment transport and trapping, with northern marshes 

often considered sediment starved and more dependent on 

organic matter accumulation, which ultimately impacts 
Factors to Consider in Development of a Strategic Monitoring Framework 29

long-term marsh stability (Stevenson and others, 1988). Hurricane Sandy came ashore just south of the glacial deposit line, 

which adds another confounding factor in understanding the 

geomorphic setting along this coastline. 

Future coastal flood risk for the east coast of the United 

States will be strongly influenced by sea-level rise and 

changes in the frequency and intensity of tropical cyclones 

(Tebaldi and others, 2012; Woodruff and others, 2013; Little 

and others, 2015). The return period for Hurricane Sandy’s 

flood height is predicted to decrease during the next century by 

a factor of as much as 17-fold, owing to both sea-level rise and 

changes in storm climatology (Lin and others, 2016). The frequency of tropical cyclones is projected to decrease, although 

the frequency of more intense storms (category 4 and 5) is 

projected to increase, as is overall tropical cyclone intensity 

(Knutson and others, 2010; Bender and others, 2010; Peduzzi 

and others, 2012). For the northeastern U.S. coast (Virginia 

and northward), relative sea-level rise is projected to be 

greater than the global average for most future Global Mean 

Sea Level rise scenarios (for example, 0.3 to 0.5 m or more 

by the year 2100 under the Intermediate Scenario [Sweet and 

others, 2017]), and the mid-Atlantic coast of the United States 

is considered a hotspot of accelerated sea-level rise (Sallenger 

and others, 2012). Furthermore, acceleration in flooding, 

including minor flooding, is predicted to occur for the northeast region (Ezer and Atkinson, 2014), although the existence 

of coastal wetlands is known to reduce flood damage to 

human infrastructure on the coast (Narayan and others, 2017). 

Thus, gains in marsh elevation capital are needed to offset the 

projected increases in sea level and coastal flooding frequency 

(Cahoon, 2015), and to sustain existing marshes. Notably, as a 

result of Hurricane Sandy, more marshes in the Delaware Bay 

and Chesapeake Bay region gained short-term resilience than 

marshes in the New Jersey to Connecticut region. Yet, each 

future major storm to make landfall in the northeastern United 

States will have its own unique characteristics and storm surge 

impacts on coastal marsh elevation that will have a cumulative 

effect on future marsh elevation capital and resilience. The 

impact of each high-magnitude, low frequency storm event (in 

other words, hurricanes) will be additive to the impacts of the 

low-magnitude, high-frequency storm events (in other words, 

northeaster storms) that typically occur in the northeast region 

of the United States each year and can generate substantial 

storm surges during the winter and spring (Davis and Dolan, 

1993; Booth and others, 2016).

Factors to Consider in Development of 

a Strategic Monitoring Framework 

Objective 4 of this project is to develop a framework 

for a strategic monitoring network of SET-MH (from here on 

SET) stations in the northeastern United States to improve 

assessments of climate change impacts and related phenomena 

on coastal wetlands. The 965 eligible SET stations located in 

the northeastern United States (fig. 3), including both geomorphic settings of estuarine marsh and back-barrier lagoonal 

marsh, are classified as estuarine emergent marsh (NWI 

classification: E2EM) habitat. We provide information on the 

spatial distribution of SET stations and compare this with the 

amount and distribution of estuarine emergent marsh across 

the region (fig. 16). We also incorporated two risk factors 

into this analysis: hurricane return interval and storm surge 

footprint. These analyses will highlight geographical areas 

that are under-represented by SET stations and can be used to 

guide future installation and improve our assessment of coastal 

marsh resilience to the impact of climate change and stormrelated phenomena on coastal wetlands. 

Methods

Spatial Analysis 

The number of hexagons (each 4,000 ha or 40 km2 in 

area; Weist and others, 2016), amount of marsh area, number 

of marsh patches, dominant geomorphic settings, and number 

of SET stations per predefined subregion were determined. 

The spatial distribution and density of SET stations in the 

study area was summarized in ArcMap 10.1 to show the 

number of stations per subregion, number of marsh patches 

with stations present, number of stations per hexagon, and the 

number of stations with federally owned data, indicating there 

is a long-term commitment to data collection. The spatial distribution of estuarine emergent marsh was determined for each 

subregion as the total marsh area, number of marsh patches 

and broad geomorphic settings of marsh patches, total marsh 

area per hexagon, and the presence of publicly owned estuarine emergent marsh within each hexagon, indicating potential locations for future SET station installations. From these 

analyses we calculated the percent of hexagons containing 

SET stations, the density of stations per marsh area for each 

subregion expressed as the number of stations per 1,000 ha 

of marsh area, the percentage of marsh patches per subregion 

containing stations, and the broad geomorphic settings of station locations.
30 Hurricane Sandy Impacts on Coastal Wetland Resilience

Incorporating Risk—Data Sources and 

Application

There are a multitude of additional factors that could be 

considered when identifying spatial gaps in an opportunistic assemblage of stations. We identified two additional risk 

factors with data available for the entire study area: hurricane 

return interval and storm surge footprint. The return interval 

of hurricanes (100 years/number of hurricane strikes) was 

calculated for the coastal counties on the basis of data from the 

National Hurricane Center (NHC), which maintains a list of all 

direct and indirect strikes from all hurricane categories from 

1900–2009, and was last updated in February 2010 (National 

Oceanic and Atmospheric Administration, 2010). For this project, direct and indirect strikes of all hurricane categories were 

included in the number of hurricane strikes over the length of 

record. 

The potential storm surge footprint was acquired from the 

Sea, Lake, and Overland Surges from a Hurricane (SLOSH) 

model (Forbes and others, 2014) that is used by the National 

Weather Service and NHC to compute storm surge and create 

management and planning products based on hypothetical hurricane tracks. We used the potential storm surge footprints for 

the maximum of maximums (MOM) for hurricane categories 

1–5, which represent the worst case scenario based on model 

results from more than 10,000 simulated storms (Federal 

Emergency Management Agency, 2015b). See also Longenecker (2011). 

75° 70°

45°

40°

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ATLANTIC

OCEAN

ME

NH

VT

NY

MA

RI

CT

PA NJ

DE

WV MD

DC

VA

NC

Hectares estuarine emergent marsh

< 1

1–9.5

9.6–20.8

20.9–34.5

34.6–54.3

54.4–83.2

83.3–148.2

148.3–308.3

308.4–660.3

660.4–2,846.4

EXPLANATION

0 90 180 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 150 300 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Figure 16. Study region between Maine and Virginia (inclusive) indicating area of estuarine emergent marsh per hexagon (40 square 

kilometers or 4,000 hectares). Note the hexagon grid is restricted to areas where estuarine emergent marsh is present in the National 

Wetlands Inventory acquired in 2010.
Results 31

Results

Spatial Distribution of SET-MH Stations 

Spatial distribution of SET stations across the Atlantic 

coast from Virginia to Maine can be evaluated for the entire 

region or by subregion. SET stations are not evenly distributed 

across the region, as installations were based on agency and 

project priorities. We then calculated the percent of hexagons 

in each subregion that contain SET stations (table 13). With 

this approach, five of the subregions (Cape Cod-Casco Bay, 

Long Island, coastal New Jersey, Delaware Bay, and coastal 

Delmarva) are fairly evenly represented with 18–22 percent of 

hexagons containing some SET stations. However, southern 

New England and coastal Virginia have few hexagons with 

stations (approximately 9.5 percent), and coastal Maine, as 

well as both western and eastern Chesapeake Bay, are much 

less represented with less than 8 percent of the hexagons 

in those regions containing stations. SET stations are also 

unevenly distributed within each subregion (fig. 17). For 

example, most of the SET stations in the coastal Maine subregion are in the northern portion (fig. 2). 

Subregions are not equivalent with respect to marsh 

area, marsh patch size, and geomorphic settings. Therefore, 

we summarized the number and size of marsh patches per 

subregion and the density of SET stations relative to existing 

estuarine emergent marsh (table 14). Two of the four subregions with the greatest number of SET stations (coastal New 

Jersey=141 and eastern Chesapeake Bay=102) have large 

areas of marsh (>50,000 ha) and consequently low densities 

of stations per marsh area (2.8 and 1.51 stations per 1,000 ha 

of marsh, respectively; table 14). Coastal Maine, eastern 

Chesapeake Bay, and western Chesapeake Bay are underrepresented by percent of marsh patches with SET stations (less 

than 1 percent of marsh patches containing stations), and the 

density of SET stations was low in the southern portion of the 

region (fewer than 3 stations per 1,000 ha of marsh) and in 

coastal Maine (4.8 stations per 1,000 ha of marsh) compared 

to the midregion from Long Island to Cape Cod/Casco Bay 

(>9 stations per 1,000 ha of marsh; table 14). 

The percent of hexagons with SETs per subregion was 

not evenly distributed (χ2 =42.5, df=9, P<0.001), and the 

density of SETs (number of stations per 1,000 ha estuarine 

emergent marsh) was strongly clustered (Global Moran’s 

I=0.157, P<0.001), confirming that SET stations are not 

evenly distributed. 

Within each subregion, SET stations were generally clustered on the basis of Global Moran’s I, a measure of spatial 

autocorrelation, calculated for number of stations per 1,000 ha 

of estuarine emergent marsh in each hexagon (table 13). 

Southern New England and coastal New Jersey subregions 

were exceptions, in that distribution of SET station density 

was not significantly different from random (Global Moran’s 

I P-values>0.1). Each subregion also had at least one pair of 

adjacent hexagons that both contained some SET stations. 

Therefore, the overall minimum distance between hexagons 

with SET stations was 0 km. However, the mean minimum 

distance (or the mean distance to the nearest hexagon with 

Table 13. Summary of the spatial distribution of surface elevation table-marker horizon (SET-MH) stations, hexagons (with estuarine 

emergent marsh [E2EM]), hexagons (with E2EM marsh) with SET-MH stations, mean minimum distance between hexagons with SETs, 

and Global Moran’s I (measure of clustering) across 10 subregions between Maine and Virginia (inclusive).

[km2, square kilometer; m, meter; ha, hectare; <, less than]

Subregion

Number of 

SET-MH 

stations

Percent of 

SET-MH 

stations

Total number 

of hexagons 

(40 km2)

Number of 

hexagons 

with SETs

Percent of 

hexagons 

with SETs

Mean minimum 

distance (m) 

between hexagons 

with SETs

Global Moran’s I 

(for number of 

SETs/1,000 ha 

marsh)

Coastal Maine 31 3.2 208 8 3.8 3,039 0.074* 

Cape Cod, Casco Bay 189 19.6 113 25 22.1 271 0.215***

Southern New England 124 12.8 180 17 9.4 6,898 0.983

Long Island 105 10.9 107 23 21.5 1,415 0.150*

Coastal New Jersey 141 14.6 109 24 22.0 1,533 0.087

Delaware Bay 88 9.1 88 19 21.6 715 0.229***

Coastal Delmarva 90 9.3 93 17 18.3 1,323 0.202**

Eastern Chesapeake Bay 120 12.4 212 16 7.1 3,410 0.149***

Western Chesapeake Bay 68 7.0 311 7 2.3 7,362 0.058*

Coastal Virginia 9 0.9 21 2 9.5 0 0.165*

Across region 965 100 1,442 158 10.9 2,277 0.157***

*Significantly different from random (clustered) with P value <0.1.

**Significantly different from random (clustered) with P value <0.01.

***Significantly different from random (clustered) with P value <0.001.
32 Hurricane Sandy Impacts on Coastal Wetland Resilience

75° 70°

45°

40°

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ATLANTIC

OCEAN

ME

NH

VT

NY

MA

RI CT

PA NJ

DE

MD WV

DC

VA

NC

A

Number of SETs per hexagon

0

1–3

4–5

6–7

8–10

11–13

14–20

21–26

27–31

32–42

EXPLANATION

0 90 180 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 150 300 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ATLANTIC

OCEAN

ME

NH

VT

NY

MA

RI

CT

PA

WV

NJ

DE

MD

DC

VA

NC

B

Number of SETs per 1,000 hectares 

estuarine emergent marsh

0

< 2

2–10

10–50

50–100

100–500

> 500

EXPLANATION

75° 70°

45°

40°

0 90 180 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 150 300 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Figure 17. Study region between Maine and Virginia (inclusive) indicating A, number of surface elevation table-marker horizon 

(SET-MH) stations per hexagon (40 square kilometers or 4,000 hectares [ha]), and B, number of SETs per 1,000 ha estuarine emergent 

marsh (E2EM) in each hexagon. Note that the hexagon grid is restricted to areas where E2EM is present in the National Wetlands 

Inventory acquired in 2010.
Results 33

SET stations) ranged from 0 km in coastal Virginia (where 

there are only two hexagons with SET stations) to 7.4 km in 

western Chesapeake Bay (table 13). The maximum distance to 

the nearest hexagon with SET stations ranged from 0 (coastal 

Virginia) to 34 km (southern New England). 

SET Station Distribution Within a Subregion 

Within a subregion, additional detail can be incorporated 

to identify gaps in SET station coverage of geomorphic settings present. For example, we quantified the broad geomorphic settings present in the marsh patches of each subregion 

and then compared the broad geomorphic settings of the 

existing SET stations (table 15, figs. 18 and 19). This comparison is not relevant for subregions where there is only one 

broad geomorphic setting present, such as eastern and western 

Chesapeake Bay, and Delaware Bay. For several subregions, 

however, this comparison highlights existing gaps. In coastal 

Virginia, all stations are located in back-barrier lagoon settings, even though the percentage of total marsh area in this 

geomorphic setting is only 29.1 percent (table 15). In the Cape 

Cod/Casco Bay subregion, most stations (by count, number of 

marsh patches, and number of hexagons) are located in backbarrier lagoon settings, even though there is a mix of estuarine and back-barrier lagoon marsh patches in the subregion 

(26.2 percent and 73.8 percent of marsh area, respectively; 

table 15). The inverse is true in southern New England, where 

most stations (by count, number of marsh patches, and number 

of hexagons) are located in estuarine settings, even though 

there is a fairly even mix of estuarine and back-barrier lagoon 

marsh patches in the subregion (37.7 percent and 61.8 percent 

of marsh area, respectively; table 15).

At the subregion level, the amount of marsh area (fig. 16) 

can be used to identify areas/hexagons in which multiple SET 

stations would be recommended (a greater number of replicate 

stations for those hexagons with more marsh area). At a local 

level (within a hexagon), there are other details to be considered, including marsh patch ownership (for example, Federal 

lands, fig. 20A) and availability of observers. Additionally, the 

presence of publicly owned marsh (fig. 20B) could be used 

within an area identified as a spatial gap to highlight candidate hexagons for future installations. Additional information 

about SET station distribution within a marsh or study area is 

presented in the SET-MH protocol manual (Lynch and others, 

2015).

Incorporating Risk

This report includes spatial representation of two risk 

factors associated with hurricanes that could be considered 

when identifying spatial gaps in an opportunistic network: the 

return interval of hurricanes by county (fig. 21) and the potential storm surge footprint (fig. 22–25). These risk factors are 

shown in relation to the hexagon sampling grid with current 

SET locations highlighted. Note that the color coding of the 

storm strength categories is cumulative, where red indicates 

flooded by hurricanes of category 1 and above, orange by 

category 2 and above, yellow by category 3 and above, and 

green by category 4 and above. FEMA SLOSH modeling for 

category 5 hurricanes was not completed for areas north of 

North Carolina, and thus this category was not included in the 

analyses. Note that some hexagons appear to have no data for 

the hurricane return period and storm surge footprint. This is 

due to the fact that some marsh areas (and therefore hexagons) 

Table 14. Summary of the spatial distribution of estuarine emergent marsh patches (E2EM) and surface elevation table-marker horizon

(SET-MH) stations within marsh patches among 10 subregions between Maine and Virginia (inclusive).

[ha, hectare]

Subregion

Total area 

of estuarine 

emergent 

marsh (ha)

Percent 

of regional 

marsh area

Number 

of marsh 

patches

Average (range) 

marsh patch 

size (ha)

Number of 

marsh patches 

with SET-MH 

stations

Percent of 

marsh patches 

with SET-MH 

stations

Number of 

SET-MH 

stations per 

1,000 ha 

of marsh

Coastal Maine 6,234 2.0 1,441 4.33 (0.02–297.69) 12 0.83 4.81

Cape Cod, Casco Bay 20,368 6.4 536 38.00 (0.03–2,559.53) 21 3.92 9.28

Southern New England 9,782 3.1 1,166 8.47 (0.01–436.84) 19 1.63 12.68

Long Island 9,921 3.1 716 13.86 (0.02–373.47) 27 3.77 10.58

Coastal New Jersey 50,319 15.8 507 94.82 (0.01–8,815.53) 19 3.75 2.80

Delaware Bay 58,788 18.4 138 360.06 (0.05–16,937.31) 9 6.52 1.48

Coastal Delmarva 45,388 14.2 471 96.37 (0.04–7,688.65) 9 1.91 1.98

Eastern Chesapeake Bay 77,725 24.4 3,277 23.42 (0.03–27,778.83) 8 0.24 1.51

Western Chesapeake Bay 34,221 10.7 4,858 7.19 (0.03–1,752.32) 6 0.12 1.99

Coastal Virginia 5,939 1.9 56 102.71 (0.11–2,452.92) 2 3.57 1.52

Across region 318,685 100 13,166 24.14 (0.01–27,778.83) 132 1.00 3.03
34 Hurricane Sandy Impacts on Coastal Wetland Resilience

are not included in the terrestrial boundaries of counties and 

modeling efforts. It can be assumed that hexagons to the open 

water side of counties have the same hurricane return interval 

as the adjacent county and that these hexagons are flooded by 

all storm surges.

Risk of Hurricane Strikes and Storm Surge by 

Subregion

The subregion with the highest hurricane return interval 

(<10 years) is coastal Virginia, which represents a small portion of the entire study area (fig. 21). However, this subregion 

has among the lowest number of SET stations per 1,000 ha of 

marsh (1.52) in the entire study area (table 14). A much greater 

portion of the study area, in particular the central portion, 

experiences a 10–30 year return interval, including parts of 

western Chesapeake Bay, coastal Delmarva, Delaware Bay, 

coastal New Jersey, Long Island, southern New England, Cape 

Cod/Casco Bay, and coastal Maine (fig. 21). The Long Island, 

southern New England, Cape Cod/Casco Bay and coastal 

Maine subregions have the highest number of SET stations per 

1,000 ha of marsh in the study area (table 14). Yet the percent 

of marsh patches with SET stations is low in many of these 

subregions, especially western Chesapeake Bay, coastal Delmarva, southern New England, and coastal Maine (table 14), 

such that many areas of these subregions do not have any 

SET stations. A smaller portion of the study area that includes 

western Chesapeake Bay, coastal Delmarva, and coastal New 

Jersey experiences a 30–50 year return interval, and there are 

only about 2 SET stations per 1,000 ha of marsh in these subregions. The longest hurricane return intervals (50–100 years 

and >100 years) occur primarily in the eastern Chesapeake 

Bay, Cape Cod/Casco Bay, and coastal Maine subregions.

The predicted worst-case scenario storm surge footprints 

acquired from the SLOSH model for the MOM for storm 

categories 1–5 are presented in figure 22 for the entire study 

area and for the northern, central, and southern portions of the 

study area in figures 23–25. Storm surge footprints are most 

prevalent in the southern portion of the study area from coastal 

New Jersey to coastal Virginia (figs. 23–25), where all subregions are broadly impacted except for the western Chesapeake 

Bay. For the southern portion of the study area there are less 

than 2 SET stations per 1,000 ha of marsh, except for coastal 

New Jersey where there are 2.80 SET stations per 1,000 ha of 

marsh. A higher resolution view of storm surge footprints for 

each subregion is presented in figures 26–32. In the coastal 

Maine subregion, SET stations are not located within the 

storm surge footprints. In the remaining subregions, there is 

much stronger overlap between SET station locations and 

storm surge footprints, although there are no SET stations in 

some prominent storm surge footprints.

Discussion

During the past two decades, more than 1,100 SET stations have been installed in coastal marshes in the northeastern 

United States in 96 unique geographic settings. These stations 

were installed separately and independently by academic 

researchers; local, state, and Federal government agencies (for 

example, USGS, NOAA, National Park Service, U.S. Fish and 

Wildlife Service), and non-government organizations for the 

Table 15. Summary of the spatial distribution of surface elevation table-marker horizon (SET-MH) stations, estuarine emergent marsh 

patches (E2EM), and geomorphic settings among 10 subregions between Maine and Virginia (inclusive).

Subregion

Broad geomorphic 

settings of all 

marsh patches; 

percent by count 

and (area)

Broad geomorphic 

settings of SETs; 

percent by count

Broad geomorphic 

settings of SETs; 

percent of marsh 

patches with SETs

Broad geomorphic 

settings of SETs; 

percent of hexagons 

with SETs

Estuarine Back-barrier 

lagoon Estuarine Back-barrier lagoon Estuarine Back-barrier lagoon Estuarine Back-barrier lagoon

Coastal Maine 94.0 (90.1) 5.4 (9.8) 100 0 100 0 100 0

Cape Cod, Casco Bay 65.3 (26.2) 33.6 (73.8) 12.2 86.2 23.8 76.2 24.0 76.0

Southern New England 52.0 (37.7) 47.3 (61.8) 62.9 29.8 63.2 31.6 70.6 29.4

Long Island 5.5 (4.8) 94.4 (95.2) 14.3 85.7 14.8 85.2 17.4 95.7

Coastal New Jersey 32.7 (9.9) 67.3 (90.1) 17.0 83.0 21.1 78.9 16.7 83.3

Delaware Bay 100 (100) 0 (0) 100 0 100 0 100 0

Coastal Delmarva 0.4 (1.6) 99.6 (98.5) 0 100 0 100 0 100

Eastern Chesapeake Bay 100 (100) 0 (0) 100 0 100 0 100 0

Western Chesapeake Bay 100 (100) 0 (0) 100 0 100 0 100 0

Coastal Virginia 28.6 (70.9) 71.4 (29.1) 0 100 0 100 0 100

Across region 82.1 (61.4) 17.7 (38.6) 46.3 52.4 45.9 53.4 48.4 53.8
Discussion 35

purpose of investigating and monitoring elevation dynamics in 

coastal wetlands. The SET stations are located in wetlands that 

are best suited to address specific research questions or monitor the habitat sustainability of important biological resources 

at a specific wetland. Thus, this existing network of stations 

represents an opportunistic collection of sampling locations 

that are not a strategically deployed collection of stations 

designed to evaluate wetland elevation dynamics on broader 

regional scales or across a suite of geomorphic settings and 

environmental stressors. One purpose of this report was to 

provide a framework that can be used to develop a strategically designed SET sampling network for the northeastern 

region of the United States. The intended audience consists of 

policy makers, government resource management agencies, 

and SET practitioners. The goal is for this information to be 

used in decision-making regarding where new SET stations 

are installed in the northeastern United States, filling in gaps 

in the existing opportunistic network when possible, to better 

address priority concerns for the region. 

To this end, the report provides examples of how a 

regional inventory of SET station metadata can be used to 

identify limitations in an opportunistic network, which can 

inform decisions on future installations. For example, our 

evaluation of the northeastern region assemblage of stations 

reveals that the general geographic coverage of SET stations 

is limited, given the low percentage of marsh patches with 

stations, the low density of stations (number per 1,000 ha of 

marsh), and the clumped distribution of stations in 8 of the 

10 subregions. Furthermore, each rod SET station covers only 

~1.37 square meters of marsh surface area, leading to a recent 

75° 70°

45°

40°

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ATLANTIC

OCEAN

ME

NH

VT

NY

MA

RI

CT

PA

WV

NJ

DE

MD

DC

VA

NC

Dominant geomorphic setting

Estuarine

Back-barrier lagoon

Other

EXPLANATION

0 90 180 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 150 300 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Figure 18. Dominant broad geomorphic setting of marsh patches (estuarine emergent marsh; E2EM) in each hexagon (40 square 

kilometers) across the study region (Virginia to Maine, inclusive). Note that the hexagon grid is restricted to areas where E2EM is 

present in the National Wetlands Inventory acquired in 2010. Estuarine category includes estuarine embayment and estuarine brackish 

marsh. Back-barrier lagoon category includes back-barrier lagoon marsh and estuarine embayment systems within back-barrier 

lagoons. Other category includes open coast and tidal fresh marsh.
36 Hurricane Sandy Impacts on Coastal Wetland Resilience

74° 73° 72° 71° 70°

43°

42°

41°

Cape Cod/Casco Bay

Southern New England

Long Island

ATLANTIC

OCEAN

RI

MA

CT

NY

VT NH

ME

NJ

A

Percent estuarine marsh by area

0% 1%–25% 26%–50% 51%–75% 76%–100%

EXPLANATION

0 30 60 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 50 100 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Cape Cod/Casco Bay

Southern New England

Long Island

ATLANTIC

OCEAN

MA

VT NH

ME

NY

CT

RI

NJ

B 74° 73° 72° 71° 70°

43°

42°

41°

Percent back-barrier lagoon (by area)

0% 1%–25% 26%–50% 51%–75% 76%–100%

EXPLANATION

0 30 60 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 50 100 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Figure 19. Percent of estuarine emergent marsh patch (E2EM) area by broad geomorphic settings in each hexagon (40 square 

kilometers) across several subregions with mixed geomorphic settings (Long Island, southern New England, and Cape Cod/Casco Bay), 

with A, percent estuarine marsh, and B, percent back-barrier lagoon. Note that the hexagon grid is restricted to areas where E2EM is 

present in the National Wetlands Inventory acquired in 2010. Estuarine category includes estuarine embayment and estuarine brackish 

marsh. Back-barrier lagoon category includes back-barrier lagoon marsh and estuarine embayment systems within back-barrier 

lagoons.
Discussion 37

75° 70°

45°

40°

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ME

NH

VT

NY

MA

RI CT

PA NJ

MD

DC

VA

NC

WV

DE ATLANTIC

OCEAN

A

Number of Federally owned 

surface elevation tables

0

1–3

4–5

6–7

8–10

11–13

14–20

21–26

27–31

32–42

EXPLANATION

0 90 180 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 150 300 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

75° 70°

45°

40°

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ME

NH

VT

NY

MA

RI CT

PA NJ

MD

DC

VA

NC

WV

ATLANTIC

OCEAN

DE

B

Hexagon sampling grid

Hexigons with publicly owned marsh

EXPLANATION

0 90 180 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 150 300 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Figure 20. Study region between Maine and Virginia (inclusive) indicating A, the number of surface elevation table-marker horizon 

(SET-MH) stations owned by Federal agencies per hexagon (40 square kilometers), 664 SETs in 107 hexagons; and B, hexagons with 

publicly owned marsh (by states, National Park Service, or U.S. Fish and Wildlife Service). Note that the hexagon grid is restricted to 

areas where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010.
38 Hurricane Sandy Impacts on Coastal Wetland Resilience

innovation to expand wetland elevation measures across 1 ha 

of marsh surface from an SET station using a level (Cain and 

Hensel, 2017). In addition, coverage of the two dominant geomorphic settings in a subregion is often skewed to one of the 

two settings, and the distribution of stations in wetlands with a 

high probability of hurricane strikes and storm surge impacts 

is often limited and uneven. These analyses can be used to 

address priority regional concerns such as a broader geographical understanding of the vulnerability of coastal marshes 

in the region to relative sea-level rise, including a comparison 

of geomorphic settings, and the impacts of storms on wetland 

resilience. Such a strategic network can provide data to managers and policymakers that better inform the development of 

management and adaptation plans for coastal resources in the 

region. 

The priority concerns for the northeastern region will 

have to be developed by the target audience of this report, 

namely, the regional policymakers and resource managers 

charged with maintaining these critical biological resources. 

During planning for a strategic distribution of SET stations, 

there are other issues to be addressed before the plan can be 

implemented, specifically, financial and infrastructural support. Development of a regional monitoring network requires 

not only financial investment in the SET-MH equipment but 

also in the personnel to install the stations and collect and 

manage the data over the long-term (Webb and others, 2013). 

This typically requires institutional commitment and support; 

see for an example the Louisiana Coast-wide Reference Monitoring System (https://www.lacoast.gov/crms/Home.aspx). At 

the local or subregion scale, SET stations can be strategically 

installed in locations and settings gradually over time, and for 

a lower initial investment, to fill in the existing gaps in the 

opportunistic network. 

Finally, the analyses of regional storm impacts were 

limited by the exclusion of a majority of stations where SET 

data did not meet the criteria needed for the analyses. There 

75° 70°

45°

40°

Western Chesapeake Bay

Coastal Maine

Eastern Chesapeake Bay

Long Island

Delaware Bay

Coastal New Jersey

Coastal Delmarva

Southern New England

Cape Cod/Casco Bay

Coastal Virginia

ME

NH

VT

NY

MA

CT

PA NJ

WV

DE

MD

DC

VA

NC

RI

EXPLANATION

Surface elevation tables

Sampling grid

Hurricane Return Period

< 10 years

10–30 years

30–50 years

50–100 years

> 100 years

Hexagons

0 50 100 MILES

Map image is the intellectual property of Esri and is used herein under license. 0 100 200 KILOMETERS

Copyright © 2019 Esri and its licensors. All rights reserved.

Figure 21. Hurricane return period (based on National Hurricane Center hurricane strike dataset from 1900–2009 for U.S. coastal 

counties) for the study region (Virginia to Maine, inclusive) with hexagon (40 square kilometers) sampling grid and hexagons with 

surface elevation table-marker horizon (SET-MH) stations indicated. Note that the hexagon grid is restricted to areas where estuarine 

emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area along open water that is 

outside of terrestrial county boundaries.
Discussion 39

are several steps individual data collectors can take to improve 

the quality of their SET-MH data and its potential for inclusion 

in future regional data analyses. First, collect data on a regular 

multi-seasonal basis to develop long-term data records. The 

single largest reason for data being excluded from our analysis 

was that data records were less than 3 years duration, largely 

as a result of stations being installed less than 3 years prior to 

the storm. Data from these stations will be available for use 

in future regional assessments so long as regular data collection continues. Furthermore, data collection should occur in 

multiple seasons to allow better comparisons to poststorm 

readings (table 3) and should be conducted before and after 

severe storm events. Other data quality factors to consider 

include diligent quality assessment/quality control checks to 

minimize data processing time, storing the data in an R-user 

friendly format, conducting routine elevation surveys to certify the stability of the SET benchmarks, and where regional 

networks have been established, standardizing data collection 

of potential covariates (for example, wetland elevation within 

the tidal frame) by all data holders in the region.

75° 70°

45°

40°

Coastal Maine

Cape Cod/Casco Bay

Southern New England

Long Island

Coastal New Jersey

Delaware Bay

Coastal Delmarva

Eastern Chesapeake Bay

Western Chesapeake Bay

Coastal Virginia

ME

NH

VT

NY

PA NJ

DE

MD

DC

VA

NC

MA

CT RI

WV

ATLANTIC

OCEAN

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 150 300 KILOMETERS

0 90 180 MILES

Map image is the intellectual property of Esri and is used herein under license. 

Copyright © 2019 Esri and its licensors. All rights reserved.

Figure 22. Predicted worst-case scenario storm surge footprints by hurricane storm strength, from the Federal Emergency 

Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges from Hurricanes) model maximum of 

maximums (MOMs) for the study region (Virginia to Maine, inclusive) with hexagon (40 square kilometers) sampling grid and hexagons 

with surface elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded by hurricanes 

of category 1 and above, orange by category 2 and above, yellow by category 3 and above, and green by category 4 and above. FEMA 

SLOSH modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is restricted to 

areas where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area 

along open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
40 Hurricane Sandy Impacts on Coastal Wetland Resilience

71° 70° 69° 68° 67°

46°

45°

44°

43°

42°

41°

Coastal Maine

Cape Cod/Casco Bay

ME

NH

MA

RI

ATLANTIC

OCEAN

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 75 150 KILOMETERS

0 25 50 75 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 23. Northern portion of study area predicted worst-case scenario storm surge footprints by hurricane storm strength, from the 

Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges from Hurricanes) 

model maximum of maximums (MOMs) for Cape Cod/Casco Bay and coastal Maine subregions with hexagon (40 square kilometers) 

sampling grid and hexagons with surface elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where 

red is flooded by hurricanes of category 1 and above, orange by category 2 and above, yellow by category 3 and above, and green by 

category 4 and above. FEMA SLOSH modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that the 

hexagon grid is restricted to areas where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this 

area includes marsh area along open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by 

all categories.
Discussion 41

74° 73° 72° 71° 70°

44°

43°

42°

41°

40°

39°

Long Island

Coastal New Jersey

Southern New England

Cape Cod/Casco Bay

ME

VT NH

NY

MA

CT RI

ATLANTIC

OCEAN

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 75 150 KILOMETERS

0 25 50 75 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 24. Central portion of study area predicted worst-case scenario storm surge footprints by hurricane storm strength, from the 

Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges from Hurricanes) 

model maximum of maximums (MOMs) for Cape Cod/Casco Bay, southern New England, Long Island, and part of coastal New Jersey 

subregions with hexagon (40 square kilometers) sampling grid and hexagons with surface elevation table-marker horizon (SET-MH)

stations indicated. Color coding is cumulative, where red is flooded by hurricanes of category 1 and above, orange by category 2 

and above, yellow by category 3 and above, and green by category 4 and above. FEMA SLOSH modeling for category 5 hurricanes 

not completed for areas north of North Carolina. Note that the hexagon grid is restricted to areas where estuarine emergent marsh 

is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area along open water that is outside of 

terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
42 Hurricane Sandy Impacts on Coastal Wetland Resilience

77° 76° 75° 74° 73°

41°

40°

39°

38°

37°

36°

Long Island

Coastal New Jersey

Delaware Bay

Coastal

Delmarva

Eastern

Chesapeake Bay

Western

Chesapeake Bay

Coastal Virginia

ATLANTIC OCEAN

NY CT

PA NJ

MD

DC

VA

NC

DE

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 75

0 25 50 75

150 KILOMETERS

MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 25. Southern portion of study area predicted worst-case scenario storm surge footprints by hurricane storm strength, from the 

Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges from Hurricanes) 

model maximum of maximums (MOMs) for coastal Virginia, eastern and western Chesapeake Bay, coastal Delmarva, Delaware Bay, and 

coastal New Jersey subregions with hexagon (40 square kilometers) sampling grid and hexagons with surface elevation table-marker 

horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded by hurricanes of category 1 and above, orange 

by category 2 and above, yellow by category 3 and above, and green by category 4 and above. FEMA SLOSH modeling for category 5 

hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is restricted to areas where estuarine emergent 

marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area along open water that is outside of 

terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
Discussion 43

70° 69° 68° 67°

45°

44°

Coastal Maine

ATLANTIC OCEAN

MAINE

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 40

40

80

20

KILOMETERS

0 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 26. Coastal Maine subregion predicted worst-case scenario storm surge footprints by hurricane storm strength, from the 

Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges from Hurricanes) 

model maximum of maximums (MOMs) with hexagon (40 square kilometers) sampling grid and hexagons with surface elevation 

table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded by hurricanes of category 1 and 

above, orange by category 2 and above, yellow by category 3 and above, and green by category 4 and above. FEMA SLOSH modeling 

for category 5 hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is restricted to areas where the 

estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area along open 

water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
44 Hurricane Sandy Impacts on Coastal Wetland Resilience

71° 70° 69°

43°

42°

Cape Cod/Casco Bay

MA

NH

ME

RI

ATLANTIC OCEAN

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 40 80 KILOMETERS

0 20 40 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 27. Cape Cod/Casco Bay subregion (and neighboring areas) predicted worst-case scenario storm surge footprints by hurricane 

storm strength, from the Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland 

Surges from Hurricanes) model maximum of maximums (MOMs) with hexagon (40 square kilometers) sampling grid and hexagons with 

surface elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded by hurricanes of 

category 1 and above, orange by category 2 and above, yellow by category 3 and above, and green by category 4 and above. FEMA 

SLOSH modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is restricted to 

areas where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area 

along open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
Discussion 45

74° 73° 72° 71° 70°

42°

41°

40°

Long Island

Southern New England

ATLANTIC OCEAN

MA

CT RI

NY

NJ

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 50 100 KILOMETERS

0 30 60 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 28. Southern New England subregion (and neighboring areas) predicted worst-case scenario storm surge footprints by 

hurricane storm strength, from the Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and 

Overland Surges from Hurricanes) model maximum of maximums (MOMs) with hexagon (40 square kilometers) sampling grid and 

hexagons with surface elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded 

by hurricanes of category 1 and above, orange by category 2 and above, yellow by category 3 and above, and green by category 4 and 

above. FEMA SLOSH modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is 

restricted to areas where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes 

marsh area along open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
46 Hurricane Sandy Impacts on Coastal Wetland Resilience

74° 73° 72°

41°

40°

Long Island

ATLANTIC OCEAN

CT

NY

NJ Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 30 60 KILOMETERS

0 15 30 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 29. Long Island subregion (and neighboring areas) predicted worst-case scenario storm surge footprints by hurricane storm 

strength, from the Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges 

from Hurricanes) model maximum of maximums (MOMs) with hexagon (40 square kilometers) sampling grid and hexagons with surface 

elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded by hurricanes of category 

1 and above, orange by category 2 and above, yellow by category 3 and above, and green by category 4 and above. FEMA SLOSH 

modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is restricted to areas 

where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area along 

open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
Discussion 47

75° 74° 73°

41°

40°

39°

Coastal New Jersey

NJ

PA

DE

MD

NY

ATLANTIC OCEAN

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 30 60 KILOMETERS

0 15 30 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 30. Coastal New Jersey subregion (and neighboring areas) predicted worst-case scenario storm surge footprints by hurricane 

storm strength, from the Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland 

Surges from Hurricanes) model maximum of maximums (MOMs) with hexagon (40 square kilometers) sampling grid and hexagons with 

surface elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded by hurricanes of 

category 1 and above, orange by category 2 and above, yellow by category 3 and above, and green by category 4 and above. FEMA 

SLOSH modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is restricted to 

areas where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area 

along open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
48 Hurricane Sandy Impacts on Coastal Wetland Resilience

PA

DE

75° 74°

40°

39°

Delaware Bay

ATLANTIC

NJ OCEAN

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 20 40 KILOMETERS

0 10 20 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 31. Delaware Bay subregion (and neighboring areas) predicted worst-case scenario storm surge footprints by hurricane storm 

strength, from the Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas SLOSH (Sea, Lake, and Overland Surges 

from Hurricanes) model maximum of maximums (MOMs) with hexagon (40 square kilometers) sampling grid and hexagons with surface 

elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where red is flooded by hurricanes of category 

1 and above, orange by category 2 and above, yellow by category 3 and above, and green by category 4 and above. FEMA SLOSH 

modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that the hexagon grid is restricted to areas 

where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 2010; this area includes marsh area along 

open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be flooded by all categories.
Discussion 49

77° 76° 75°

39°

38°

37°

Coastal

Virginia

Western 

Chesapeake Bay

Eastern 

Chesapeake Bay

ATLANTIC

OCEAN

NJ

DE

MD

VA

DC

NC

Surface elevation tables

Sampling grid

Federal Emergency Management Agency

Coastal Flood Loss Atlas maximum of maximums

storm surge footprints by hurricane strength

Category 1

Category 2

Category 3

Category 4

Category 5

Hexagons

EXPLANATION

0 40 80 KILOMETERS

0 20 40 MILES

Map image is the intellectual property of Esri and is used 

herein under license. Copyright © 2019 Esri and 

its licensors. All rights reserved.

Figure 32. Coastal Virginia and eastern/western Chesapeake Bay subregions (and neighboring areas) predicted worst-case scenario 

storm surge footprints by hurricane storm strength, from the Federal Emergency Management Agency (FEMA) Coastal Flood Loss Atlas 

SLOSH (Sea, Lake, and Overland Surges from Hurricanes) model maximum of maximums (MOMs) with hexagon (40 square kilometers) 

sampling grid and hexagons with surface elevation table-marker horizon (SET-MH) stations indicated. Color coding is cumulative, where 

red is flooded by hurricanes of category 1 and above, orange by category 2 and above, yellow by category 3 and above, and green by 

category 4 and above. FEMA SLOSH modeling for category 5 hurricanes not completed for areas north of North Carolina. Note that 

the hexagon grid is restricted to the area where estuarine emergent marsh is present in the National Wetlands Inventory acquired in 

2010; this area includes marsh area along open water that is outside of terrestrial FEMA modeling boundaries, which is assumed to be 

flooded by all categories.
50 Hurricane Sandy Impacts on Coastal Wetland Resilience

Conclusions

Using data collected from an assemblage of SET-MH stations spread across the northeast U.S. coastline from Virginia 

to Maine, we evaluated the effects of Hurricane Sandy on 

marsh elevation trends by comparing prestorm and poststorm 

data. We hypothesized that the effect of Hurricane Sandy on 

marsh elevation trends would differ by position relative to 

landfall (right or left) and distance from landfall in southern 

New Jersey, as both these variables influence the presence or 

absence of storm surge as a result of the physical characteristics of tropical cyclones (fig. 4). As expected, storm surge 

strength and extent were greater to the right of landfall in the 

northeast quadrant of the storm, compared to the left of landfall. Thus, the interaction of position relative to landfall with 

distance from landfall significantly influenced marsh elevation 

trends (fig. 15), indicating significant spatial variation in Hurricane Sandy effects and potential resilience to future storms 

across the region. 

The majority of SET stations had a poststorm deviation 

from the expected elevation change trend that was within a 

range commonly observed in prestorm data (<5 mm). For the 

SET stations where deviation from the expected trend was 

greater than 5 mm, position relative to landfall had a significant influence. More marshes located to the left of landfall, 

where storm surge was less extensive and less deep, had a 

significant and greater deviation in their elevation trend that 

was more likely to be positive (elevation gain), compared to 

marshes located to the right of landfall where the surge was 

more extensive and deeper. Fewer marshes located to the 

right of landfall had a significant deviation in their elevation 

trend, and that trend was more likely to be negative (elevation loss). In addition, positive trends (elevation gain) were 

lower compared to left of landfall. The cause for this finding 

apparently is directly related to storm surge impacts on marsh 

sediment deposition. Other researchers (Gardner and others, 

1991, 1992; Quirk, 2016) have shown that 3- to 4-m-deep 

storm surge results in sediment deposition in habitats inland of 

coastal marshes but less so in the marshes themselves, and the 

deep surge water apparently protects the marsh surface from 

erosive forces related to currents and waves that would affect 

more shallowly flooded surfaces. Substrate compaction by 

the storm surge overburden may have contributed to elevation 

loss in marshes located to the right of landfall, as has occurred 

in other marshes during previous storms (Cahoon, 2006), but 

this was not measured because marker horizon data were not 

available from all sites. In contrast, wind-driven flooding of 

sediment laden water pushed into the headwaters of rivers 

and small bays on the east shore of Chesapeake Bay associated with an ~1-m surge resulted in more prevalent sediment 

deposition and elevation gain on the marsh surfaces there. 

Consequently, as a result of Hurricane Sandy, more marshes 

located left of landfall (for example, Chesapeake Bay region) 

gained more elevation capital (Cahoon and Guntenspergen, 

2010), and hence resilience, than marshes located to the right 

of landfall.

Even though marsh settings were separated geographically with more back-barrier lagoon settings right of landfall 

and estuarine marsh left of landfall, estuarine marsh setting did 

not influence marsh elevation trends or the presence/absence 

of storm surge (fig. 15). The spatial characteristics of the storm 

apparently overwhelmed any influence that geomorphic setting 

had on storm impact. 

Lastly, we developed a framework that will enable 

conversion of the opportunistic assemblage of 965 stations in 

the northeast United States into a strategic monitoring network designed to address specific climate change impacts and 

related phenomena identified by land managers and stakeholders. To accomplish this, we evaluated the spatial distribution 

and density of SET-MH stations in relation to geographic coverage, marsh setting, availability of public land, and historical 

storm surge footprints and hurricane return intervals in order 

to identify gaps in our understanding of risk and our ability to 

assess it. The analyses revealed that the general geographic 

coverage of SET stations is limited, given the low percentage of marsh patches with stations, low density of stations, 

and the clumped distribution of stations in 8 of the 10 predefined subregions. Also, spatial coverage of the two dominant 

geomorphic settings in a subregion is often skewed to one of 

the settings, and the distribution of stations in wetlands with a 

high probability of hurricane strikes and storm surge impacts 

is often limited and uneven. These findings can be used by 

managers and planners to inform the creation of a strategic 

monitoring network by providing a guide to future SET station installations at regional and local scales, the results from 

which can inform management and adaptation efforts for 

coastal resources in the region. These management concerns 

will have to be identified and prioritized by the target audience of this report, the local and regional policymakers and 

resource managers charged with maintaining critical biological 

resources. Final plan designs will have to incorporate financial 

and infrastructural support required to collect and manage the 

data over the long term. 

References Cited

American Littoral Society, 2012, Assessing the impacts of 

Hurricane Sandy on coastal habitats: Final report to The 

National Fish and Wildlife Foundation, December 17, 2012, 

p. 58, accessed January 23, 2013, at https://www.nfwf.

org/hurricanesandy/Documents/Hurricane-Sandy-CoastalHabitats.pdf.

Bender, M.A., Knutson, T.R., Tuleya, R.E., Sirutis, J.J., 

Vecchi, G.A., Garner, S.T., and Held, I.M., 2010, Modeled impact of anthropogenic warming on the frequency of 

intense Atlantic hurricanes: Science, v. 327, p. 454–458.

Bivand, R., Pebesma, E., and Bubio, V.G., 2013, Applied 

spatial data analysis with R (2d ed.): New York, Springer 

Press, 405 p.
References Cited 51

Bivand, R., and Piras, G., 2015, Comparing implementations 

of estimation methods for spatial econometrics: Journal 

of Statistical Software, v. 63, no. 18, p. 1–36, accessed 

November 2016 at http://www.jstatsoft.org/v63/i18/.

Blake, E.S., Kimberlain, T.B., Berg, R.J., Cangialosi, J.P., and 

Beven, J.L., II, 2013, Tropical cyclone report, Hurricane 

Sandy (AL182012) 22–29 October 2012: National Oceanic and Atmospheric Administration, National Hurricane 

Center, 157 p.

Blum, L., Christian, R., Brinson, M., and Willis, P., 2017, 

Surface elevation data for the Upper Phillips Creek Marsh 

at the Virginia Coast Reserve, 1998: Virginia Coast Reserve 

Long-Term Ecological Research Project Data Publication 

knb-lter-vcr.148.23, accessed April 2014 at https://doi.

org/10.6073/pasta/427e78ec51022e1ab667c6ce206b9025. 

Booth, J.F., Rieder, H.E., and Kushnir, Y., 2016, Comparing hurricane and extratropical storm surge for 

the Mid-Atlantic and Northeast Coast of the United 

States for 1979–2013: Environmental Research Letters, v. 11, December 2016 at https://iopscience.iop.org/

article/10.1088/1748-9326/11/9/094004/meta.

Boumans, R.M.J., and Day, J.W., Jr., 1993, High precision 

measurements of sediment elevation in shallow coastal 

areas using a sedimentation-erosion table: Estuaries, v. 16, 

p. 375–380.

Bourke, P. [2015], Pointline: Paul Bourke web page, accessed 

September 2015 at http://paulbourke.net/geometry/pointlineplane/pointline.r.

Burnham, K.P., and Anderson, D.R., 2002, Model selection 

and multimodel inference—A practical information theoretic approach (2d ed.): New York, Springer, 488 p.

Cahoon, D.R., 2006, A review of major storm impacts on 

coastal wetland elevations: Estuaries and Coasts, v. 29, 

no. 6, p. 889–898.

Cahoon, D.R., 2015, Estimating relative sea-level rise and 

submergence potential at a coastal wetland: Estuaries and 

Coasts, v. 38, p. 1077–1084.

Cahoon, D.R., and Guntenspergen, G.R., 2010, Climate 

change, sea-level rise, and coastal wetlands: National Wetlands Newsletter, v. 32, no. 1, p. 8–12.

Cahoon, D.R., Hensel, P., Rybczyk, J., McKee, K.L., Proffitt, 

C.E., and Perez, B.C., 2003, Mass tree mortality leads to 

mangrove peat collapse at Bay Islands, Honduras after Hurricane Mitch: Journal of Ecology, v. 91, p. 1093–1105.

Cahoon, D.R., Lynch, J.C., Hensel, P., Boumans, R., Perez, 

B.C., Segura, B., and Day, J.W., 2002a, High-precision 

measurements of wetland sediment elevation—I. Recent 

improvements to the sedimentation-erosion table: Journal of 

Sedimentary Research, v. 72, no. 5, p. 730–733.

Cahoon, D.R., Lynch, J.C., Perez, B.C., Segura, B., Holland, 

R.D., Stelly, C., Stephenson, G., and Hensel, P., 2002b, 

High-precision measurements of wetland sediment elevation—II. The rod surface elevation table: Journal of Sedimentary Research, v. 72, no. 5, p. 734–739.

Cahoon, D.R., Lynch, J.C., Roman, C., Schmit, J.P., and 

Skidds, D., 2019, Evaluating the relationship among wetland vertical development, elevation capital, sea-level rise 

and tidal marsh sustainability: Estuaries and Coasts, v. 42, 

p. 1–15.

Cahoon, D.R., Reed, D.J., and Day, J.W., 1995a, Estimating shallow subsidence in microtidal salt marshes of the 

southeastern United States—Kaye and Barghoorn revisited: 

Marine Geology, v. 128, no. 1–2, p. 1–9.

Cahoon, D.R., Reed, D.J., Day, J.W., Steyer, G.D., Boumans, 

R.M., Lynch, J.C., McNally, D., and Latif, N., 1995b, The 

influence of Hurricane Andrew on sediment distribution in 

Louisiana coastal marshes: Journal of Coastal Research, 

SI 21, p. 280–294.

Cahoon, D.R., Reed, D.J., Kolker, A., Brinson, M.M., Stevenson, J.C., Riggs, S., Christian, R., Reyes, E., Voss, C., 

and Kunz, D., 2009, Coastal wetland sustainability, chap. 

4 of Titus, J.G. (coordinating lead author), Anderson, K.E., 

Cahoon, D.R., Gill, S., Thieler, E.R., and Williams, S.J., 

(lead authors), Coastal sensitivity to sea-level rise—A focus 

on the mid-Atlantic region: U.S. Environmental Protection 

Agency, p. 57–72. 

Cain, M.R., and Hensel, P.F., 2017, Wetland elevations at subcentimeter precision—Exploring the use of digital barcode 

leveling for elevation monitoring: Estuaries and Coasts, 

v. 41, no. 2, p. 582–591.

Callaway, J.C., Cahoon, D.R., and Lynch, J.C., 2013, The surface elevation table—Marker horizon method for measuring wetland accretion and elevation dynamics, chap. 46 of

DeLaune, R.D., Reddy, K.R., Richardson, C.J., and Megonigal, J.P., eds., Methods in biogeochemistry of wetlands: 

Madison, Wis., Soil Science Society of America, SSSA 

Book Series 10, p. 901–918.

Conway, C.J., and Droege, S., 2006, A unified strategy for 

monitoring changes in abundance of birds associated with 

North American tidal marshes, in Greenberg, R., Maldonado, J.E., Droege, S., and McDonald, M.V., eds., Terrestrial vertebrates of tidal marshes—Evolution, ecology, and 

conservation: Studies in Avian Biology, no. 32, p. 282–297.

Davis, R.E, and Dolan, R., 1993, Nor’easters: American Scientist, v. 81, p. 428–439.
52 Hurricane Sandy Impacts on Coastal Wetland Resilience

Dennison, W.C., Saxby, T., and Walsh, B.M., eds., 2012, 

Responding to major storm impacts—Chesapeake Bay 

and Delmarva Coastal Bays: Integration & Application 

Network, University of Maryland Center for Environmental Science, 16 p., accessed January 23, 2013, at https://

mdcoastalbays.org/files/pdfs_pdf/HurricaneSandyAssessment-Final-1.pdf.

Dowle, M., Srinivasan, A., Short, T., and Lianoglou, S., with 

contributions from Saporta, R., and Antonyan, E., 2015, 

data.table—Extension of data.frame (v. 1.9.6): R package, accessed March 2017 at https://CRAN.R-project.org/

package=data.table.

Emanuel, K.A., 2013, Downscaling CMIP5 climate models 

show increased tropical cyclone activity over the 21st century: Proceedings of the National Academy of Sciences of 

the United States of America, v. 110, p. 12219–12224.

Ezer, T., and Atkinson, L.P., 2014, Accelerated flooding along 

the U.S. east coast—On the impact of sea-level rise, tides, 

storms, the Gulf Stream, and the North Atlantic Oscillations: Earth’s Future, v. 2, p. 362–382.

Federal Emergency Management Agency [2015a], FEMA 

Modeling Task Force (MOTF) Hurricane Sandy impact 

analysis: Federal Emergency Management Agency web 

page, accessed February 29, 2015, at http://www.arcgis.

com/home/item.html?id=307dd522499d4a44a33d7296a5d

a5ea0.

Federal Emergency Management Agency, 2015b, FEMA 

Coastal Flood Loss Atlas (v. 3.01): Federal Emergency 

Management Agency, accessed July 29, 2015, at https://

fema.maps.arcgis.com/home/item.html?id=b4ae0b4278944

7b18c4b919682b848ad.

Folke, C., Carpenter, S., Walker, B., Scheffer, M., Elmqvist, 

T., Gunderson, L., and Holling, C.S., 2004, Regime shifts, 

resilience and biodiversity in ecosystem management: 

Annual Review of Ecology, Evolution, and Systematics, 

v. 35, p. 557–581.

Forbes, C., Rhome, J., Mattocks, C., and Taylor, A., 2014, Predicting the storm surge threat of Hurricane Sandy with the 

National Weather Service SLOSH Model: Journal of Marine 

Science and Engineering, v. 2, p. 437–476.

Fox, J., and Weisberg, S., 2011, An R companion to applied 

regression (2d ed.): Thousand Oaks, Calif., Sage Publications, 449 p. 

Gardner, L.R., Michener, W.K., Kjerfve, B., and Karinshak, 

D.A., 1991, The geomorphic effects of Hurricane Hugo 

on an undeveloped coastal landscape at North Inlet, South 

Carolina: Journal of Coastal Research, special issue 8, 

p. 181–186.

Gardner, L.R., Michener, W.K., Williams, T.M., Blood, E.R., 

Kjerfve, B., Smock, L.A., Lipscomb, D.J., and Gresham, C., 

1992, Disturbance effects of Hurricane Hugo on a pristine 

coastal landscape—North Inlet, South Carolina, USA: Netherlands Journal of Sea Research, v. 30, p. 249–263.

Grace, J.B., Schoolmaster, Jr., D.R., Guntenspergen, G.R., 

Little, A.M., Mitchell, B.R., Miller, K.M., and Schweiger, 

E.W., 2012, Guidelines for a graph-theoretic implementation of structural equation modeling: Ecosphere, v. 3, no. 8, 

44 p., accessed August 2016 at http://dx.doi.org/10.1890/

ES12-00048.1.

Grubel, C., Waldman, J., Lodge, J., and Suszkowski, D., 2012, 

Rapid assessment of habitat and wildlife losses from Hurricane Sandy in the Hudson Raritan Estuary: Report by the 

Hudson River Foundation to The National Fish and Wildlife 

Foundation, December 12, 2012, 22 p. accessed January 23, 

2013, at http://www.hudsonriver.org/download/HRF%20

RAP%20Final%20Report%20-%20Sent%2012-21-12.pdf. 

Hall, T.M., and Sobel, A.H., 2013, On the impact angle of 

Hurricane Sandy’s New Jersey landfall: Geophysical 

Research Letters, v. 40, p. 2312–2315.

Hauser, S., Meixler, M.S., and Laba, M., 2015, Quantification of impacts and ecosystem services loss in New Jersey 

coastal wetlands due to Hurricane Sandy storm surge: Wetlands v. 35, p. 1137–1148.

Horton, R.M., Gornitz, V., Bader, D.A., Ruane, A.C., Goldberg, R., and Rosenzweig, C., 2011, Climate hazard assessment for stakeholder adaptation planning in New York City: 

Journal of Applied Meteorology and Climatology, v. 50, 

p. 2247–2266.

Horton, R., Yohe, G., Easterling, W., Kates, R., Ruth, M., 

Sussman, E., Whelchel, A., Wolfe, D., and Lipschultz, F., 

2014, Chapter 16—Northeast, in Melillo, J.M., Richmond, 

T.C., and Yohe, G.W., eds., Climate change impacts in the 

United States—The third National climate assessment: U.S. 

Global Change Research Program, p. 371–395, accessed 

March 2015 at http://nca2014.globalchange.gov

Kemp, A.C., Hill, T.D., Vane, C.H., Cahil, N., Orton, P.M., 

Talke, S.A., Parnell, A.C., Sanborn, K., and Hartig, E.K., 

2017, Relative sea-level trends in New York City during the 

past 1500 years: The Holocene, v. 27, no. 8, p. 1169–1186.

Kemp, A.C., and Horton, B.P., 2013, Contribution of relative sea-level rise to historical hurricane flooding in New 

York City: Journal of Quaternary Science, v. 28, no. 6, 

p. 537–541.

Knutson, T.R., McBride, J.L., Chan, J., Emanuel, K., Holland, 

G., Landsea, C., Held, I., Kossin, J.P., Srivastava, A.K., 

and Sugi, M., 2010, Tropical cyclones and climate change: 

Nature Geoscience, v. 3, p. 157–163.
References Cited 53

Leonardi, N., Carnacina, I., Donatelli, C., Ganju, N., Plater, 

A., Schuerch, M., and Temmerman, S., 2018, Dynamic 

interactions between coastal storms and salt marshes—A 

review: Geomorphology, v. 301, p. 92–107.

Lin, N., Kopp, R.E., Horton, B.P., and Donnelly, J.P., 2016, 

Hurricane Sandy’s flood frequency increasing from year 

1800 to 2100: Proceedings of the National Academy of Sciences, v. 113, no. 43, p. 12071–12075.

Little, C.M., Horton, R.M., Kopp, R.E., Oppenheimer, M., 

Vecchi, G.A., and Villarini, G., 2015, Joint projections of 

US East coast sea level and storm surge: Nature Climate 

Change, v. 5, p. 1114–1120.

Longenecker, III, H.E.G., 2011, Development and applications of the FEMA Region IV Coastal Flood Loss Atlas: 

ASCE Solutions to Coastal Disasters Conference 2011, 

June 26–29, 2011, Anchorage, Alaska, p. 650–665. 

Longenecker, R., Bowman, J., Olsen, B., Roberts, S., Elphick, 

C., Castelli, P., and Shriver, W.G., 2018, Short-term resilience of New Jersey tidal marshes to Hurricane Sandy: 

Wetlands, v. 38, no. 3, p. 565–575.

Lynch, J.C., Hensel, P.F., and Cahoon, D.R., 2015, The surface 

elevation table and marker horizon technique—A protocol 

for monitoring wetland elevation dynamics: National Park 

Service, Natural Resources Report NPS/NCBN/NRR–

2015/1078, 62 p. 

Mazerolle, M.J., 2016, AICcmodavg—Model selection and 

multi-model inference based on (Q)AIC(c) (v. 2.0-4): R 

package, accessed August 2016 at http://CRAN.R-project.

org/package=AICcmodavg. 

Middleton, B., 2016, Differences in impacts of Hurricane 

Sandy on freshwater swamps on the Delmarva Peninsula, 

Mid-Atlantic Coast, USA: Ecological Engineering, v. 87, 

p. 62–70.

Moher, D., Liberati, A., Tetzlaff, J., and Altman, D.G., 2009, 

Preferred reporting items for systematic reviews and metaanalyses—The PRISMA statement: PLoS Medicine, v. 6, 

no. 6, e1000097, accessed September 2015 at https://doi.

org/10.1371/journal.pmed.1000097.

Moller, I., Kudella, M., Rupprecht, F., Spencer, T., Paul, M., 

van Wesenbeeck, B.K., Wolters, G., Jensen, K., Bouma, 

T.J., Miranda-Lange, M., and Schimmels, S., 2014, Wave 

attenuation over coastal salt marshes under storm surge 

conditions: Nature Geoscience v. 7, p. 727–731.

Narayan, S., Beck, M., Wilson, P., Thomas, C., Guerrero, A., 

Shepard, C., Reguero, B., Franco, G., Ingram, J., and Trespalacios, D., 2017, The value of coastal wetlands for flood 

damage reduction in the northeastern USA: Nature Scientific Reports, v. 7, accessed December 2017 at https://www.

nature.com/articles/s41598-017-09269-z.

National Aeronautics and Space Administration [2013], Hurricane Sandy (Atlantic Ocean), October 28, 2013: National 

Aeronautics and Space Administration web page, accessed 

March 3, 2017, at https://www.nasa.gov/mission_pages/hurricanes/archives/2012/h2012_Sandy.html. 

National Oceanic and Atmospheric Administration [2010], 

County by county hurricane strikes (1900–2009): National 

Oceanic and Atmospheric Administration, National Hurricane Center web page, last updated February 2010, accessed 

July 29, 2015, at https://www.nhc.noaa.gov/ms-excel/HurricaneStrikes_20100204.xls.

National Oceanic and Atmospheric Administration, 2014, 

NOAA/National Hurricane Center preliminary best track 

tropical cyclone tracks [file: al182012_best_track.zip]: 

National Oceanic and Atmospheric Administration, National 

Hurricane Center, accessed July 29, 2015, at http://www.

nhc.noaa.gov/gis/.

Pebesma, E.J., and Bivand, R.S., 2005, Classes and methods 

for spatial data in R: R News, v. 5, no. 2, accessed April 

2015 at http://cran.r-project.org/doc/Rnews/.

Peduzzi, P., Chatenoux, B., Dao, H., De Bono, A., Herold, 

C., Kossin, J., Mouton, F., and Nordbeck, O., 2012, Global 

trends in tropical cyclone risk: Nature Climate Change, v. 2, 

p. 289–294.

Quirk, T., 2016, Impact of Hurricane Sandy on salt marshes of 

New Jersey: Estuarine, Coastal and Shelf Science, v. 183, 

p. 235–248.

R Core Team, 2016, R—A language and environment for statistical computing: R Foundation for Statistical Computing, 

Vienna, Austria, accessed August 2015 at https://www.Rproject.org/.

Rachlin, J.W., Stalter, R., Kincaid, D., and Warkentine, 

B.E., 2017, The effect of Superstorm Sandy on salt marsh 

vascular flora in the New York bight: Journal of the Torrey 

Botanical Society, v. 144, no. 1, p. 40–46.

Rangoonwala, A., Enwright, N., Ramsey, E., and Spruce, J., 

2016, Radar and optical mapping of surge persistence and 

marsh dieback along the New Jersey Mid-Atlantic coast 

after Hurricane Sandy: International Journal of Remote 

Sensing, v., 37, p. 1692–1713.

Reed, A.J., Mann, M.E., Emanuel, K.A., Lin, N., Horton, B.P., 

Kemp, A.C., and Donnelly, J.P., 2015, Increased threat of 

tropical cyclones and coastal flooding to New York City 

during the anthropogenic era: Proceedings of the National 

Academy of Sciences, v. 112, no. 41, p. 12610–12615.

Reed, D.J., 2002, Sea-level rise and coastal marsh sustainability—Geological and ecological factors in the Mississippi 

delta plain: Geomorphology, v. 48, p. 233–243.
54 Hurricane Sandy Impacts on Coastal Wetland Resilience

Resio, D.T., and Westerink, J.J., 2008, Modeling the physics 

of storm surges: Physics Today, v. 61, p. 33–38.

Rosseel, Y., 2012, lavaan—An R package for structural equation modeling: Journal of Statistical Software, v. 48, no. 2, 

p. 1–36, accessed September 2015 at http://www.jstatsoft.

org/v48/i02/.

Rupprecht, F., Moller, I., Paul, M., Kudella, M. Spencer, T., 

van Wesenbeeck, B.K., Wolters, G., Jensen, K., Bouma, 

T.J., Miranda-Lange, M., and Schimmels, S., 2017, Vegetation-wave interactions in salt marshes under storm surge 

conditions: Ecological Engineering, v. 100, p. 301–315.

Sallenger, A.H., Doran, K.S., and Howd, P.A., 2012, Hotspot 

of accelerated sea-level rise on the Atlantic coast of North 

America: Nature Climate Change, v. 2, p. 884–888.

Sopkin, K.L., Stockdon, H.F., Doran, K.S., Plant, N.G., 

Morgan, K.L.M., Guy, K.K., and Smith, K.E.L., 2014, Hurricane Sandy—Observations and analysis of coastal change: 

U.S. Geological Survey Open-File Report 2014–1088, 

54 p., accessed July 2015 at http://dx.doi.org/10.3133/

ofr20141088.

Stevens, D.L., and Olsen, A.R., 2004, Spatially balanced sampling of natural resources: Journal of the American Statistical Association, v. 99, p. 262–278. 

Stevenson, J.C., Ward, L.G., and Kearney, M.S, 1988, Sediment transport and trapping in marsh system—Implications 

of tidal flux studies: Marine Geology, v. 80, p. 37–59.

Sweet, W.V., Kopp, R.E., Weaver, C.P., Obeysekera, J., 

Horton, R.M., Thieler, E.R., and Zervas, C., 2017, Global 

and regional sea level rise scenarios for the United States: 

National Oceanic and Atmospheric Administration Technical Report NOS CO-OPS 083, 55 p., + appendices.

Talke, S.A., Orton, P., and Jay, D.A., 2014, Increasing storm 

tides in New York Harbor, 1844–2013: Geophysical 

Research Letters, v. 41, p. 3149–3155.

Tebaldi, C., Strauss, B.H., and Zervas, C.E., 2012, Modelling 

sea level rise impacts on storm surges along US coasts: 

Environmental Research Letters, v. 7, no. 1, 11 p.

Valle-Levinson, A., Olabarrieta, M., and Valle, A., 2013, 

Semi-diurnal perturbations to the surge of Hurricane Sandy: 

Geophysical Research Letters, v. 40, p. 2211–2217.

Wang, H., Chen, Q., Hu, K., Snedden, G.A., Hartig, E.K., 

Couvillion, B.R., Johnson, C.L., and Orton, P.M., 2017, 

Numerical modeling of the effects of Hurricane Sandy and 

potential future hurricanes on spatial patterns of salt marsh 

morphology in Jamaica Bay, New York City: U.S. Geological Survey Open-File Report 2017–1016, 43 p., accessed 

March 2018 at https://doi.org/10.3133/ofr20171016.

Webb, E.L., Friess, D.A., Krauss, K.W., Cahoon, D.R., Guntenspergen, G.R., and Phelps, J., 2013, A global standard for 

monitoring coastal wetland vulnerability to accelerated sealevel rise: Nature Climate Change, v. 3, no. 5, p. 458–465.

Weist, W.A., Correll, M.D., Olsen, B.J., Elphick, C.S., Hodgman, T.P., Curson, D.R., and Shriver, W.G., 2016, Population estimates for tidal marsh birds of high conservation 

concern in the northeastern USA from a design-based 

survey: The Condor, v. 118, p. 274–288.

Wickham H., 2007, Reshaping data with the reshape package: 

Journal of Statistical Software, v. 21, no. 12, accessed 

March 2017 at http://www.jstatsoft.org/v21/i12/.

Wickham, H., 2014, Tidy data: Journal of Statistical Software, 

v. 59, no. 10, accessed March 2017 at http://www.jstatsoft.

org/V59/i10/.

Woodruff, J.D., Irish, J.L., and Camargo, S.J., 2013, Coastal 

flooding by tropical cyclones and sea-level rise: Nature, 

v. 504, p. 44–52.

Zuur, A.F., Ieno, E.N., Walker, N.J., Saveliev, A.A., and Smith, 

G.M., 2009, Mixed effects models and extensions in ecology with R: New York, Springer, 574 p.
Glossary 55

Glossary

accretion The accumulation of matter, both 

mineral and organic, carried by a river or 

stream. Vertical accretion refers to the buildup 

of the sediment substrate, whereas lateral 

accretion refers to horizontal expansion of the 

sediment substrate.

covariate An observable, continuous secondary variable that may affect the response 

variable. Covariates are often used in a statistical model to help control variability, so that 

the response to the primary factors of interest 

can be discerned. For example, wetland elevation relative to mean high water is a secondary variable that may help determine the effect 

of vegetation type on elevation change.

elevation change Change in the height of 

the wetland surface (positive or negative) 

relative to the base of the SET mark as measured by the surface elevation table (SET).

hurricane strike Refers to a location where 

a hurricane strike occurs, if the location 

passes within the hurricane’s strike circle, a 

circle of 125 nautical mile (n mi) diameter, 

centered 12.5 n mi to the right of the hurricane center (looking in the direction of motion). This circle is meant to depict the typical 

extent of hurricane force winds, which are 

approximately 75 n mi to the right of center 

and 50 n mi to the left (from http://www.nhc.

noaa.gov/aboutgloss.shtml#i).

indirect hurricane strike Refers to locations that do not experience a direct hit from 

a hurricane, but do experience hurricane force 

winds (either sustained or gusts) or tides of at 

least 4 feet above normal (from http://www.

nhc.noaa.gov/aboutgloss.shtml#i).

inundation The total water level that occurs 

on normally dry ground as a result of the 

storm tide, expressed in terms of height above 

ground level (from Blake and others, 2013).

marker horizon An artificial soil horizon 

placed on a wetland surface to measure vertical accretion (in other words, the accumulation of material above the marker horizon). 

Feldspar is a common marker material.

marsh buffer A designated area surrounding marsh polygons; a buffer allows adjacent 

marsh in close proximity to be combined into 

a single marsh patch. 

marsh patch Discrete spatial areas of marsh 

defined by marsh polygons (from National 

Wetlands Inventory, code E2EM); a 50-meter 

marsh buffer was created around each marsh 

polygon, and those polygons with intersecting 

buffers are considered to be part of the same 

marsh patch. The 50-m buffer connects polygons that are artificially divided by channels 

or roads. 

marsh polygon Geographic boundary surrounding estuarine emergent marsh identified 

by the National Wetlands Inventory (code 

E2EM).

marsh resilience The capacity of a marsh 

system to maintain function, structure, and 

feedbacks in the face of disturbance (Folke 

and others, 2004)

sea-level rise, eustatic Vertical rate of increase in local sea level; typically determined 

from long-term sea-level records. 

sea-level rise, relative The combination of 

eustatic sea-level rise and local vertical land 

motion (in other words, isostatic land subsidence or uplift and near surface processes 

including shallow subsidence and shallow 

expansion).

SET mark The permanent infrastructure 

established at a surface elevation table-marker 

horizon (SET-MH) station, from which SET 

measurements are taken; also colloquially 

referred to as a SET benchmark in early SET 

literature. If an SET mark meets National 

Geodetic Survey bluebook standards, it can be 

referred to as a bench mark. There are three 

types of SET marks: pipe SET mark, deep-rod 

SET mark (deep RSET mark), and shallowrod SET mark (shallow RSET mark).

shallow expansion The upward movement 

of the wetland surface relative to the base of 

the SET mark caused by subsurface expansion 

of the substrate (for example, dilation water 

storage or enhanced root growth), calculated 

as the difference between vertical accretion, 

as measured by a marker horizon, and elevation change, as measured by the SET (in other 

words, vertical accretion minus elevation). 

Shallow expansion only applies to the portion 

of the substrate above the base of the SET 

mark and not the portion below it.
56 Hurricane Sandy Impacts on Coastal Wetland Resilience

shallow subsidence The sinking or downward movement of the wetland surface relative to the base of the SET mark caused by 

subsurface compaction or soil shrinkage. It is 

calculated as the difference between vertical 

accretion, as measured by a marker horizon, 

and elevation change, as measured by the 

SET (in other words, vertical accretion minus 

elevation). Shallow subsidence only applies to 

the portion of the substrate above the base of 

the SET mark, and not the portion below it. 

storm surge The abnormal rise of water generated by a storm, over and above the predicted astronomical tide, expressed in terms of 

height above normal tide levels (from Blake 

and others, 2013)

storm tide The water level owing to the 

combination of storm surge and astronomical 

tide, expressed in terms of height above a vertical datum, for example, the North American 

Vertical Datum of 1988 or Mean Lower Low 

Water (from Blake and others, 2013).

subsidence The sinking or downward 

movement of a surface relative to a datum. 

surface elevation table (SET) A portable mechanical device that provides high-resolution 

measurements of relative elevation change in 

wetland sediments or shallow water bottoms 

relative to the depth of the SET mark to which 

it is attached. The original SET was designed 

to attach to a hollow pipe mark. The rod SET 

(RSET) was designed to attach to either a 

stainless steel rod mark (deep RSET mark) or 

a shallow hollow-legged mark (shallow RSET 

mark).

surface sediment deposition The process of 

suspended sediment deposition on the wetland 

surface; which contributes to wetland vertical 

accretion. 

vertical accretion The building up of a 

wetland surface through the deposition and 

accumulation of sediments. See accretion.
Appendixes 1–3

Figures

1.1. A, Photographs of the surface elevation table developed in the 1990s and, B, the rod 

surface elevation table developed in the 2000s, deployed on their benchmarks and 

pin heights being measured......................................................................................................60

1.2. A, Photograph showing the spatial relation between the rod surface elevation table 

mark and feldspar marker horizons established on a recent thin-layer sediment 

deposit designed to restore elevations in this degraded marsh. B, Photograph 

showing a core taken through a marker horizon revealing the visible feldspar layer, 

from which vertical accretion is measured ...........................................................................61

1.3. Diagram of a wetland substrate showing the vertical relation between the 

measurements of elevation change by the rod surface elevation table (vertical 

land motion or VLMw) and vertical accretion (VA) by the marker horizon........................62

Tables

2.1. Surface elevation table-marker horizon data ........................................................................63

3.1. Summary output for best deviation from expected surface elevation change model 

(model 15e).................................................................................................................................117

3.2. Summary output for the best storm surge submodel (model 3) using eligible surface 

elevation table dataset ............................................................................................................117

Appendix 1. The Surface Elevation Table-Marker Horizon Method 59

Appendix 1. The Surface Elevation Table-Marker Horizon Method

An in-depth and detailed description of the surface elevation table-marker horizon (SET-MH) method is provided in 

the SET-MH protocol by Lynch and others (2015). For anyone 

wishing to use this method to measure wetland elevation 

dynamics, it is recommended that you consult this document 

before commencing. The following text is a brief overview of 

the SET-MH method derived from the SET-MH protocol. 

Surface Elevation Table 

The surface elevation table (SET) is a portable, mechanical device that attaches to a pipe or rod mark driven permanently into the wetland substrate (fig. 1.1) and provides 

high-precision measurements of relative elevation change in 

wetland sediments or shallow water bottoms relative to the 

base of the pipe or rod mark. The measurements are made by 

lowering nine pins from the SET device to the wetland surface 

from as many as eight positions around the mark. The SET is 

attached to the mark in such a way that it reoccupies the same 

reference plane in space, and each time readings are taken 

each pin reoccupies the same point on the wetland surface. 

Hence, the measurements are repeatable, can be made over 

long periods of time, and are of sufficiently high resolution to 

compare to long-term sea level trends measured by tide gages 

(Cahoon, 2015). Detailed designs of the original (pipe) SET 

are provided in Boumans and Day (1993) and Cahoon and 

others (2002a); detailed designs of the Rod SET are in Cahoon 

and others (2002b) and Callaway and others (2013).

Marker Horizon

A marker horizon is an artificial soil layer placed on 

the wetland surface that over time becomes buried and from 

which vertical accretion can be measured (fig. 1.2A). Numerous materials are used as marker horizons (for example, sand, 

feldspar, brick dust), but the most common is feldspar because 

it is (1) bright white and easily distinguishable from the sediments, (2) has a higher density than water, and (3) forms a 

colloidal layer when wet. A core is taken through the horizon, 

and the thickness of sediment accumulated above the horizon 

is measured as vertical accretion (fig. 1.2B). Marker horizons 

are typically established at an SET station within the immediate vicinity of the SET on the date of the initial SET reading 

(fig. 1.2A).

Shallow Subsurface Processes

When used in combination, the SET and MH methods 

provide information on both surface and below ground processes that influence elevation change (fig. 1.3; Cahoon and 

others, 1995a). The SET measures elevation change (VLMw) 

over the depth of the mark that includes both surface accretion 

and erosion combined with subsurface processes of subsidence 

or expansion (for example, expansion of the root zone by root 

growth). The MH measures near-surface vertical accretion 

(VA). The difference between VA minus VLMw indicates the 

amount of shallow subsidence or expansion occurring between 

the depth of the MH and base of the SET mark (fig. 1.3). 

Subsurface process influences on elevation change occurring 

below the base of the mark are not included in the SET-MH 

measurements.
60 Hurricane Sandy Impacts on Coastal Wetland Resilience

A. Surface Elevation Table (SET) in 1990s

B. Rod Surface Elevation Table (RSET) in 2000s

Pipe benchmark depth = 3–6 meters

Rod benchmark depth = 10–25 meters

Figure 1.1. A, Photographs of the surface elevation table (SET) developed in the 1990s and, B, the rod surface elevation table (RSET) 

developed in the 2000s, deployed on their benchmarks and pin heights being measured. Photographs by Donald R. Cahoon, 

U.S. Geological Survey.
Appendix 1. The Surface Elevation Table-Marker Horizon Method 61

A

B

RSET mark

Marker horizon

Marker horizon

Vertical accretion

Figure 1.2. A, Photograph showing the spatial relation between the rod surface elevation table (RSET) mark and feldspar marker 

horizons established on a recent thin-layer sediment deposit designed to restore elevations in this degraded marsh. Photograph by 

Cahoon and others (2019). Note the RSET benchmark is covered with a cap to protect it during the deposition of dredged material. 

B, Photograph showing a core taken through a marker horizon revealing the visible feldspar layer from which vertical accretion is 

measured. Photograph by Donald R. Cahoon, U.S. Geological Survey.
62 Hurricane Sandy Impacts on Coastal Wetland Resilience

Rod SET

(about 2–40 meters deep)

Marker Horizon

(Surface)

SET

Rod

Marker

Horizon

Vertical

Accretion

(VA)

Shallow

Subsidence

or

Expansion

(VLMS

)

Live Root

Zone

Soil

VLMW

VLMC

Bedrock

Figure 1.3. Diagram of a wetland substrate showing the vertical relation between the measurements of elevation change by the rod 

surface elevation table (RSET) (vertical land motion or VLMw) and vertical accretion (VA) by the marker horizon. Shallow subsidence 

(VLMs) or expansion (VLMe) is calculated from a direct comparison of the two rates (VA-VLMw). Crustal vertical land motion (VLMc) is not 

measured by the SET-MH method. Figure from Cahoon, 2015.
Appendix 2. SET-MH Metadata SpreadsheetTable 2.1. Surface elevation table-marker horizon (SET-MH) data.[ME, Maine; VA, Virginia; MA, Massachusetts; CT, Connecticut; NH, New Hampshire; NY, New York; RI, Rhode Island; NJ, New Jersey; DE, Delaware; MD, Maryland; NWRWMA, Wildlife Management Area; NS, National Seashore; LTER, Long Term Ecological Research site; PIE LTER, Plum Island Ecosystems; VCR LTER, Virginia Coast ReservUSFWS, U.S. Fish and Wildlife Service; USGS, U.S. Geological Survey; NYC, New York City; TNC, The Nature Conservancy; MERI, Meadowlands Environmental Research son University; SERC; Smithsonian Environmental Research Center; NERR, National Estuarine Research Reserve; LIS, Long Island Sound]

SET_Geographical_Location Site State Sub_Region Partner 

Acadia National Park, ME Acadia.Bass.Harbor ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Bass.Harbor ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Bass.Harbor ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Schoolic.Peninsula ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Schoolic.Peninsula ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Schoolic.Peninsula ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Maine.Coast.Heritage ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Maine.Coast.Heritage ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Maine.Coast.Heritage ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Thompson.Island ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Thompson.Island ME 1_Coastal_Maine NPS Acadia National Park, ME Acadia.Thompson.Island ME 1_Coastal_Maine NPS PETIT MANAN NATIONAL WILDLIFE 

REFUGE

Gouldsboro Marsh 3 ME 1_Coastal_Maine USFWS 

PETIT MANAN NATIONAL WILDLIFE 

REFUGE

Gouldsboro Marsh 2 ME 1_Coastal_Maine USFWS 

PETIT MANAN NATIONAL WILDLIFE 

REFUGE

Gouldsboro Marsh 1 ME 1_Coastal_Maine USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

PETIT MANAN NATIONAL WILDLIFE REFUGE Sawyers Marsh 3 ME 1_Coastal_Maine USFWS PETIT MANAN NATIONAL WILDLIFE REFUGE Sawyers Marsh 2 ME 1_Coastal_Maine USFWS PETIT MANAN NATIONAL WILDLIFE REFUGE Sawyers Marsh 1 ME 1_Coastal_Maine USFWS MOOSEHORN NATIONAL WILDLIFE REFUGE Hallowell Island ME 1_Coastal_Maine USFWS MOOSEHORN NATIONAL WILDLIFE REFUGE Hallowell Island ME 1_Coastal_Maine USFWS MOOSEHORN NATIONAL WILDLIFE REFUGE Hallowell Island ME 1_Coastal_Maine USFWS MOOSEHORN NATIONAL WILDLIFE REFUGE Hobart St. West ME 1_Coastal_Maine USFWS MOOSEHORN NATIONAL WILDLIFE REFUGE Hobart St. West ME 1_Coastal_Maine USFWS MOOSEHORN NATIONAL WILDLIFE REFUGE Hobart St. West ME 1_Coastal_Maine USFWS MOOSEHORN NATIONAL WILDLIFE 

REFUGE

Hobart St. East ME 1_Coastal_Maine USFWS 

MOOSEHORN NATIONAL WILDLIFE 

REFUGE

Hobart St. East ME 1_Coastal_Maine USFWS 

MOOSEHORN NATIONAL WILDLIFE 

REFUGE

Hobart St. East ME 1_Coastal_Maine USFWS 

MOOSEHORN NATIONAL WILDLIFE 

REFUGE

Ox Cove Rd. Area ME 1_Coastal_Maine USFWS 

MOOSEHORN NATIONAL WILDLIFE 

REFUGE

Ox Cove Rd. Area ME 1_Coastal_Maine USFWS 

MOOSEHORN NATIONAL WILDLIFE 

REFUGE

Ox Cove Rd. Area ME 1_Coastal_Maine USFWS 

PETIT MANAN NATIONAL WILDLIFE 

REFUGE

Sawyers Marsh 4 ME 1_Coastal_Maine USFWS 

Back Bay NWR Long.Island.South VA 10_Coastal_Virginia USFWS Back Bay NWR Long.Island.South VA 10_Coastal_Virginia USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Back Bay NWR Long.Island.South VA 10_Coastal_Virginia USFWS Back Bay NWR Long.Island.North VA 10_Coastal_Virginia USFWS Back Bay NWR Long.Island.North VA 10_Coastal_Virginia USFWS Back Bay NWR Long.Island.North VA 10_Coastal_Virginia USFWS Back Bay NWR North.Marsh VA 10_Coastal_Virginia USFWS Back Bay NWR North.Marsh VA 10_Coastal_Virginia USFWS Back Bay NWR North.Marsh VA 10_Coastal_Virginia USFWS Plum Island Ecosystems LTER LTE-MP-LPP MA 2_CapeCod_CascoBay Marine Biological 

Lab/PIE LTER

Plum Island Ecosystems LTER LTE-MP-LPA MA 2_CapeCod_CascoBay Marine Biological 

Lab/PIE LTER

Plum Island Ecosystems LTER LTE-MP-LPA MA 2_CapeCod_CascoBay Marine Biological 

Lab/PIE LTER

Plum Island Ecosystems LTER LTE-MP-LPA MA 2_CapeCod_CascoBay Marine Biological 

Lab/PIE LTER

Plum Island Ecosystems LTER LTE-MP-LPP MA 2_CapeCod_CascoBay Marine Biological 

Lab/PIE LTER

Plum Island Ecosystems LTER LTE-MP-LPP MA 2_CapeCod_CascoBay Marine Biological 

Lab/PIE LTER

Cape Cod NS, MA Nauset.Marsh MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Nauset.Marsh MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Nauset.Marsh MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Nauset.Marsh MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Peddocks.Island MA 2_CapeCod_CascoBay NPS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Boston Harbor Island, MA Boston.Harbor.Peddocks.Island MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Peddocks.Island MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Thompson.Island MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Thompson.Island MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Thompson.Island MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Thompson.Island MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_N MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_N MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_N MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_GUTSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_GUTSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_GUTSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_PHRAGSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_PHRAGSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_PHRAGSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HTSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HTSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HTSET MA 2_CapeCod_CascoBay NPS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Cape Cod NS, MA Cape Cod NS, MA_H MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_H MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_H MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Cape Cod NS, MA Cape Cod NS, MA_HHSET MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Calf.Island MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Calf.Island MA 2_CapeCod_CascoBay NPS Boston Harbor Island, MA Boston.Harbor.Calf.Island MA 2_CapeCod_CascoBay NPS Plum Island Estuary MAR-RO-OldLevine-Set1 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-NewLevine-Set2 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-NewLevine-Set1 MA 2_CapeCod_CascoBay PIE LTER 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Plum Island Estuary MAR-RO-NewLevine-Set3 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-OldLevine-Set2 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-OldLevine-Set3 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-InfillPond-Set2 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-InfillPond-Set3 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-MorrisIsle-Set1 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-MorrisIsle-Set2 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-MorrisIsle-Set3 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-HolyIs-Set 3 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-HolyIs-Set 2 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-HolyIs-Set 1 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-LawsPt-Set2 MA 2_CapeCod_CascoBay PIE LTER Plum Island Estuary MAR-RO-LawsPt-Set1 MA 2_CapeCod_CascoBay PIE LTER Hampton-Seabrook Estuary Browns Seafood NH 2_CapeCod_CascoBay Academic Hampton-Seabrook Estuary Walton Road NH 2_CapeCod_CascoBay Academic Hampton-Seabrook Estuary Hampton NH 2_CapeCod_CascoBay Academic Hampton-Seabrook Estuary Hampton Falls NH 2_CapeCod_CascoBay Academic Hampton-Seabrook Estuary Route 101 NH 2_CapeCod_CascoBay Academic 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Hampton-Seabrook Estuary Route 1 NH 2_CapeCod_CascoBay Academic Rye Harbor - Awcomin Marsh Awcomin NH 2_CapeCod_CascoBay Academic Rye Harbor - Awcomin Marsh Awcomin NH 2_CapeCod_CascoBay Academic Rye Harbor - Awcomin Marsh Awcomin NH 2_CapeCod_CascoBay Academic Rye Harbor - Awcomin Marsh Awcomin NH 2_CapeCod_CascoBay Academic Plum Island Estuary Plum Island Estuary_Oak Knoll MA 2_CapeCod_CascoBay Academic Plum Island Estuary Plum Island Estuary_Oak Knoll MA 2_CapeCod_CascoBay Academic Plum Island Estuary Plum Island Estuary_Oak Knoll MA 2_CapeCod_CascoBay Academic Plum Island Estuary Plum Island Estuary_Oak Knoll MA 2_CapeCod_CascoBay Academic Squamscott River Squamscott River NH 2_CapeCod_CascoBay Academic Great Bay NERR Sandy Point NERR NH 2_CapeCod_CascoBay Academic Great Bay NERR Sandy Point NERR NH 2_CapeCod_CascoBay Academic Great Bay NERR Sandy Point NERR NH 2_CapeCod_CascoBay Academic Great Bay NERR Sandy Point NERR NH 2_CapeCod_CascoBay Academic Great Bay Farms Great Bay Farms NH 2_CapeCod_CascoBay Academic Great Bay Farms Great Bay Farms NH 2_CapeCod_CascoBay Academic Great Bay Farms Great Bay Farms NH 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_Mile Rd ME 2_CapeCod_CascoBay Academic 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Webhannet Marsh Webhannet Marsh_Mile Rd ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_Oxcart Lane ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_Harbor Rd ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_Harbor Rd ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_Harbor Rd ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_Harbor Rd ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_DIM ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_DIM ME 2_CapeCod_CascoBay Academic Webhannet Marsh Webhannet Marsh_DIM ME 2_CapeCod_CascoBay Academic Rachel Carson NWR Rachel Carson NWR_Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Rachel Carson NWR_Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Rachel Carson NWR_Granite Point Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Rachel Carson NWR_Granite Point Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Rachel Carson NWR_Granite Point Marsh ME 2_CapeCod_CascoBay USFWS MOMOMOY NATIONAL WILDLIFE 

REFUGE

North Monomoy 03 MA 2_CapeCod_CascoBay USFWS 

MOMOMOY NATIONAL WILDLIFE 

REFUGE

North Monomoy 02 MA 2_CapeCod_CascoBay USFWS 

MOMOMOY NATIONAL WILDLIFE 

REFUGE

North Monomoy 01 MA 2_CapeCod_CascoBay USFWS 

MOMOMOY NATIONAL WILDLIFE 

REFUGE

Morris 01 MA 2_CapeCod_CascoBay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Cross Farm 02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Cross Farm 03 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Cross Farm 01 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Grape_Clam_01 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Clam Flats 02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Clam Flats 01 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Grape 02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Knobb 03 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Knobb 02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Knobb 01 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Bill_Forward_2014 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Npool_Impoun 03 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Nelson 02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Nelson 01 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

NP02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

NP03 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Nelson 03 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Npool_Impoun 02 MA 2_CapeCod_CascoBay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

PARKER RIVER NATIONAL WILDLIFE REFUGE Npool_Impoun 01 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE NP01 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE Area_B 03 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE Area_B 01 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE Area_B 02 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE AAS01 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE After_02 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE After_01 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE REFUGE AAS03 MA 2_CapeCod_CascoBay USFWS PARKER RIVER NATIONAL WILDLIFE 

REFUGE

After_03 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

AAS02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

SP02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

SP01 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

AAN 01 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

SP03 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

ANN 02 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

B2 5-40 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

B2 4-120 MA 2_CapeCod_CascoBay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

B2 1-80 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Control 4-120 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Control 3-120 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

Control 3-40 MA 2_CapeCod_CascoBay USFWS 

PARKER RIVER NATIONAL WILDLIFE 

REFUGE

ANN 03 MA 2_CapeCod_CascoBay USFWS 

Rachel Carson NWR Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Moody Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Bourne 3 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Bourne 2 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Bourne 1 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Furbish 3 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Furbish 2 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Furbish 1 ME 2_CapeCod_CascoBay USFWS Webhannet Marsh Mile South 3 ME 2_CapeCod_CascoBay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Webhannet Marsh Mile South 2 ME 2_CapeCod_CascoBay USFWS Webhannet Marsh Mile South 1 ME 2_CapeCod_CascoBay USFWS Webhannet Marsh Mile North 3 ME 2_CapeCod_CascoBay USFWS Webhannet Marsh Mile North 2 ME 2_CapeCod_CascoBay USFWS RACHEL CARSON NATIONAL WILDLIFE REFUGE Harbor 02 ME 2_CapeCod_CascoBay USFWS RACHEL CARSON NATIONAL WILDLIFE REFUGE Drakes 03 ME 2_CapeCod_CascoBay USFWS RACHEL CARSON NATIONAL WILDLIFE REFUGE Drakes 02 ME 2_CapeCod_CascoBay USFWS RACHEL CARSON NATIONAL WILDLIFE REFUGE Little River 2 ME 2_CapeCod_CascoBay USFWS RACHEL CARSON NATIONAL WILDLIFE REFUGE Little River 1 ME 2_CapeCod_CascoBay USFWS RACHEL CARSON NATIONAL 

WILDLIFE REFUGE

Little River 3 ME 2_CapeCod_CascoBay USFWS 

Rachel Carson NWR Mousam Seaward 10 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Mousam Seaward 9 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Mousam Seaward 3 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Mousam River 5 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Mousam River 7 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Mousam River 6 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Granite Point Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Granite Point Marsh ME 2_CapeCod_CascoBay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Rachel Carson NWR Granite Point EU 2 new ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Granite Point Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Granite Point Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Granite Point Marsh ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Goosefare Restrict 4 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Goosefare Restrict 3 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Goosefare Restrict 1 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Goosefare 2 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Goosefare 3 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Goosefare 1 ME 2_CapeCod_CascoBay USFWS Rachel Carson NWR Rachel.Carson ME 2_CapeCod_CascoBay USGS Rachel Carson NWR Rachel.Carson ME 2_CapeCod_CascoBay USGS Rachel Carson NWR Rachel.Carson ME 2_CapeCod_CascoBay USGS Rachel Carson NWR Rachel.Carson ME 2_CapeCod_CascoBay USGS Wells NERR, Maine WR8 ME 2_CapeCod_CascoBay NERR Wells NERR, Maine LR21 ME 2_CapeCod_CascoBay NERR Mamacoke Marsh Mamacoke Marsh_Waterford CT 3_Southern_New_England Academic Mamacoke Marsh Mamacoke Marsh_Waterford CT 3_Southern_New_England Academic 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Mamacoke Marsh Mamacoke Marsh_Waterford CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Barn Island Barn Island_Stonington CT 3_Southern_New_England Academic Pelham Bay Park A series (LIS side of Park), 

Bronx, NY

Pelham Bay Park A series (LIS side of 

Park)_PB

NY 3_Southern_New_England NYC 

Pelham Bay Park A series (LIS side of Park), 

Bronx, NY

Pelham Bay Park A series (LIS side of 

Park)_PB

NY 3_Southern_New_England NYC 

Pelham Bay Park A series (LIS side of Park), 

Bronx, NY

Pelham Bay Park A series (LIS side of 

Park)_PB

NY 3_Southern_New_England NYC 

Pelham Bay Park B series (Hutchinson River 

side of Park), Bronx, NY

Pelham Bay Park B series (Hutchinson 

River side of Park)_PB

NY 3_Southern_New_England NYC 

Pelham Bay Park B series (Hutchinson River 

side of Park), Bronx, NY

Pelham Bay Park B series (Hutchinson 

River side of Park)_PB

NY 3_Southern_New_England NYC 

Pelham Bay Park B series (Hutchinson River 

side of Park), Bronx, NY

Pelham Bay Park B series (Hutchinson 

River side of Park)_PB

NY 3_Southern_New_England NYC 

Narragansett Bay NERR, Prudence Island RI Nag RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Nag RI 3_Southern_New_England NERR 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Narragansett Bay NERR, Prudence Island RI Nag RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Nag RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Nag RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Nag RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Coggeshall RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Coggeshall RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Coggeshall RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Coggeshall RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Coggeshall RI 3_Southern_New_England NERR Narragansett Bay NERR, Prudence Island RI Coggeshall RI 3_Southern_New_England NERR Sachuest NWR, Middletown RI Sachuest Point RI 3_Southern_New_England Other Sachuest NWR, Middletown RI Sachuest Point RI 3_Southern_New_England Other Sachuest NWR, Middletown RI Sachuest Point RI 3_Southern_New_England Other Gooseneck Cove, Newport RI Gooseneck Cove RI 3_Southern_New_England Other Gooseneck Cove, Newport RI Gooseneck Cove RI 3_Southern_New_England Other Gooseneck Cove, Newport RI Gooseneck Cove RI 3_Southern_New_England Other Long Island Sound - Sherwood Island State 

Park

Sherwood CT 3_Southern_New_England Academic 

Long Island Sound - Sherwood Island State 

Park

Sherwood CT 3_Southern_New_England Academic 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Long Island Sound - Sherwood Island State Park Sherwood CT 3_Southern_New_England Academic Long Island Sound - Hoadley Creek Hoadley CT 3_Southern_New_England Academic Long Island Sound - Hoadley Creek Hoadley CT 3_Southern_New_England Academic Long Island Sound - Hoadley Creek Hoadley CT 3_Southern_New_England Academic Long Island Sound - Hoadley Creek Hoadley CT 3_Southern_New_England Academic Long Island Sound - Hoadley Creek Hoadley CT 3_Southern_New_England Academic Long Island Sound - Hoadley Creek Hoadley CT 3_Southern_New_England Academic Long Island Sound - Jarvis Creek Jarvis CT 3_Southern_New_England Academic Long Island Sound - Jarvis Creek Jarvis CT 3_Southern_New_England Academic Long Island Sound - Jarvis Creek Jarvis CT 3_Southern_New_England Academic Long Island Sound - Hoadley Creek Long Island Sound - Hoadley Creek_

Hoadley

CT 3_Southern_New_England Academic 

Long Island Sound - Hoadley Creek Long Island Sound - Hoadley Creek_

Hoadley

CT 3_Southern_New_England Academic 

Long Island Sound - Hoadley Creek Long Island Sound - Hoadley Creek_

Hoadley

CT 3_Southern_New_England Academic 

Long Island Sound - Hoadley Creek Long Island Sound - Hoadley Creek_

Hoadley

CT 3_Southern_New_England Academic 

Long Island Sound - Hoadley Creek Long Island Sound - Hoadley Creek_

Hoadley

CT 3_Southern_New_England Academic 

Long Island Sound - Hoadley Creek Long Island Sound - Hoadley Creek_

Hoadley

CT 3_Southern_New_England Academic 

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Leetes Island Marsh Long Island Sound - Leetes Island Marsh_

Leetes

CT 3_Southern_New_England Academic

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

Long Island Sound - Quinnipiac Estuary Long Island Sound - Quinnipiac Estuary_

Quinnipiac

CT 3_Southern_New_England Academic 

STEWART B. MCKINNEY NATIONAL 

WILDLIFE REFUGE

GMU CT 3_Southern_New_England USFWS 

STEWART B. MCKINNEY NATIONAL 

WILDLIFE REFUGE

GMU CT 3_Southern_New_England USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

STEWART B. MCKINNEY NATIONAL WILDLIFE REFUGE GMU CT 3_Southern_New_England USFWS STEWART B. MCKINNEY NATIONAL WILDLIFE REFUGE DEP001 CT 3_Southern_New_England USFWS STEWART B. MCKINNEY NATIONAL WILDLIFE REFUGE SMU CT 3_Southern_New_England USFWS STEWART B. MCKINNEY NATIONAL WILDLIFE REFUGE SMU CT 3_Southern_New_England USFWS STEWART B. MCKINNEY NATIONAL WILDLIFE REFUGE SMU CT 3_Southern_New_England USFWS NINIGRET NATIONAL WILDLIFE REFUGE NIN RI 3_Southern_New_England USFWS NINIGRET NATIONAL WILDLIFE REFUGE NIN RI 3_Southern_New_England USFWS NINIGRET NATIONAL WILDLIFE REFUGE NIN RI 3_Southern_New_England USFWS NINIGRET NATIONAL WILDLIFE REFUGE Ninigret North RI 3_Southern_New_England USFWS NINIGRET NATIONAL WILDLIFE 

REFUGE

Ninigret North RI 3_Southern_New_England USFWS 

NINIGRET NATIONAL WILDLIFE 

REFUGE

Ninigret North RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

SD RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

SD RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

JHC RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

JHC RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

JHC RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

JHC RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

Chafee RI 3_Southern_New_England USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

Chafee RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

Chafee RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

JHC RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

JHC RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

JHC RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

MB RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

MB RI 3_Southern_New_England USFWS 

JOHN H. CHAFEE NATIONAL WILDLIFE 

REFUGE

MB RI 3_Southern_New_England USFWS 

SACHUEST POINT NATIONAL 

WILDLIFE REFUGE

SPT RI 3_Southern_New_England USFWS 

SACHUEST POINT NATIONAL 

WILDLIFE REFUGE

SPT RI 3_Southern_New_England USFWS 

SACHUEST POINT NATIONAL 

WILDLIFE REFUGE

SPT RI 3_Southern_New_England USFWS 

MOMOMOY NATIONAL WILDLIFE 

REFUGE

Minimoy MA 3_Southern_New_England USFWS 

MOMOMOY NATIONAL WILDLIFE 

REFUGE

Minimoy MA 3_Southern_New_England USFWS 

Great Meadows Great Meadows_Stratford CT 3_Southern_New_England USFWS Great Meadows Great Meadows_Stratford CT 3_Southern_New_England USFWS Great Meadows Great Meadows_Stratford CT 3_Southern_New_England USFWS Great Meadows, NWR Great.Meadows CT 3_Southern_New_England USGS Great Meadows, NWR Great.Meadows CT 3_Southern_New_England USGS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Great Meadows, NWR Great.Meadows CT 3_Southern_New_England USGS Great Meadows, NWR Great.Meadows CT 3_Southern_New_England USGS Waquoit Bay NERR Waquoit Bay NERR_Section1 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section1 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section1 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section1 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section3 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section3 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section3 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section2 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section2 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section2 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section3 MA 3_Southern_New_England NERR Waquoit Bay NERR Waquoit Bay NERR_Section2 MA 3_Southern_New_England NERR Idlewild Park, Queens, NY Idlewild Park, Queens, NY_IP NY 4_Long_Island NYC Idlewild Park, Queens, NY Idlewild Park, Queens, NY_IP NY 4_Long_Island NYC Idlewild Park, Queens, NY Idlewild Park, Queens, NY_IP NY 4_Long_Island NYC Spring Creek Park, Queens, NY Spring Creek Park, Queens, NY_SC NY 4_Long_Island NYC 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Spring Creek Park, Queens, NY Spring Creek Park, Queens, NY_SC NY 4_Long_Island NYC Spring Creek Park, Queens, NY Spring Creek Park, Queens, NY_SC NY 4_Long_Island NYC Udall’s Cove Park Preserve, Queens, NY Udall’s Cove Park Preserve, Queens, 

NY_UC

NY 4_Long_Island NYC 

Udall’s Cove Park Preserve, Queens, NY Udall’s Cove Park Preserve, Queens, 

NY_UC

NY 4_Long_Island NYC 

Udall’s Cove Park Preserve, Queens, NY Udall’s Cove Park Preserve, Queens, 

NY_UC

NY 4_Long_Island NYC 

Jamaica Bay, NY GATE.Big.Egg.Spray NY 4_Long_Island NPS Jamaica Bay, NY GATE.Big.Egg.Spray NY 4_Long_Island NPS Jamaica Bay, NY GATE.JOCO.REF NY 4_Long_Island NPS Jamaica Bay, NY GATE.JOCO.REF NY 4_Long_Island NPS Jamaica Bay, NY GATE.JOCO.REF NY 4_Long_Island NPS Jamaica Bay, NY GATE.JOCO NY 4_Long_Island NPS Jamaica Bay, NY GATE.JOCO NY 4_Long_Island NPS Jamaica Bay, NY GATE.JOCO NY 4_Long_Island NPS Jamaica Bay, NY GATE.Black.Bank NY 4_Long_Island NPS Jamaica Bay, NY GATE.Elders.East NY 4_Long_Island NPS Jamaica Bay, NY GATE.Elders.East NY 4_Long_Island NPS Fire Island NS, NY FIIS.Watch.Hill NY 4_Long_Island NPS Fire Island NS, NY FIIS.Watch.Hill NY 4_Long_Island NPS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Fire Island NS, NY FIIS.Watch.Hill NY 4_Long_Island NPS Fire Island NS, NY FIIS.Hospital.Point NY 4_Long_Island NPS Fire Island NS, NY FIIS.Hospital.Point NY 4_Long_Island NPS Fire Island NS, NY FIIS.Hospital.Point NY 4_Long_Island NPS Fire Island NS, NY FIIS.Great.Gun NY 4_Long_Island NPS Fire Island NS, NY FIIS.Great.Gun NY 4_Long_Island NPS Jamaica Bay, NY GATE.Big.Egg.Reference NY 4_Long_Island NPS Jamaica Bay, NY GATE.Big.Egg.Spray NY 4_Long_Island NPS Jamaica Bay, NY GATE.Big.Egg.Reference NY 4_Long_Island NPS Jamaica Bay, NY GATE.Big.Egg.Reference NY 4_Long_Island NPS Jamaica Bay, NY GATE.Black.Bank NY 4_Long_Island NPS Jamaica Bay, NY GATE.Black.Bank NY 4_Long_Island NPS Jamaica Bay, NY GATE.Elders.East.NF NY 4_Long_Island NPS Jamaica Bay, NY GATE.Elders.East.NF NY 4_Long_Island NPS Jamaica Bay, NY GATE.Elders.East.NF NY 4_Long_Island NPS Jamaica Bay, NY GATE.Elders.East NY 4_Long_Island NPS Fire Island NS, NY FIIS.Great.Gun NY 4_Long_Island NPS East Creek-Sands Point, NY EC NY 4_Long_Island NYS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

East Creek-Sands Point, NY EC NY 4_Long_Island NYS East Creek-Sands Point, NY EC NY 4_Long_Island NYS West Pond-Glen Cove, NY WP NY 4_Long_Island NYS West Pond-Glen Cove, NY WP NY 4_Long_Island NYS West Pond-Glen Cove, NY WP NY 4_Long_Island NYS Frost Creek-Lattingtown, NY FC NY 4_Long_Island NYS Frost Creek-Lattingtown, NY FC NY 4_Long_Island NYS Frost Creek-Lattingtown, NY FC NY 4_Long_Island NYS Flax Pond-Old Field, NY FP NY 4_Long_Island NYS Flax Pond-Old Field, NY FP NY 4_Long_Island NYS Flax Pond-Old Field, NY FP NY 4_Long_Island NYS Long Island, New York Bass.Creek NY 4_Long_Island TNC Long Island, New York Bass.Creek NY 4_Long_Island TNC Long Island, New York Bass.Creek NY 4_Long_Island TNC Long Island, New York Lawrence.Marsh NY 4_Long_Island TNC Long Island, New York Lawrence.Marsh NY 4_Long_Island TNC Long Island, New York Lawrence.Marsh NY 4_Long_Island TNC Long Island, New York North.Greensedge.West.Hempstead NY 4_Long_Island TNC 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Long Island, New York North.Greensedge.West.Hempstead NY 4_Long_Island TNC Long Island, New York North.Greensedge.West.Hempstead NY 4_Long_Island TNC Long Island, New York Pine.Neck NY 4_Long_Island TNC Long Island, New York Pine.Neck NY 4_Long_Island TNC Long Island, New York Pine.Neck NY 4_Long_Island TNC Long Island, New York Pine.Neck NY 4_Long_Island TNC Long Island, New York Pine.Neck NY 4_Long_Island TNC Long Island, New York Pine.Neck NY 4_Long_Island TNC Long Island, New York Hubbard.Creek NY 4_Long_Island TNC Long Island, New York Hubbard.Creek NY 4_Long_Island TNC Long Island, New York Hubbard.Creek NY 4_Long_Island TNC Long Island, New York Indian.Island NY 4_Long_Island TNC Long Island, New York Indian.Island NY 4_Long_Island TNC Long Island, New York Indian.Island NY 4_Long_Island TNC Long Island, New York Indian.Island NY 4_Long_Island TNC Long Island, New York Indian.Island NY 4_Long_Island TNC Long Island, New York Indian.Island NY 4_Long_Island TNC Long Island, New York Accabonac.Harbor NY 4_Long_Island TNC 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Long Island, New York Accabonac.Harbor NY 4_Long_Island TNC Long Island, New York Accabonac.Harbor NY 4_Long_Island TNC Long Island, New York Mashomack.Point NY 4_Long_Island TNC Long Island, New York Mashomack.Point NY 4_Long_Island TNC Long Island, New York Mashomack.Point NY 4_Long_Island TNC Long Island, New York Cedar.Beach NY 4_Long_Island TNC Long Island, New York Cedar.Beach NY 4_Long_Island TNC Long Island, New York Cedar.Beach NY 4_Long_Island TNC SEATUCK NATIONAL WILDLIFE 

REFUGE

Lido Beach NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Lido Beach NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Lido Beach NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Seatuck NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Seatuck NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Seatuck NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Seatuck NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Seatuck NY 4_Long_Island USFWS 

SEATUCK NATIONAL WILDLIFE 

REFUGE

Seatuck NY 4_Long_Island USFWS 

Wertheim NWR, NY WWU NY 4_Long_Island USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Wertheim NWR, NY WWU NY 4_Long_Island USFWS Wertheim NWR, NY WWU NY 4_Long_Island USFWS Smith Point, NY Smith.Point NY 4_Long_Island USFWS Smith Point, NY Smith.Point NY 4_Long_Island USFWS Smith Point, NY Smith.Point NY 4_Long_Island USFWS Wertheim NWR, NY WEU NY 4_Long_Island USFWS Wertheim NWR, NY WEU NY 4_Long_Island USFWS Wertheim NWR, NY WEU NY 4_Long_Island USFWS Wertheim NWR, NY WNU NY 4_Long_Island USFWS Wertheim NWR, NY WNU NY 4_Long_Island USFWS Wertheim NWR, NY WNU NY 4_Long_Island USFWS Absecon, New Jersey Absecon, New Jersey_Absecon NJ 5_Coastal_New_Jersey USGS Absecon, New Jersey Absecon, New Jersey_Absecon NJ 5_Coastal_New_Jersey USGS Absecon, New Jersey Absecon, New Jersey_Absecon NJ 5_Coastal_New_Jersey USGS Absecon, New Jersey Absecon, New Jersey_Fish Island South NJ 5_Coastal_New_Jersey USGS Absecon, New Jersey Absecon, New Jersey_Middle Island NJ 5_Coastal_New_Jersey USGS Absecon, New Jersey Absecon, New Jersey_Fish Island North NJ 5_Coastal_New_Jersey USGS Forsythe NWR- West Creek, NJ (Barnegat 

Bay)

West Creek NJ 5_Coastal_New_Jersey Other 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Forsythe NWR- West Creek, NJ (Barnegat 

Bay)

West Creek NJ 5_Coastal_New_Jersey Other 

Forsythe NWR- West Creek, NJ (Barnegat 

Bay)

West Creek NJ 5_Coastal_New_Jersey Other 

Island Beach State Park, NJ (Barnegat Bay) Island Beach State Park NJ 5_Coastal_New_Jersey Other Island Beach State Park, NJ (Barnegat Bay) Island Beach State Park NJ 5_Coastal_New_Jersey Other Island Beach State Park, NJ (Barnegat Bay) Island Beach State Park NJ 5_Coastal_New_Jersey Other Forsythe NWR- Mantoloking, NJ (Barnegat 

Bay)

Reedy Creek NJ 5_Coastal_New_Jersey Other 

Forsythe NWR- Mantoloking, NJ (Barnegat 

Bay)

Reedy Creek NJ 5_Coastal_New_Jersey Other 

Forsythe NWR- Mantoloking, NJ (Barnegat 

Bay)

Reedy Creek NJ 5_Coastal_New_Jersey Other 

Saw Mill Creek Marsh, Staten Island, NY Saw Mill Creek, Staten Island, NY_SM NY 5_Coastal_New_Jersey NYC Saw Mill Creek Marsh, Staten Island, NY Saw Mill Creek, Staten Island, NY_SM NY 5_Coastal_New_Jersey NYC Saw Mill Creek Marsh, Staten Island, NY Saw Mill Creek, Staten Island, NY_SM NY 5_Coastal_New_Jersey NYC NJ Meadowlands WS.1 NJ 5_Coastal_New_Jersey MERI NJ Meadowlands WS.2 NJ 5_Coastal_New_Jersey MERI NJ Meadowlands WS.3 NJ 5_Coastal_New_Jersey MERI NJ Meadowlands EDS.1 NJ 5_Coastal_New_Jersey MERI NJ Meadowlands EDS.3 NJ 5_Coastal_New_Jersey MERI NJ Meadowlands EDS.2 NJ 5_Coastal_New_Jersey MERI NJ Meadowlands RB.4 NJ 5_Coastal_New_Jersey MERI/FDU 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

NJ Meadowlands RB.6 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands RB.5 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands RB.1 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands RB.2 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands RB.3 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands SM.1 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands SM.2 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands SM.3 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands LR.1 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands LR.2 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands LR.3 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands SHS.1 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands SHS.2 NJ 5_Coastal_New_Jersey MERI/FDU NJ Meadowlands SHS.3 NJ 5_Coastal_New_Jersey MERI/FDU Sandy Hook NJ GATE.Sandy.Hook NJ 5_Coastal_New_Jersey NPS Sandy Hook NJ GATE.Sandy.Hook NJ 5_Coastal_New_Jersey NPS Sandy Hook NJ GATE.Sandy.Hook NJ 5_Coastal_New_Jersey NPS CAPE MAY NATIONAL WILDLIFE 

REFUGE

TMBU02 NJ 5_Coastal_New_Jersey USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

TMBU01 NJ 5_Coastal_New_Jersey USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

TMBU03 NJ 5_Coastal_New_Jersey USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Cedar Headwaters01 NJ 5_Coastal_New_Jersey USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Cedar Headwaters02 NJ 5_Coastal_New_Jersey USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Cedar Headwaters03 NJ 5_Coastal_New_Jersey USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Cedar Swamp01 NJ 5_Coastal_New_Jersey USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Cedar Swamp02 NJ 5_Coastal_New_Jersey USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Cedar Swamp03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Reeds Bay/Hamm Cove SET 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Wildlife Drive 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

EAST POOL NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

East Pool 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

East Pool 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Wildlife Drive 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Galloway South 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Galloway South 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Galloway South 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Wildlife Drive 01 NJ 5_Coastal_New_Jersey USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Galloway North 02 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Wildlife Drive 04 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Galloway North 03 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Galloway North 01 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Reeds Bay SET 02 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Reeds Bay/Hamm Cove SET 01 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Oyster Creek SET 03 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Oyster Creek SET 02 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Oyster Creek SET 01 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Motts/Mullica SET 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Motts/Mullica SET 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Motts/Mullica SET 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Motts/Mull. Wild SET 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Nacote Crk. Treat SET 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Nacote Crk. Treat SET 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Motts/Mull. Wild SET 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Motts/Mull. Wild SET 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Nacote Crk. Treat SET 01 NJ 5_Coastal_New_Jersey USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Parkertown SET 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

West Creek NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

West Creek NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

West Creek NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Parkertown SET 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Dinner 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Dinner 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Purple* NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Yellow* NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Green * NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Purple* NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Purple* NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Cedar Run Dock SET 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Green * NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Yellow* NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mill Crk-Cedar Run SET Green * NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Cedar Run 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Cedar Run 02 NJ 5_Coastal_New_Jersey USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Cedar Run 03 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE AT&T 03 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE AT&T 02 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE AT&T (New) SET 03 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE AT&T (New) SET 02 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE AT&T 01 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE AT&T (New) SET 01 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Forked River 05 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Forked River 03 NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Forked River 06 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Forked River 04 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Ocean Gate 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Ocean Gate 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Ocean Gate 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Good Luck Point 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Good Luck Point 03 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Good Luck Point 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mandolay 03 NJ 5_Coastal_New_Jersey USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mandolay 01 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Mandolay 02 NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Reedy Creek NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Reedy Creek NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Reedy Creek NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Metedeconk NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Metedeconk NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Metedeconk NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Metedeconk NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Metedeconk NJ 5_Coastal_New_Jersey USFWS 

EDWIN B. FORSYTHE NATIONAL 

WILDLIFE REFUGE

Metedeconk NJ 5_Coastal_New_Jersey USFWS 

Forsythe, New Jersey Little.Beach NJ 5_Coastal_New_Jersey USFWSForsythe, New Jersey Little.Beach NJ 5_Coastal_New_Jersey USFWSForsythe, New Jersey Little.Beach NJ 5_Coastal_New_Jersey USFWSForsythe, New Jersey Little.Beach NJ 5_Coastal_New_Jersey USFWSForsythe, New Jersey Little.Beach NJ 5_Coastal_New_Jersey USFWSForsythe, New Jersey Little.Beach NJ 5_Coastal_New_Jersey USFWSForsythe NWR ATT NJ 5_Coastal_New_Jersey USFWS
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Forsythe NWR ATT NJ 5_Coastal_New_Jersey USFWS Forsythe NWR ATT NJ 5_Coastal_New_Jersey USFWS Forsythe NWR ATT NJ 5_Coastal_New_Jersey USFWS Forsythe NWR ATT NJ 5_Coastal_New_Jersey USFWS Forsythe NWR ATT NJ 5_Coastal_New_Jersey USFWS EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Horse Point NJ 5_Coastal_New_Jersey EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Horse Point NJ 5_Coastal_New_Jersey EDWIN B. FORSYTHE NATIONAL WILDLIFE REFUGE Horse Point NJ 5_Coastal_New_Jersey Delaware NERR (St Jones Component) Impoundment DE 6_Delaware_Bay NERRDelaware NERR (St Jones Component) Boardwalk DE 6_Delaware_Bay NERRDelaware NERR (St Jones Component) Wildcat DE 6_Delaware_Bay NERRDelaware NERR (St Jones Component) Upstream Isaacs Branch DE 6_Delaware_Bay NERRDelaware NERR (Blackbird Creek 

Component)

Blackbird Landing Road DE 6_Delaware_Bay NERR

Delaware NERR (Blackbird Creek 

Component)

Delon DE 6_Delaware_Bay NERR

Delaware NERR (Blackbird Creek 

Component)

Eagle’s Nest DE 6_Delaware_Bay NERR

Delaware NERR (Blackbird Creek 

Component)

Beaver Branch DE 6_Delaware_Bay NERR

Delaware NERR (St Jones Component) Reserve.Ditch DE 6_Delaware_Bay NERRDelaware NERR (St Jones Component) Trail DE 6_Delaware_Bay NERR
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Dennis, NJ (Delaware Bay) Dennis Creek NJ 6_Delaware_Bay Other Dennis, NJ (Delaware Bay) Dennis Creek NJ 6_Delaware_Bay Other Dennis, NJ (Delaware Bay) Dennis Creek NJ 6_Delaware_Bay Other Downe, NJ (Delaware Bay) Dividing Creek NJ 6_Delaware_Bay Other Downe, NJ (Delaware Bay) Dividing Creek NJ 6_Delaware_Bay Other Downe, NJ (Delaware Bay) Dividing Creek NJ 6_Delaware_Bay Other Bivalve, NJ (Delaware Bay) Maurice River NJ 6_Delaware_Bay Other Bivalve, NJ (Delaware Bay) Maurice River NJ 6_Delaware_Bay Other Bivalve, NJ (Delaware Bay) Maurice River NJ 6_Delaware_Bay Other PRIME HOOK NATIONAL WILDLIFE 

REFUGE

SET_IV_03 DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

SET_IV_02 DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

SET_IV_01 DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

PH2-6 (Deep) DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

PH2-5 (Deep) DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

PH2-4 (Deep) DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

PH2-3 (Deep) DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

PH2-2 (Deep) DE 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

PH2-1 (Deep) DE 6_Delaware_Bay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

PRIME HOOK NATIONAL WILDLIFE REFUGE Set 2 (Deep) DE 6_Delaware_Bay USFWS PRIME HOOK NATIONAL WILDLIFE REFUGE Set 1 (Deep) DE 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE REFUGE Sunray03 NJ 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE REFUGE Sunray02 NJ 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE REFUGE Sunray01 NJ 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE REFUGE Delhaven03 NJ 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE REFUGE Delhaven02 NJ 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE REFUGE Delhaven01 NJ 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE REFUGE Green Creek 03 NJ 6_Delaware_Bay USFWS CAPE MAY NATIONAL WILDLIFE 

REFUGE

Green Creek 01 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Green Creek 02 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Dias Headwaters 03 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Dias Headwaters 02 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Dias Headwaters 01 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Dias Creek01 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Dias Creek02 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Dias Creek03 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Bidwells Headwaters03 NJ 6_Delaware_Bay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Reeds Beach01 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Bidwells Headwaters02 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Reeds Beach02 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Reeds Beach04 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Bidwells Headwaters01 NJ 6_Delaware_Bay USFWS 

CAPE MAY NATIONAL WILDLIFE 

REFUGE

Reeds Beach03 NJ 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET03_AF DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET03_KELL DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET02_AF DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET01_AF DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SB03 DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET02_KELL DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SB02 DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET01_KELL DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SB01 DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET03_Kent DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET01_Kent DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET02_Kent DE 6_Delaware_Bay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

BOMBAY HOOK NATIONAL WILDLIFE REFUGE Set03-BHIS DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE SET02_GI DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE SET01_GI DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE Set01-BHIS DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE SET03_GI DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE Set02-BHIS DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE SET01_BHIN DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE SET02_BHIN_Redo DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE REFUGE Set01_LTHB DE 6_Delaware_Bay USFWS BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET03_BHIN DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET03_LTHB DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET02_LTHB DE 6_Delaware_Bay USFWS 

BOMBAY HOOK NATIONAL WILDLIFE 

REFUGE

SET04_LTHB DE 6_Delaware_Bay USFWS 

SUPAWNA MEADOWS NATIONAL 

WILDLIFE REFUGE

Bald02 NJ 6_Delaware_Bay USFWS 

SUPAWNA MEADOWS NATIONAL 

WILDLIFE REFUGE

Bald03 NJ 6_Delaware_Bay USFWS 

SUPAWNA MEADOWS NATIONAL 

WILDLIFE REFUGE

Bald01 NJ 6_Delaware_Bay USFWS 

SUPAWNA MEADOWS NATIONAL 

WILDLIFE REFUGE

Mud01 NJ 6_Delaware_Bay USFWS 

SUPAWNA MEADOWS NATIONAL 

WILDLIFE REFUGE

Mud03 NJ 6_Delaware_Bay USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

SUPAWNA MEADOWS NATIONAL 

WILDLIFE REFUGE

Mud02 NJ 6_Delaware_Bay USFWS 

PRIME HOOK NATIONAL WILDLIFE 

REFUGE

Set 3 (Deep) DE 6_Delaware_Bay USFWS 

Bombay Hook NWR Bombay.Hook DE 6_Delaware_Bay USGS Bombay Hook NWR Bombay.Hook DE 6_Delaware_Bay USGS Bombay Hook NWR Bombay.Hook DE 6_Delaware_Bay USGS Bombay Hook NWR Bombay.Hook DE 6_Delaware_Bay USGS EA Vaughn EA Vaughn_EAV1-ditched MD 7_Coastal_Delmarva NERR EA Vaughn EA Vaughn_EAV1-ditched MD 7_Coastal_Delmarva NERR EA Vaughn EA Vaughn_EAV1-ditched MD 7_Coastal_Delmarva NERR EA Vaughn EA Vaughn_EA V2-unditched MD 7_Coastal_Delmarva NERR EA Vaughn EA Vaughn_EA V2-unditched MD 7_Coastal_Delmarva NERR EA Vaughn EA Vaughn_EA V2-unditched MD 7_Coastal_Delmarva NERR Assateague Island, MD ASIS.Marsh.5 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.5 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.5 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.5 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.8 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.8 MD 7_Coastal_Delmarva NPS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Assateague Island, MD ASIS.Marsh.8 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.8 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.6 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.6 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.6 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.6 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.11 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.11 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.11 MD 7_Coastal_Delmarva NPS Assateague Island, MD ASIS.Marsh.11 MD 7_Coastal_Delmarva NPS FISHERMAN ISLAND NATIONAL 

WILDLIFE REFUGE

FIE Plot 1 VA 7_Coastal_Delmarva USFWS 

FISHERMAN ISLAND NATIONAL 

WILDLIFE REFUGE

FIE Plot 2 VA 7_Coastal_Delmarva USFWS 

FISHERMAN ISLAND NATIONAL 

WILDLIFE REFUGE

FIE Plot 3 VA 7_Coastal_Delmarva USFWS 

FISHERMAN ISLAND NATIONAL 

WILDLIFE REFUGE

FIW Plot 1 VA 7_Coastal_Delmarva USFWS 

FISHERMAN ISLAND NATIONAL 

WILDLIFE REFUGE

FIW Plot 2 VA 7_Coastal_Delmarva USFWS 

FISHERMAN ISLAND NATIONAL 

WILDLIFE REFUGE

FIW Plot 3 VA 7_Coastal_Delmarva USFWS 

EASTERN SHORE OF VIRGINIA 

NATIONAL WILDLIFE REFUGE

ESV Plot 3 VA 7_Coastal_Delmarva USFWS 

EASTERN SHORE OF VIRGINIA 

NATIONAL WILDLIFE REFUGE

ESV Plot 1 VA 7_Coastal_Delmarva USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

EASTERN SHORE OF VIRGINIA 

NATIONAL WILDLIFE REFUGE

ESV Plot 2 VA 7_Coastal_Delmarva USFWS 

EASTERN SHORE OF VIRGINIA 

NATIONAL WILDLIFE REFUGE

Bull Plot 3 VA 7_Coastal_Delmarva USFWS 

EASTERN SHORE OF VIRGINIA 

NATIONAL WILDLIFE REFUGE

Bull Plot 2 VA 7_Coastal_Delmarva USFWS 

EASTERN SHORE OF VIRGINIA 

NATIONAL WILDLIFE REFUGE

Bull Plot 1 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

Cedar 03 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

Cedar 02 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

Cedar 01 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

BDM3 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

BDM2 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

BDM1 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

APool01 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

APool02 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

APool03 VA 7_Coastal_Delmarva USFWS 

WALLOPS ISLAND NATIONAL 

WILDLIFE REFUGE

Wall 01 VA 7_Coastal_Delmarva USFWS 

WALLOPS ISLAND NATIONAL 

WILDLIFE REFUGE

Wall 02 VA 7_Coastal_Delmarva USFWS 

WALLOPS ISLAND NATIONAL 

WILDLIFE REFUGE

Wall 03 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

SPSM01 VA 7_Coastal_Delmarva USFWS 

CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

SPImp03 VA 7_Coastal_Delmarva USFWS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

CHINCOTEAGUE NATIONAL WILDLIFE REFUGE SPImp01 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE SPSM02 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE SPImp02 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE SPSM03 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE Wild 02 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE Wild 01 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE Wild 03 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE RPSM02 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE REFUGE RPSM01 VA 7_Coastal_Delmarva USFWS CHINCOTEAGUE NATIONAL WILDLIFE 

REFUGE

RPSM03 VA 7_Coastal_Delmarva USFWS 

Watchapreague,VA Watchapreague,VA_Mockhorn West VA 7_Coastal_Delmarva USGS Watchapreague,VA Watchapreague,VA_Mockhorn East VA 7_Coastal_Delmarva USGS Watchapreague,VA Watchapreague,VA_Curlew Bay VA 7_Coastal_Delmarva USGS Watchapreague,VA Watchapreague,VA_Curlew Bay VA 7_Coastal_Delmarva USGS Watchapreague,VA Watchapreague,VA_Curlew Bay VA 7_Coastal_Delmarva USGS Watchapreague,VA Watchapreague,VA_Curlew Bay VA 7_Coastal_Delmarva USGS Watchapreague,VA Watchapreague,VA_Gates Bay VA 7_Coastal_Delmarva USGS Watchapreague,VA Watchapreague,VA_Gates Bay VA 7_Coastal_Delmarva USGS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

VCR - LTER tidal.creek VA 7_Coastal_Delmarva VCR-LTER VCR - LTER low VA 7_Coastal_Delmarva VCR-LTER VCR - LTER mid VA 7_Coastal_Delmarva VCR-LTER VCR - LTER low VA 7_Coastal_Delmarva VCR-LTER VCR - LTER mid VA 7_Coastal_Delmarva VCR-LTER VCR - LTER low VA 7_Coastal_Delmarva VCR-LTER VCR - LTER mid VA 7_Coastal_Delmarva VCR-LTER VCR - LTER hig VA 7_Coastal_Delmarva VCR-LTER VCR - LTER hig VA 7_Coastal_Delmarva VCR-LTER VCR - LTER hig VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_FowlingPoint VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_FowlingPoint VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_FowlingPoint VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_FowlingPoint VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_FowlingPoint VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_FowlingPoint VA 7_Coastal_Delmarva VCR-LTER VCR - LTER tidal.creek VA 7_Coastal_Delmarva VCR-LTER VCR - LTER tidal.creek VA 7_Coastal_Delmarva VCR-LTER 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

VCR - LTER tidal.creek VA 7_Coastal_Delmarva VCR-LTER VCR - LTER tidal.creek VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_ChimneyPole VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_ChimneyPole VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_ChimneyPole VA 7_Coastal_Delmarva VCR-LTER VCR - LTER VCR - LTER_ChimneyPole VA 7_Coastal_Delmarva VCR-LTER Nanticoke River Nanticoke River_1 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_1 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_1 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_2 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_2 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_2 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_3 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_3 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_3 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_4 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_4 MD 8_Eastern_Chesapeake_Bay Academic Institution Nanticoke River Nanticoke River_4 MD 8_Eastern_Chesapeake_Bay Academic Institution 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Monie Bay, MD MCMST2L MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCMST2H MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCMST1L MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCMST3L MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCMST3H MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCMST1H MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCHST3L MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCHST1H MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCHST3H MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCHST1L MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCHST2L MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD MCHST2H MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal2-unditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal2-unditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal2-unditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal1-ditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal1-ditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal1-ditched MD 8_Eastern_Chesapeake_Bay NERR 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Deal Island WMA Deal Island WMA_Deal4-ditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal4-ditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal4-ditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal3-unditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal3-unditched MD 8_Eastern_Chesapeake_Bay NERR Deal Island WMA Deal Island WMA_Deal3-unditched MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD Monie Bay, MD_Monie Creek-unditched MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD Monie Bay, MD_Monie Creek-unditched MD 8_Eastern_Chesapeake_Bay NERR Monie Bay, MD Monie Bay, MD_Monie Creek-unditched MD 8_Eastern_Chesapeake_Bay NERR Saxis WMA Saxis VA 8_Eastern_Chesapeake_Bay USGS Saxis WMA Saxis VA 8_Eastern_Chesapeake_Bay USGS Saxis WMA Saxis VA 8_Eastern_Chesapeake_Bay USGS Saxis WMA Saxis VA 8_Eastern_Chesapeake_Bay USGS Audubon Property- Farm Creek Wetlands Audubon.Property.Fishing.Bay MD 8_Eastern_Chesapeake_Bay USGS Audubon Property- Farm Creek Wetlands Audubon.Property.Fishing.Bay MD 8_Eastern_Chesapeake_Bay USGS Fishing Bay WMA Fishing.Bay.8A MD 8_Eastern_Chesapeake_Bay USGS Fishing Bay WMA Fishing.Bay.8A MD 8_Eastern_Chesapeake_Bay USGS Fishing Bay WMA Fishing.Bay.8A MD 8_Eastern_Chesapeake_Bay USGS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Fishing Bay WMA Fishing.Bay.8A MD 8_Eastern_Chesapeake_Bay USGS Fishing Bay WMA Fishing.Bay.8D MD 8_Eastern_Chesapeake_Bay USGS Fishing Bay WMA Fishing.Bay.8D MD 8_Eastern_Chesapeake_Bay USGS Fishing Bay WMA Fishing.Bay.8D MD 8_Eastern_Chesapeake_Bay USGS Fishing Bay WMA Fishing.Bay.8D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.7A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.7A MD 8_Eastern_Chesapeake_Bay USGS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Blackwater NWR Blackwater.7A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.7A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A31 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A31 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A31 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A31 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A31 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.7D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.7D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.7D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.7D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2A MD 8_Eastern_Chesapeake_Bay USGS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Blackwater NWR BWB_Unit2A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit2C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A10 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A10 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A10 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A10 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1C MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A33 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1B MD 8_Eastern_Chesapeake_Bay USGS 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Blackwater NWR Blackwater.A33 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1B MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit1A MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A33 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A33 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A33 MD 8_Eastern_Chesapeake_Bay USGS Eastern Neck, NWR Eastern.Neck MD 8_Eastern_Chesapeake_Bay USGS Eastern Neck, NWR Eastern.Neck MD 8_Eastern_Chesapeake_Bay USGS Eastern Neck, NWR Eastern.Neck MD 8_Eastern_Chesapeake_Bay USGS Eastern Neck, NWR Eastern.Neck MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR BWB_Unit3D MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A33 MD 8_Eastern_Chesapeake_Bay USGS Blackwater NWR Blackwater.A33 MD 8_Eastern_Chesapeake_Bay USGS Goodwin Island Goodwin Island_Middle Island - Water 

Quality Station

VA 9_Western_Chesapeake_Bay NERR 

Goodwin Island Main Island - Reference Site Transect VA 9_Western_Chesapeake_Bay NERR Goodwin Island Main Island - Reference Site Transect VA 9_Western_Chesapeake_Bay NERR 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Goodwin Island Goodwin Island_Main Island - Thorofare 

Transect

VA 9_Western_Chesapeake_Bay NERR 

Goodwin Island Goodwin Island_Main Island - Thorofare 

Transect

VA 9_Western_Chesapeake_Bay NERR 

Goodwin Island Goodwin Island_Middle Island Transect VA 9_Western_Chesapeake_Bay NERR Goodwin Island Goodwin Island_Middle Island Transect VA 9_Western_Chesapeake_Bay NERR Goodwin Island Goodwin Island_Middle Island Transect VA 9_Western_Chesapeake_Bay NERR Goodwin Island Goodwin Island_Main Island - North 

Transect

VA 9_Western_Chesapeake_Bay NERR 

Goodwin Island Goodwin Island_Main Island - North 

Transect

VA 9_Western_Chesapeake_Bay NERR 

Catlett Island Catlett Island_Inner Site VA 9_Western_Chesapeake_Bay NERR Catlett Island Catlett Island_Inner Site VA 9_Western_Chesapeake_Bay NERR Taskinas Creek Taskinas Creek_Reference Site Transect VA 9_Western_Chesapeake_Bay NERR Catlett Island Catlett Island_Outer Site VA 9_Western_Chesapeake_Bay NERR Catlett Island Catlett Island_Outer Site VA 9_Western_Chesapeake_Bay NERR Taskinas Creek Taskinas Creek_Reference Site Transect VA 9_Western_Chesapeake_Bay NERR Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued

SET_Geographical_Location Site State Sub_Region Partner 

Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC 
Table 2.1. Surface elevation table-marker horizon (SET-MH) data.—Continued SET_Geographical_Location Site State Sub_Region Partner 

Smithsonian Environmental Research Center SERC MD 9_Western_Chesapeake_Bay SERC Western Shore, Cove Point Western Shore, Cove Point_Cove Point MD 9_Western_Chesapeake_Bay Academic Institution Western Shore, Cove Point Western Shore, Cove Point_Cove Point MD 9_Western_Chesapeake_Bay Academic Institution Western Shore, Parkers Creek Western Shore, Parkers Creek_Parkers Creek MD 9_Western_Chesapeake_Bay Academic Institution Western Shore, Parkers Creek Western Shore, Parkers Creek_Parkers Creek MD 9_Western_Chesapeake_Bay Academic Institution Western Shore, Parkers Creek Western Shore, Parkers Creek_Parkers Creek MD 9_Western_Chesapeake_Bay Academic Institution Western Shore, Parkers Creek Western Shore, Parkers Creek_Parkers Creek MD 9_Western_Chesapeake_Bay Academic Institution SERC, MD Hog.Island.SERC MD 9_Western_Chesapeake_Bay USGS SERC, MD Hog.Island.SERC MD 9_Western_Chesapeake_Bay USGS SERC, MD Hog.Island.SERC MD 9_Western_Chesapeake_Bay USGS SERC, MD Hog.Island.SERC MD 9_Western_Chesapeake_Bay USGS 
Appendix 3. Best Model Summaries 117

Appendix 3. Best Model Summaries

Model summaries for the deviation from expected surface elevation model and storm surge submodel using the eligible 

surface elevation table (SET) data (table 3.1 and table 3.2, respectively).

Table 3.1. Summary output for best deviation from expected surface elevation change model (model 15e). Adjusted values for reduced 

effective sample size (170) in parentheses when differs from unadjusted values (n=223).

[<, less than]

Residuals

Minimum 1st quarter Median 3rd quarter Maximum

−47.03 −4.28 −1.65 4.06 55.90

Predictor Estimate Standard error t-value P-value

Intercept −23.90 4.18(4.77) −5.73 (−5.00) <0.0001

Distance 186.16 33.41(38.26) 5.57 (4.87) <0.0001

Distance squared −279.00 54.47(62.38) −5.12 (−4.47) <0.0001

Position 22.39 6.17(7.07) 3.63 (3.17) <0.001 (<0.005)

Distance × Position −103.66 31.91(36.55) −3.25 (−2.84) <0.005 (<0.01)

Residual standard error: 12.04 on 118 degrees of freedom

Multiple R-squared: 0.16

Adjusted R-squared: 0.14 

F-statistic: 10.33 on 54 and 218 DF, p-value: <0.0001

Table 3.2. Summary output for the best storm surge submodel (model 3) using eligible surface elevation table (SET) dataset. Adjusted 

values for reduced effective sample size (156) in parentheses when differs from unadjusted values (n=223).

[<, less than]

Residuals

Minimum 1st quarter Median 3rd quarter Maximum

−2.18 0.00 0.01 0.33 2.68

Predictor Estimate Standard error ztvalue Ptvalue

Intercept 24.41 4.56 (5.45) 5.36 (4.48) <0.0001

Distance −54.53 9.83 (11.75) −5.55 (−4.64) <0.0001

Position −11.68 2.52 (3.01) −4.64 (−3.88) <0.0001 (<0.0005)

Null deviance: 232.288 on 222 degrees of freedom

Residual deviance: 89.249 on 220 degrees of freedom

Akaike’s Information Criteria: 95.249

For additional information, contact:

Director, Patuxent Wildlife Research Center

U.S. Geological Survey

12311 Beech Forest Road

Laurel, MD 20708

or visit our website at:

https://www.usgs.gov/centers/pwrc

Publishing support provided by the West Trenton Publishing 

Service Center
Cahoon and others—Hurricane Sandy Impacts on Coastal Wetland Resilience—Open-File Report 2018–1142

ISSN 2331–1258 (online)

https://doi.org/10.3133/ofr20181142