Forecasting the Impact of Storm Waves and SeaLevel Rise on Midway Atoll and Laysan Island 

within the Papahānaumokuākea Marine National 

Monument—A Comparison of Passive Versus 

Dynamic Inundation Models

Open-File Report 2013–1069

U.S. Department of the Interior

U.S. Geological Survey
FRONT COVER: Photograph showing the impact of a large wave on the south 

shore of Laysan Island, with endangered Laysan teal in the foreground (USGS 

photograph by M. Reynolds).
Forecasting the Impact of Storm Waves and SeaLevel Rise on Midway Atoll and Laysan Island 

within the Papahānaumokuākea Marine National 

Monument—A Comparison of Passive Versus 

Dynamic Inundation Models

By Curt D. Storlazzi, Paul Berkowitz, Michelle H. Reynolds, and Joshua B. Logan

Open-File Report 2013–1069

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director 

U.S. Geological Survey, Reston, Virginia: 2013

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the Earth, its natural and living resources, natural hazards, and the 

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visit http://www.usgs.gov/pubprod

Suggested citation: 

Storlazzi, C.D., Berkowitz, P., Reynolds, M.H., and Logan, J.B., 2013, 

Forecasting the impact of storm waves and sea-level rise on Midway Atoll 

and Laysan Island within the Papahānaumokuākea Marine National 

Monument—a comparison of passive versus dynamic inundation models: 

U.S. Geological Survey Open-File Report 2013-1069, 78 p.

Any use of trade, product, or firm names is for descriptive purposes only and 

does not imply endorsement by the U.S. Government.

Although this information product, for the most part, is in the public domain, it 

also may contain copyrighted materials as noted in the text. Permission to 

reproduce copyrighted items must be secured from the copyright owner.
iii

Contents

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

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

Study Area ..........................................................................................................................................................4

Methods ..............................................................................................................................................................6

Oceanographic and Meteorological Forcing Data..................................................................................6

Wave and Water-Level Models ..................................................................................................................7

Modeled Water Surfaces and Wave-Driven Total Water Levels.........................................................7

Topography and Bathymetry .......................................................................................................................8

Inundation Mapping....................................................................................................................................12

Land Cover and Habitat Delineation ........................................................................................................13

Uncertainty in Inundation Models ............................................................................................................14

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

General Deep-water Oceanographic and Meteorological Forcing ...................................................16

Modeled Waves and Water Levels on the Atolls ..................................................................................17

Inundation Mapping....................................................................................................................................21

Land Cover and Habitat Inundation..........................................................................................................23

Discussion ........................................................................................................................................................27

Conclusions ......................................................................................................................................................30

Acknowledgments ...........................................................................................................................................32

References Cited .............................................................................................................................................33

Additional Digital Information .......................................................................................................................37

Figures

1. Map showing observed trends in sea level between 1993 and 2010...................................................3

2. Schematic diagram comparing passive inundation models with dynamic wavedriven inundation models..........................................................................................................................4

3. Map of the Northwestern Hawaiian Islands in the Papahānaumokuākea Marine 

National Monument....................................................................................................................................5

4. Maps showing the large-scale, coarse-resolution bathymetric grid of Midway used 

in the Delft3D hydrodynamic model ........................................................................................................9

5. Maps showing the small-scale, fine-resolution bathymetric grids surrounding Sand, 

Spit, and Eastern Islands used in the Delft3D hydrodynamic model ..............................................10

6. Maps showing the large-scale, coarse-resolution bathymetric grid of Laysan used 

in the Delft3D hydrodynamic model ......................................................................................................11

7. Map showing the small-scale, fine-resolution bathymetric grid surrounding Laysan 

Island used in the Delft3D hydrodynamic model. ...............................................................................12

8. Plot showing monthly means of wave heights, wave periods, and wind speeds ...........................17

9. Plot of seasonal variations in wave height by wave direction............................................................18

10. Plot of seasonal variations in wave period by wave direction .........................................................19
iv

11. Plot of seasonal variations in wind speed by wind direction............................................................20

12. Plots of the mean variations in significant wave height, peak wave period, and 

mean wavelength and the resulting set-up, top 2 percent run-up, and total wavedriven water levels for the five future sea-level rise (SLR) scenarios relative to 

present sea level during North Pacific winter conditions ................................................................22

13. Plots of the mean variations in significant wave height, peak wave period, and 

mean wavelength and the resulting set-up, top 2 percent run-up, and total wavedriven water levels for the five future sea-level rise (SLR) scenarios relative to 

present sea level during North Pacific summer conditions .............................................................23

14. Map of inundation at Sand Island due to both passive and dynamic sea-level rise 

(SLR) scenarios ........................................................................................................................................24

15. Map of inundation at Spit Island due to both passive and dynamic sea-level rise 

(SLR) scenarios ........................................................................................................................................25

16. Map of inundation at Eastern Island due to both passive and dynamic sea-level 

rise (SLR) scenarios ................................................................................................................................26

17. Map of inundation at Laysan Island due to both passive and dynamic sea-level rise 

(SLR) scenarios ........................................................................................................................................27

18. Plot of percentage of land area inundated due to both passive and dynamic sealevel rise (SLR) scenarios.......................................................................................................................28

19. Plot of percentage of land cover classes inundated on Sand Island due to both 

passive and dynamic sea-level rise (SLR) scenarios .......................................................................29

20. Plot of percentage of land cover classes inundated on Spit Island due to both 

passive and dynamic sea-level rise (SLR) scenarios .......................................................................30

21. Plot of percentage of land cover classes inundated on Eastern Island due to both 

passive and dynamic sea-level rise (SLR) scenarios .......................................................................31

22. Plot of percentage of land cover classes inundated on Laysan Island due to both 

passive and dynamic sea-level rise (SLR) scenarios .......................................................................32

Tables

1. Descriptions of the land cover classes...................................................................................................38

2. Monthly mean wave heights, wave periods, wave directions, wind 

speeds, and wind directions...................................................................................................................38

3. Monthly top 5 percent wave heights, wave periods, wave directions, 

wind speeds, and wind directions for the study area........................................................................39

4. Areal extent and change in area for all islands due to both passive and dynamic 

sea-level rise scenarios ..........................................................................................................................39

5. Areal extent and change in land cover classes on Sand Island due to 

passive sea-level rise scenarios ...........................................................................................................40

6. Areal extent and change in land cover classes on Spit Island due to 

passive sea-level rise scenarios ...........................................................................................................40

7. Areal extent and change in land cover classes on Eastern Island due to passive 

sea-level rise scenarios .......................................................................................................................... 41 
v

8. Areal extent and change in land cover classes on Laysan Island due to 

passive sea-level rise scenarios ........................................................................................................... 41 

9. Areal extent and change in land cover classes on Sand Island due to 

 dynamic sea-level rise scenarios .......................................................................................................... 42 

10. Areal extent and change in land cover classes on Spit Island due to 

 dynamic sea-level rise scenarios .......................................................................................................... 42 

11. Areal extent and change in land cover classes on Eastern Island due to dynamic 

sea-level rise scenarios .......................................................................................................................... 43 

12. Areal extent and change in land cover classes on Laysan Island due to dynamic 

sea-level rise scenarios .......................................................................................................................... 43 

13. Distribution of species by island............................................................................................................. 44 

14. Species habitat use by land cover classes .......................................................................................... 45 

15. Land cover class by island ...................................................................................................................... 46 

 

Appendixes

1. Maps of Significant Wave Height around the Atoll Islands ................................................................47

2. Maps of Combined Effects of Wave-driven Set-up and Run-up 

 around the Atoll Islands ............................................................................................................................. 71 

3. Maps of Land Cover Classes on the Atoll Islands ................................................................................. 75 
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Forecasting the Impact of Storm Waves and Sea-Level 

Rise on Midway Atoll and Laysan Island within the 

Papahānaumokuākea Marine National Monument—A 

Comparison of Passive Versus Dynamic Inundation 

Models 

By Curt D. Storlazzi1 Paul Berkowitz2, Michelle H. Reynolds3, and Joshua B. Logan1

Abstract

Two inundation events in 2011 underscored the potential for elevated water levels to 

damage infrastructure and affect terrestrial ecosystems on the low-lying Northwestern Hawaiian 

Islands in the Papahānaumokuākea Marine National Monument. The goal of this study was to 

compare passive “bathtub” inundation models based on geographic information systems (GIS) to 

those that include dynamic water levels caused by wave-induced set-up and run-up for two endmember island morphologies: Midway, a classic atoll with islands on the shallow (2–8 m) atoll 

rim and a deep, central lagoon; and Laysan, which is characterized by a deep (20–30 m) atoll rim 

and an island at the center of the atoll. Vulnerability to elevated water levels was assessed using 

hindcast wind and wave data to drive coupled physics-based numerical wave, current, and waterlevel models for the atolls. The resulting model data were then used to compute run-up 

elevations using a parametric run-up equation under both present conditions and future sea-levelrise scenarios. In both geomorphologies, wave heights and wavelengths adjacent to the island

shorelines increased more than three times and four times, respectively, with increasing values of 

sea-level rise, as more deep-water wave energy could propagate over the atoll rim and larger 

wind-driven waves could develop on the atoll. Although these increases in water depth resulted 

in decreased set-up along the islands’ shorelines, the larger wave heights and longer wavelengths 

due to sea-level rise increased the resulting wave-induced run-up. Run-up values were spatially 

heterogeneous and dependent on the direction of incident wave direction, bathymetry, and island

configuration. Island inundation was modeled to increase substantially when wave-driven effects 

were included, suggesting that inundation and impacts to infrastructure and terrestrial habitats 

will occur at lower values of predicted sea-level rise, and thus sooner in the 21st century, than 

suggested by passive GIS-based “bathtub” inundation models. Lastly, observations and the 

modeling results suggest that classic atolls with islands on a shallow atoll rim are more 

susceptible to the combined effects of sea-level rise and wave-driven inundation than atolls 

characterized by a deep atoll rim.

 

1

U.S. Geological Survey, Pacific Coastal and Marine Science Center, 400 Natural Bridges Drive, Santa 

Cruz, CA 95060, USA

2

Hawaii Cooperative Studies Unit, University of Hawaii at Hilo, Hawaii National Park, HI 96718, USA

3

U.S. Geological Survey, Pacific Island Ecosystems Research Center, PO Box 44, Hawaii National Park, 

HI 96718, USA
2

Introduction

A number of recent studies (Grinsted and others, 2009; Jevrejeva and others, 2009; 

Merrifield and others, 2009; Milne and others 2009) suggest that not only is global sea-level rise 

(SLR) occurring and accelerating in response to global climate change, but that rapid, meterscale SLR due to ice sheet collapse has occurred in the past (Blanchon and others, 2009). 

Furthermore, syntheses by Grinsted and others (2009) and Nicholls and Cazenave (2010) suggest 

that global mean sea level in 2100 may exceed the average projection by the Intergovernmental 

Panel on Climate Change (2007) of approximately 60 cm above 2000 levels, with some studies 

suggesting extreme (although less likely) rises as high as 200 cm in that time frame (Vermeer 

and Rahmstorf, 2009; Pfeffer and others, 2008; Rahmstorf, 2007). Beyond the year 2100, or 

perhaps sooner according to some scientists, rapid collapses of the Greenland and West Antarctic 

ice sheets could lead to a SLR of many meters (Overpeck and others, 2006). Although coral reefs 

can accrete into the accommodation space provided by sea-level rise over geologic time scales, 

published vertical reef-flat accretion rates for exposed fringing reefs (1–4 mm/yr; see 

Buddemeier and Smith, 1988; Montaggioni, 2005) are as much as an order of magnitude smaller 

than the rates of SLR projected for the years 2000–2100 (8–16 mm/yr; see Grinsted and others, 

2009; Nicholls and Cazenave, 2010). It is therefore likely that projected SLR will outpace 

potential new vertical reef-flat accretion, resulting in a net increase in water depth over exposed 

reef flats on the order of 0.5–2.0 m during the 21st century. 

Satellite observations from 1993 to 2010 (Leuliette, 2012) show global SLR occurring at 

almost double the rate cited in the Intergovernmental Panel on Climate Change (2007) report, 

and above-average rates have been observed in the Northwestern Hawaiian Islands (fig. 1). 

Rising sea levels have the potential to exacerbate the impacts of storms and wave action on 

coastlines and coral reefs by reducing wave-energy dissipation, primarily by reducing wave 

breaking at the reef crest and increasing the water depth relative to hydrodynamic roughness over 

the reef flat (see, for example, Storlazzi and others, 2011). By reducing wave-energy dissipation 

at the reef crest and over the reef flat, SLR will cause larger waves to directly affect the coastline 

and potentially drive coastal erosion. These larger waves at the shoreline increase the potential 

for marine inundation that can extend inland considerable distances. The maximum vertical 

extent of wave-driven inundation is primarily a function of the wave height, wavelength, and 

coastal slope. Because storm wave heights and wavelengths vary in time and space, and coral 

reefs are spatially heterogeneous, wave- and SLR-induced inundation will vary spatially and 

temporally. This variation is particularly large for Pacific Ocean islands and atolls that are 

exposed to waves in excess of 5 m high numerous times each year (U.S. Army Corps of 

Engineers, 2011). On low-lying atolls that typify much of the central and western Pacific Islands, 

a small rise in sea level may cause large horizontal migrations of the shoreline, impacts to 

terrestrial infrastructure, loss of critical terrestrial nesting and foraging habitat, or even complete 

inundation of the atoll islands. 

Although there have been a number of efforts to investigate how reefs may respond to SLR 

(for example, Ogston and Field, 2010; Field and others, 2011; Storlazzi and others, 2011), there 

has been little information presented on how infrastructure and natural resources of atoll islands 

may be affected by changes in sea level. Studies to date that describe SLR threats to atolls (for 

example, Baker and others, 2006; Krause and others, 2012) have generally used passive 

inundation models to simulate flooding of the islands (fig. 2). These passive models, often 

referred to as “bathtub” models, do not project the cumulative effects of SLR and storm-driven 
3

Figure 1. Map showing observed trends in sea level between 1993 and 2010 (Leuliette, 

2012). Note the high rates (>5 millimeters per year, displayed in reds and pinks) 

observed in the central and western North Pacific Ocean, near the northwest end of 

Papahānaumokuākea Marine National Monument. The locations of Midway and 

Laysan are denoted with black circles. 

waves on the adjacent terrestrial landforms, infrastructure, and natural resources. Although 

passive inundation represents an important element of SLR, islands are likely to be affected by a 

broader, more complex, and interrelated set of processes, including the following: loss of land 

due to erosion; island migration, breaching, and segmentation; wetland drowning, accretion, or 

migration; saltwater intrusion; and increased frequency of storm flooding (Gesch and others, 

2009). The unique characteristics of a particular location affect the relative importance of each of 

these processes. More comprehensive modeling techniques that consider sediment transport, 

morphological changes to the island, currents, stratified and density-driven flows, and salt-water 

intrusion require additional data, including substrate analyses, grain size, current measurements, 

and detailed hydrodynamic roughness (Deltares, 2012). 

This study explores the combined effect of SLR and storm-induced wave events for Laysan 

Island and Midway Atoll’s Sand, Spit, and Eastern Islands within the Northwestern Hawaiian 

Islands. Wave and water-level model simulations under the present conditions and four SLR 

scenarios were used to map inundation and provide estimates of potential impacts to 

infrastructure and natural resources. These dynamic SLR model estimates that include wavedriven set-up and run-up are compared to passive SLR estimates to understand the relative 

importance of these processes on inundation and impacts to terrestrial habitats on Laysan Island 

and Midway Atoll’s Sand, Spit, and Eastern Islands. By providing information on the range of 

forcing parameters (for example, SLR scenario, wave climate) that may threaten habitats, 

wildlife, and infrastructure, this study will help managers to prepare for possible climate-change 

scenarios and extreme weather events. 
4

Figure 2. Schematic diagram comparing passive inundation models (also known as 

“bathtub” models; top panel) with dynamic wave-driven inundation models that 

incorporate wave-driven water levels (bottom panel). Most SLR models employ 

passive inundation modeling techniques, while the dynamic inundation model 

presented here includes wave-driven water levels. 

Study Area

Laysan Island and Midway Atoll’s Sand, Spit, and Eastern Islands are part of the 

Northwestern Hawaiian Islands (NWHI) and lie in the Papahānaumokuākea Marine National 

Monument (PMNM). PMNM is the largest conservation area in the United States and 

incorporates small islands, atolls, submerged banks, and reefs (fig. 3). The diverse ecosystems of 

the NWHI support 21 breeding seabirds and 17 terrestrial breeding species listed as endangered, 

threatened, or species of concern by the U.S. Fish and Wildlife Service, State of Hawaii, or 

International Union for Conservation of Nature (Krause and others, 2012). 
5

Figure 3. Map of the Northwestern Hawaiian Islands (NWH) in the 

Papahānaumokuākea Marine National Monument. Midway Atoll at the northwestern 

end of the island chain is located between Kure and Pearl and Hermes Atolls; 

Laysan is in the middle of the Northwestern Hawaiian Islands between the 

Northhampton Seamounts and Maro Reef. Image from the Pacific Islands Benthic 

Habitat Mapping Center (2011). The location where the U.S. Army Corps of 

Engineers’ Wave Information System (2011) wave hindcast data were generated 

(28°00’N, 174°00’W) would be under the second “e” in the label for “Hermes Atoll.”

Midway (28 ̊11–16’ N and 177 ̊18–25’ W) is a coral atoll situated between Kure Atoll to 

the west-northwest and Pearl and Hermes Atoll to the east-southeast. Midway Atoll comprises 

three islands: Sand (mean and maximum elevations = 3.2 m and 11.7 m, respectively), Spit 

(mean and maximum elevations = 1.5 m and 2.4 m, respectively), and Eastern (mean and 

maximum elevations = 2.6 m and 7.5 m, respectively). Sand and Eastern Islands have been 

significantly altered by human activity since the early 1900s (McDermond and Morgan, 1993). 

Under the jurisdiction of the United States since 1903, Midway has been occupied since the 

Commercial Pacific Cable Company began constructing cable houses and residences (Bryan, 

1938). As a national defense facility, the islands experienced significant development, including 

seawalls, a harbor, piers, runways and other paved surfaces, dredge and fill operations, species 

introductions, and numerous buildings constructed from the 1930s to 1990s. In 1993 the Midway 
6

Naval Air Station was decommissioned, and in 1996 jurisdiction over Midway was transferred to 

the U.S. Department of Interior as a National Wildlife Refuge (Speulda-Drews, 2010). 

Laysan Island (25 ̊41–54’ N and 171 ̊36–53 W) is situated between Lisianski Island to the 

west-northwest and Maro Reef to the east-southeast. Laysan is the second largest land mass in 

the Northwestern Hawaiian Islands and has mean and maximum elevations of 3.9 m and 10.4 m, 

respectively. Laysan lies approximately 1,600 km northwest of Honolulu and 700 km southeast 

of Midway Atoll. Laysan contrasts sharply with the lower lying open and closed atolls in the 

region, having substantially more emergent land (412.0 hectares [ha], including the hypersaline 

lake basin) than most islands within the monument, the largest natural lake in the Hawaiian 

Islands, and less lagoon/insular shelf habitat (approximately 57 km2

 of habitat less than 100 m 

water depth) than any nearby island or atoll. Guano miners in the early 1900s introduced rabbits 

and other mammals to Laysan Island, devastating the flora and fauna (Olson, 1996). Laysan has 

been protected as a bird reserve since 1909, introduced mammals have been extirpated, and the 

island has no infrastructure besides a small field camp.

Methods

The potential impact of SLR and inundation from ocean surface gravity waves (wind waves 

and swell) on Laysan Island and Midway Atoll’s Sand, Spit, and Eastern Islands were 

investigated quantitatively using a suite of physics-based, numerical wave and water-level 

models driven by historical hindcast data and projected values of SLR. 

Oceanographic and Meteorological Forcing Data

There are a very large number of potential combinations of storm sources, so deep-water 

storm waves generated by specific storms were not modeled in this study. Rather, a number of 

simulations of varying wave height and wave period were developed around the primary wave 

sources for the area (North Pacific swell, trade-wind waves, and South Pacific swell). There is a 

lack of wave buoys with long records for the areas of interest. Accordingly, hourly U.S. Army 

Corps of Engineers’ Wave Information System (2011) model hindcast wind and wave data from 

1981 to 2004 for a location (28°00’N, 174°00’W) approximately 330 km east of Midway and 

375 km northwest of Laysan were used. These data sets were analyzed for end-member (top 5 

percent) storm conditions based on the 24 years of available Wave Information System (WIS) 

hourly hindcast data, using methodology presented by Storlazzi and Wingfield (2005) and 

Storlazzi and Reid (2010). The top 5 percent of monthly data was chosen because it represents 

those conditions exceeded 36 hours per month and most likely to coincide with a high tide and 

thus be representative of maximum water-level conditions that would be experienced in a given 

year. These different sets of conditions constrained the combinations of deep-water wave 

heights, wave periods, and wave directions above which possible damage to infrastructure and 

natural resources may occur under historical wind and wave forcing conditions. Existing 

forecasts of how the wind and wave climate in the study areas of the northern Pacific Ocean may 

be affected by climate change (Caires and others, 2006; Mori and others, 2010) are not in firm 

agreement on the seasonality and magnitude of the resulting change. Because of such lack of 

agreement, this study does not take into account any possible future change in the wind and wave 

climate. Because of the large range of conditions and SLR scenarios, the data presented here are 

constrained to the two end-members: North Pacific winter conditions and summer conditions 

(which include the time periods when the islands are exposed to trade-wind waves and South 

Pacific swell). The conditions that typified the spring and fall seasons fell between these two 

end-members.
7

Wave and Water-Level Models

The WIS hindcast deep-water ocean surface gravity waves (wind waves and swell) and 

winds were used as boundary conditions to drive simulations of storm waves and water levels at 

Sand, Spit, Eastern, and Laysan Islands using the Deltares Delft3D hydrodynamic model. Delft3D 

simulates currents and water levels via the Delft3D-FLOW module, which is coupled to the thirdgeneration SWAN wave model using the Delft3D-WAVE module. The SWAN model is based on 

discrete spectral action balance equations, computing the evolution of random, short-crested 

waves (Holthuijsen and others, 1993; Booij and others, 1999; Ris and others, 1999). Physical 

processes such as bottom friction and depth-induced breaking, and nonlinear quadruplet and triad 

wave-wave interactions are included. Wave propagation, growth, and decay from deep-water 

sources and in situ wind-wave growth are solved periodically throughout the model grid. The 

SWAN model has been shown to accurately model the propagation and breaking of waves over 

Pacific coral reefs (Lowe and others, 2009; Hoeke and others, 2011; Storlazzi and others, 2011). 

The results of the SWAN wave simulations, such as significant wave height (Hs), peak spectral 

period (Tp), mean wave direction (θwave), wind speed (Uw), mean wind direction (θwind), and mass 

fluxes (wave-driven water levels such as set-up, the additional elevation of the water level due to 

the effects of transferring wave-related momentum to the surf zone) are stored on the grid, with 

the wave-driven water levels coupled between the SWAN model and Delft3D-FLOW module, 

thus providing updated water levels over which to compute the updated wave fields. 

Most of the standard Delft3D model settings were used. The SWAN model space had a 

frequency range of 0.05–1.00 Hz in 24 frequency bins over 36 (10°) directional bins. Processes 

incorporated in the model included radiation stress forcing, wave set-up, depth-induced breaking 

using the Battjes and Janssen (1978) formulation (α = 1.0, γ = 0.78), nonlinear triad interactions, 

wind-wave growth, and whitecapping using the Komen and others (1984) formulation. Wave 

propagation in spectral space included both refraction and frequency shift. Based on the results 

presented in Hoeke and others (2011), a wave hydraulic roughness length scale of 0.1 m was used 

for the entire model domains in the Madsen and others (1988) formulation for bottom friction. 

The Delft3D-FLOW module that was coupled with the SWAN wave model was run with open 

water-level boundaries with a reflection parameter of 0 s2 and the boundaries defined by 

astronomic forcing. Because the goal was to determine the influence of wave-driven forcing over 

the course of wave events that generally occur on time scales of 12–24 hours, the contribution 

from subdiurnal tidal constituents was deemed not important, and thus the simulations were run 

with sea level set to zero and with the vertical datum of the grids defined by mean higher water 

(MHW). To do this, the astronomical forcing had an M2 tidal amplitude and phase of 0 m and 0°, 

respectively, and the water level was adjusted for the SLR simulation by defining an A0 tide 

amplitude (0.00 m, +0.50 m, +1.00 m, +1.50 m, and +2.00 m) with 0° phase. The background 

horizontal eddy viscosity was set at 1 m2

/s, free wall roughness slip conditions were used, the 

stress formulation due to waves followed the Fredsoe (1984) methodology, and a uniform 

Madsen and others (1988) wave hydraulic roughness length scale of 0.1 m was used, following 

Hoeke and others (2011). The results from the larger, outer domains for both the SWAN and 

Delft3D-FLOW modules that covered the entire atolls were used as boundary input into the finer 

scale, smaller sized domains in the SWAN and Delft3D-FLOW modules around the atoll islands.

Modeled Water Surfaces and Wave-Driven Total Water Levels

The SWAN model was used to generate input parameters for computations of wave run-up 

(the maximum vertical reach of wave uprush on a shore). The SWAN output parameters include 
8

wave height, wavelength, and wave-induced set-up (for example, a rise in mean water level 

inshore of the initial point of wave breaking). For each grid cell, these parameters were extracted 

for present sea level (+0.00 m) and four future SLR scenarios (+0.50 m, +1.00 m, +1.50 m, and 

+2.00 m), as defined on the basis of studies and projections from the Intergovernmental Panel on 

Climate Change (2007), Grinsted and others (2009), and Nicholls and Cazenave (2010) and 

similar to the prescribed scenarios for the 2009 sea-level risk assessment for Department of 

Defense (DoD) coastal installations (for example, Mickler, 2009). Using the extracted wave 

height and wavelength data, wave run-up heights were computed with the methodology of 

Stockdon and others (2006). For each computational grid cell, the wave-induced set-up, wavedriven run-up heights, and SLR values were combined into total water elevations and then 

projected on the islands’ slopes along shore-normal transects. 

Topography and Bathymetry

As input to the wave inundation models, seamless nested topographic/bathymetric grids of 

differing scales were created. The larger, outer atoll grids covered a broad area surrounding the 

entire atoll to water depths of 3,000 m and had coarser spatial resolutions or grid cell sizes, and 

the finer grids encompassed the islands plus the surrounding waters and had higher spatial 

resolution. Midway Atoll’s grid had 451 (east-west) x 401 (north-south) cells at 50-m resolution 

(fig. 4), the Sand Island grid had 420 (east-west) x 350 (north-south) cells at 20-m resolution, 

and the Spit and Eastern Islands’ grid had 325 (east-west) x 225 (north-south) cells at 20-m 

resolution (fig. 5). Laysan atoll’s grid had 501 (east-west) x 351 (north-south) cells at 100-m 

resolution (fig. 6), and the Laysan Island grid had 258 (east-west) x 333 (north-south) cells at 20-

m resolution (fig. 7). 

For Midway Atoll, a 1/3 arc-second (~10 m) integrated bathymetric–topographic digital 

elevation model (DEM) had been compiled previously by Grothe and others (2010) as boundary 

information to model tsunami generation, propagation, and inundation. For Laysan, extensive 

preprocessing was required to generate integrated bathymetric–topographic DEMs from a wide 

range of data sources and formats, including the following: bathymetric gridded data from the 

Pacific Island Benthic Habitat Mapping Center (2011), synthesized grids from IKONOS satellite 

imagery (in depths of <16 m) and multibeam sonars (in depths of 20–5,000 m); raster and 

electronic navigational charts from the Office of Coast Survey (2011); bare-earth 1-m DEM data 

derived from photogrammetric methods by PhotoSat Information Ltd. (2010, unpublished); and a 

digitized coastline based on a May 18, 2010, WorldView-2 satellite photo from DigitalGlobe Inc. 

(2010, unpublished). When two or more data sources covered the same area, the less reliable 

sources were excluded from analysis. In general, older navigational chart data were used only to 

fill in data gaps in the newer IKONOS-derived and multibeam sonar data. After converting all 

depths and elevations to a common datum, the two grids were generated using geostatistical 

kriging techniques (Childs, 2004) in ArcGIS (Environmental Systems Research Institute, 2010). 

For more detailed maps of the islands’ topography based on airborne lidar surveys, please see 

Krause and others (2012).

The methodology and bathymetric grids presented here reflect the current state of the reefs 

without future reef accretion. Reef accretion was not included in this study because no data exist 

for the study areas and published vertical reef flat accretion rates for reef flats exposed to openocean storm waves (1–4 mm/yr; see Buddemeier and Smith, 1988; Montaggioni 2005) such as 

Laysan and Midway are very small compared with the rates of projected SLR until 2100. 

(including wave set-up and run-up) assigned to coastal points spaced 20 m apart. For each SLR 

scenario, wave-driven inundation was projected inland from each coastal point along shore- 
9

Figure 4. Maps showing the large-scale, coarse-resolution bathymetric grid of Midway 

used in the Delft3D hydrodynamic model. The top image shows the bathymetry of 

the entire atoll by focusing on a greater depth range; the bottom image shows the 

bathymetry of the atoll’s top by focusing on a shallower depth range. 

normal transects oriented in a direction perpendicular to coastal segments drawn as regression 

lines based on the location of each coastal point and its 10 nearest neighbors (5 to each side). 

Orthogonal transects were defined to run in the direction of the negative reciprocal of the 
10

Figure 5. Maps showing the small-scale, fine-resolution bathymetric grids surrounding 

Sand, Spit, and Eastern Islands used in the Delft3D hydrodynamic model. The top 

image shows the bathymetry surrounding Sand Island; the bottom image shows the 

bathymetry surrounding Spit and Eastern Islands.

regression slope. For each scenario, the combined SLR and wave-driven inundation heights were 

projected orthogonally upslope from each coastal point until land elevations exceeded combined 

water heights, with the highest point reached on each shore-normal transect representing the high 
11

Figure 6. Maps showing the large-scale, coarse-resolution bathymetric grid of Laysan 

used in the Delft3D hydrodynamic model. The top image shows the bathymetry of 

the entire atoll by focusing on a greater depth range; the bottom image shows the 

bathymetry of the atoll’s top by focusing on a shallower depth range.

water mark. The extent of inundation was then delineated by connecting the high water marks 

from adjacent transects on each of the four islands. 
12

Figure 7. Map showing the small-scale, fine-resolution bathymetric grid surrounding 

Laysan Island used in the Delft3D hydrodynamic model. 

Inundation Mapping

In order to map inundation on the islands, the modeled SLR and wave-driven water-level 

surface (20-m grid format) was linked to the atoll islands’ coastlines using nearest neighbor 

techniques (Environmental Systems Research Institute, 2010), with the nearest inundation values 

As a refinement to the above method, to model inundation of the three major depressions 

on Laysan, water was modeled to flow into these basins if they were adjacent to inundated 

transects, hydrologically connected, and at lower elevations than the inundated transects. While 

the models produce run-up elevations, they do not estimate run-up volumes; therefore, the 

volume of run-up that is likely to flow into adjacent topographic depressions is unknown. Thus 

in depicting the extent of inundation for SLR scenarios on Laysan, the initial inundation patterns 

were mapped as wave inundation propagates onshore, representing a transient state before run-up 

volumes flow laterally into adjacent depressions. Based on the long average duration of storms 

(>6 hours) and high frequency of swash motions (order ~5–360 times/hour) relative to hydraulic 
13

conductivities (<0.0001 m/s; Hunt and Peterson, 1980), it was assumed that on the time-scale of 

storm-wave-driven inundation events, infiltration is approximately nonexistent. Thus the 

maximum extent of inundation was delineated as if run-up volumes were unlimited and no 

infiltration occurred. This allowed seawater to fill Laysan’s topographic lows (terrestrial basins 

in the islands’ DEMs) during storm events. 

For both the passive and dynamic wave-modeling approach, inundation extents were 

analyzed and mapped within an ArcGIS framework for all five SLR scenarios (+0.00 m, +0.50 

m, +1.00 m, +1.50 m, and +2.00 m). The passive approach represents a reference level and 

depicts the amount of inundation due to SLR only, while the dynamic approach considers the 

additional effect of wave-driven set-up and run-up from the average of the top 5 percent winter 

and summer events in the U.S. Army Corps of Engineers (2011) data set. As mentioned above, 

all inundation maps depict flooding under the worst-case daily scenario (for example, at mean 

high water [MHW], defined as the average of all high water heights over a 19-year National 

Tidal Datum Epoch, the period of time that includes most tidal variation due to lunar and solar 

forces).

Land Cover and Habitat Delineation

Land cover on Midway Atoll was classified using WorldView-2 satellite imagery collected 

during 2011; Laysan Island’s land cover was classified using WorldView-2 satellite imagery 

from 2010. To classify satellite imagery digitally, the IsoCluster unsupervised classification tool 

in ArcGIS (Environmental Systems Research Institute, 2010) was used; this tool classifies pixels 

based on color, texture, tone, pattern, and associated information (Xie and others, 2008). Where 

field mapped land cover data were available from the U.S. Fish and Wildlife Service (USFWS), 

these were incorporated (USFWS unpublished data, 2007; Cornett and others, 2008; Boyd and 

others, 2009; Kristof and others, 2011). 

Remotely sensed and field mapped land cover on Midway Atoll and Laysan Island was 

classified into categories, including six vegetation classes (tree/shrub, mixed shrub, 

grass/herbaceous cover, vine/ground cover, partially vegetated overgrown runways, and wetland 

vegetation), four unvegetated areas (bare ground, hard pan, beach, and wetland), and human 

infrastructure (including active runways, roads, and structures). Not all land cover classes appear 

on the different ecosystems of each island, and species composition may vary within land cover 

vegetation classes between islands. Definitions for land cover classes are provided in table 1, 

which lists some, but not all, of the dominant plant species identified in each land cover class. 

Plant species were described from Wagner and others (2012) and multiple botanical reviews for

Midway Atoll (Starr and Martz, 1999; Klavitter, 2006; Starr and others, 2006; Starr and others, 

2008) and Laysan Island (USFWS, written commun., 1999; Kristof and others, 2011). A rigorous 

quantitative accuracy assessment of the vegetation composition was not possible owing to the 

logistical constraints of collecting ground-truth data on remote islands. The accuracy assessment 

of remotely sensed land cover classification included visual inspection and comparison with 

other available mapping data, field reports, and past botanical surveys (Starr and Martz, 1999a; 

Starr and Martz, 1999b; Starr and others, 2001; Klavitter, 2006; Starr and others, 2006; Starr and 

others, 2008). Expert opinions from USFWS field biologists were solicited for general 

classification accuracy of Laysan Island (E. Flint, T. Speetjens, and M. Stelmach). 

Land cover classes were designated as habitat for wildlife on the basis of species-specific 

nesting (or pupping) behavior known from each island. Potential inundation to wildlife habitats 

was described as the sum of all utilized land cover classes typically used by each species for 

breeding or nesting habitat without differentiating between vertical habitat structures within land 
14

cover classes. For example, tree/shrub landcover was quantified equally for Great Frigatebird, 

which nest on top of trees and shrubs, and Red-tailed Tropicbird, which nest on the ground 

beneath trees and shrubs. Wetlands were not included as suitable nesting habitat for wildlife, but 

this land cover is important foraging habitat and a source of water for endemic passerines, 

waterfowl, and migratory shore birds. The distribution of breeding wildlife on the four islands of 

this study and the habitats typically used were compiled from site visits, literature, and personal 

communication with USFWS managers (Poole, 2012; John Klavitter, USFWS, oral commun. 

2011; also see Reynolds and others, 2012). 

By overlaying the predicted inundation patterns with the remotely sensed land cover maps 

defined here, it was possible to estimate the amount of wildlife habitat likely to be inundated by 

SLR and wave-driven processes. However, the potential land cover change from SLR could be 

predicted using two different vegetation response models: (1) a static vegetation response model, 

in which SLR occurs at a rate that outpaces vegetation regeneration, and (2) a dynamic 

vegetation response model, in which land cover shifts upslope of SLR inundation via replanting 

or natural succession. The static vegetation response model used here predicts that land cover 

does not shift upslope as water levels rise but, rather, the inundated land cover is lost. In contrast, 

the dynamic vegetation response model assumes vegetation will regenerate toward higher 

elevations as sea levels rise, “migrating” from one elevation to the next, following the methods 

described by LaFever and others (2007). Krause and others (2012) suggested that Sand, Eastern, 

and Laysan Islands require additional adaptive models to improve predictions of dynamic inland 

vegetation change. Because vegetation response models have not been developed for these 

ecosystems, only the simpler static vegetation response models were applied in this study of 

Midway Atoll and Laysan Island. 

Uncertainty in Inundation Models 

Three sources of uncertainty affect the vertical accuracy of the inundation models 

presented here: (1) uncertainty in tidal elevations, (2) uncertainty in topographic elevations, and 

(3) uncertainty in wave-driven set-up and run-up values. For Laysan Island, a robust tidal datum 

does not exist because there is no tide gauge on the island. Thus, without many alternatives, the 

National Oceanic and Atmospheric Administration (2011a) predicted tide of –0.065 m relative to 

mean sea level (MSL) at the moment when the stereo-pair images were captured was used as a 

reference elevation, and the MSL tidal datum was defined relative to this level. The accuracy of 

the predicted tides at Laysan Island is unknown because there has never been verification. 

However, given the small tidal range in the Central Pacific, the relatively flat tidal levels within 6 

hours of the time of the photos (<0.10 m range), and the small deviations between predicted and 

verified tides at Midway Atoll within 12 hours of the photo time (0.07 m), it would be expected 

that National Oceanic and Atmospheric Administration’s predicted tide relative to predicted 

MSL would be within 0.10 m of the actual tide relative to actual MSL. This uncertainty estimate 

expresses the relative difference between predicted tidal stage and actual tidal stage (for 

example, predicted tide relative to predicted MSL versus actual tide relative to actual MSL), not 

the absolute accuracy of the predicted tide relative to an ellipsoid, geoid, or other fixed surface. 

For Midway Atoll, less tidal uncertainty exists because Sand Island has both predicted and 

verified tides (National Oceanic and Atmospheric Administration, 2011a). 

The uncertainty in topographic elevation on Laysan was estimated using 27 survey-grade 

(>cm accuracy) Global Positioning System (GPS) points collected in 2011 (National Oceanic 

and Atmospheric Administration, 2011b). National Oceanic and Atmospheric Administration

surveyors located survey points in flat, open areas to ensure that horizontal uncertainty did not 
15

have a major effect on vertical accuracy. The root-mean squared error (RMSE) between the 

elevations provided in PhotoSat Information Ltd.’s (2010, unpublished) DEM and the 27 survey 

points was 0.32 m. Using the same validation procedures for Midway Atoll, the RMSE was 

computed as 0.39 m. 

Lastly, sensitivity analysis of the input parameters to the wave inundation model indicate 

that modeled wave height and wave period were within less than 2 percent of the mean values 

for wave height and wave period, while the standard deviation in beach slope was approximately 

2 percent. The resulting mean error in run-up was 0.11 m. Since these uncertainties (expressed as 

standard deviation [SD]) are uncorrelated, they can be combined into an overall uncertainty term 

(Coastal Services Center, 2010): 

SDTotal = (SDTidal

2

+ SDTopography

2

+ SDRun-up

2

)

0.5

From the uncertainty estimates above, the overall vertical uncertainty or RMSE was 

computed to be 0.35 m for Laysan. The comparable calculation for Midway yielded a RMSE of 

0.41 m. These vertical uncertainties have a variable effect on horizontal inundation extent, 

depending on topography: areas with gradual slopes will exhibit more horizontal uncertainty than 

areas with steep slopes. Inundation extents or boundaries can be created from data of any quality 

and are not sensitive to accuracy, although data accuracy determines the area of confidence 

around inundation boundaries (Coastal Services Center, 2010). The National Oceanic and 

Atmospheric Administration uses a value of 80 percent confidence as the threshold between high 

and low confidence. By definition, the Z-score at the inundation boundary equals zero, with the 

probability of inundation on this boundary equaling 50 percent. At elevations above the 

inundation boundary, the probability of inundation decreases according to the normal probability 

distribution, such that a location +0.84 SDs above the inundation level has a 20 percent

probability of inundation (or 80 percent probability of being dry). Similarly, a location -0.84 SDs 

below the inundation level has an 80 percent probability of inundation (or 20 percent probability 

of remaining dry). Between these two thresholds lies an area of low confidence (<80 percent), 

while beyond these thresholds lie areas of high confidence (≥80 percent). 

In terms the modeled results, none of the projected inundation boundaries are biased by 

positional uncertainty, although the true position of the boundary may be higher or lower given 

the uncertainty in the model. For all SLR scenarios under consideration, if the desire was to 

maintain 80 percent confidence that the inundation boundary would remain dry, then as a 

precaution, +0.29 m of elevation on Laysan (0.84 x RMSE) would need to be added to the flood 

surface and the horizontal boundary allowed to adjust accordingly. For Midway Atoll, the 

comparable increment of elevation to add would be +0.34 m. Although one could adopt such a 

precautionary approach, it was decided to analyze inundation extent using only unbiased 

inundation boundaries. Because multiple scenarios of SLR were modeled and a range of 

inundation boundaries were presented, the effects of uncertainty on inundation extent are 

relatively easy to visualize by examining the changes in inundation extent as a result of different 

increments of SLR. 

The run-up elevations determined using the Stockdon and others (2006) methodology is 

very dependent on the local coastal slope and assumes a relatively uniform beach slope from the 

upper shoreface to the back-beach dune system. A steep beachface up to a berm crest that is

backed by a relatively low-slope back beach can result in a rather long projected inundation zone 

that progresses inland until the inundation transect intersects a point on the island’s topography 

where elevation exceeds the run-up calculated using the Stockdon and others (2006) 

methodology. Such cases would tend to over-predict the distance inland, and thus the potential 
16

area inundated, along the given transect. Stating this, however, the Stockdon and others (2006) 

methodology would correctly predict run-up to exceed the berm crest, and seawater would then 

spread out inland and alongshore from the location where the elevation of the berm crest was 

breached. Because the procedures used to project run-up inland do not take this lateral spreading 

into account (except for the major basins on Laysan), it thus under-predicts the potential 

inundation into adjacent transects. It is not clear how these two procedural issues with projecting 

and mapping inundation may offset one another. Friction, which would limit run-up distances, 

was not accounted for in the longer run-up trajectories; similarly, scour, which would increase 

the potential run-up distances (see, for example, Fletcher and others, 1995), was not accounted 

for in the simulations. Furthermore, these modeling efforts also assume constant meteorological 

and atmospheric forcing that drives the waves and run-up, which, as discussed earlier, may be 

different in the future owing to global climate change. Because of the low confidence level of 

existing projections, however, it was not possible to accurately predict the future change to wind, 

waves, and the resulting wave-driven inundation. Lastly, although Webb and Kench (2010) 

suggest that atoll island morphology has shown little response to the +0.3 m of SLR over the past 

50 years, it is not clear how island morphology may respond to much higher SLR scenarios (for 

example, +1.00 m, +1.50 m, and +2.00 m modeled here). These issues, together with the lack of 

understanding of how the islands’ hydrogeology may change under future climate change 

scenarios, result in the presentation of the inundation extents and associated changes in land 

cover classes and habitats discussed in the following sections not as exact values, but rather as 

relative values to be compared to one another for the different SLR models and SLR scenarios.

Results

General Deep-water Oceanographic and Meteorological Forcing

The WIS hindcast data for deep-water ocean surface waves and wind show both seasonal 

and spatial trends for the study area, as shown in figures 8–11 and listed in tables 2–3. Monthly 

mean wave heights, periods, and directions range from 1.80 m to 4.61 m, 9.5 s to 12.5 s, and 4°

to 354°, respectively. Monthly top 5 percent wave heights and their periods and directions range 

from 2.96 m to 8.99 m, 8.9 s to 15.3 s, and 4° to 359°, respectively. Monthly mean wind speeds 

and directions range from 5.6 m/s to 9.5 m/s and 16° to 264°, respectively. Monthly top 5 percent 

wind speeds and their directions range from 10.1 m/s to 17.6 m/s and 36° to 319°, respectively. 

Not only are the wave heights, wave periods, and wind speeds greatest during the winter months, 

but they are also then the most variable, with episodic high-energy conditions during winter 

storms punctuating more frequent, lower energy periods characterized by trade or variable winds. 

Although the waves are relatively unidirectional from the northwest during the winter (figs. 9-

10), the winds are almost evenly distributed around the islands (fig. 11), reflecting the passage of 

shear lines and weather fronts through the area. During the summer months, both the waves and 

winds are relatively unidirectional and appear primarily controlled by trade-wind patterns. Of 

note is the infrequent contribution of waves of low height but long period out of the south during 

the summer, likely due to storms in the Southern Ocean during the southern hemisphere’s winter. 

From these data, two wave and wind end-members (top 5 percent) were used as boundary 

input into the Laysan and Midway models. Winter conditions with very large North Pacific 

winter swell and storm winds were defined as having significant wave height (Hs

) of 8.53 m, a 

peak wave period (Tp) of 15.0 s, a mean wave direction (θwave) of 307°, a wind speed (Uw) of 16.9 

m/s, and a mean wind direction (θwind) of 273°. High-end summer conditions characterized by 
17

Figure 8. Time series plot showing monthly means and 1-standard deviation error bars 

of wave heights, in meters, wave periods, in seconds, and wind speeds, in meters 

per second, based on U.S. Army Corps of Engineers (2011) hindcast data for the 

years 1981–2004 at 28° 00’ N, 174° 00’ W. Blue represents all of the data; red 

represents the top 5 percent of the data.

relatively (for trade-wind conditions) large trade-wind waves and winds were defined as having a 

significant wave height (Hs

) of 3.00 m, a peak wave period (Tp) of 9.8 s, a mean wave direction 

(θwave) of 71°, a wind speed (Uw) of 10.4 m/s, and a mean wind direction (θwind) of 77°. 

Modeled Waves and Water Levels on the Atolls

Maps showing the spatial variation in modeled significant wave height (H, in meters) 

output by the Delft3D model for the four atoll islands under both winter and summer conditions 

are presented in appendix 1. A synthesis of the mean and variability in changes in waves and the 

resulting water levels from around the four islands are shown in figures 12 and 13 for North 
18

Figure 9. Directional plot of seasonal variations in wave height, in meters, by wave 

direction, in compass orientation, based on U.S. Army Corps of Engineers (2011) 

hindcast data for the years 1981–2004 at 28° 00’ N, 174° 00’ W. Radial 

axis, frequency of occurrence, in percent, increase outward from the center of the 

plot.

Pacific winter conditions and summer trade-wind conditions, respectively. As discussed earlier, 

most reef crests and reef flats are depth-limited for waves, in that wave heights are limited to a

fraction of the water depth. Thus, as water depth increases with SLR over the atolls’ reef flat, it 

allows for larger waves to propagate onto or develop on the reef flat. On average, wave heights 

around the atoll islands’ shorelines for both winter and summer conditions are approximately 0.4 

m to 0.5 m higher than at present with +1.0 m of SLR and approximately 0.9 m to 1.0 m higher 

with +2.0 m of SLR. There are no definite mean trends in wave period around the islands during 
19

Figure 10. Directional plot of seasonal variations in wave period, in seconds, by wave 

direction, in compass orientation, based on U.S. Army Corps of Engineers (2011) 

hindcast data for the years 1981-2004 at 28° 00’ N, 174° 00’ W. Radial 

axis, frequency of occurrence, in percent, increase outward from the center of the 

plot.

winter conditions that are characterized by longer period swell from the northwest, but wave 

periods during summer conditions that are characterized by shorter period waves from the 

northeast are, on average, 1 s shorter with +2.0 m of SLR. Because wave length in shallow water 

is primarily a function of the ratio of wave period to water depth, with increasing SLR, mean 

wave lengths around the atoll islands under winter conditions are approximately 7 m to 10 m 

longer than at present with +1.0 m of SLR and approximately 15 m to 20 m longer with +2.0 m 

of SLR. There is less increase during the summer (fig. 13), when the wave periods are slightly 
20

Figure 11. Directional plot of seasonal variations in wind speed, in meters per 

second, by wind direction, in compass orientation, based on U.S. Army Corps of 

Engineers (2011) hindcast data for the years 1981–2004 at 28° 00’ N, 174° 00’ W. 

Radial axis, frequency of occurrence, in percent, increase outward from the center of 

the plot.

lower with increasing SLR. Mean set-up values around the atoll islands, which are a function of 

the ratio of wave height to water depth, are approximately 0.05 m to 0.08 m lower than at present 

with +1.0 m of SLR and approximately 0.07 m to 0.15 m lower with +2.0 m of SLR. The mean 

top 2 percent run-up values around the atoll islands, which are a function of wave height, wave 

period, and the cross-shore slope of the beachface, are 0.17 m to 0.20 m higher than at present 

with +1.0 m of SLR and approximately 0.31 m to 0.41 m higher with +2.0 m of SLR. The trend 

in combined set-up and run-up around the atoll islands mirrors that of the variations in top 2 
21

percent run-up, being 0.06 m to 0.08 m higher than at present with +1.0 m of SLR and 

approximately 0.11 m to 0.14 m higher with +2.0 m of SLR. Variations in averaged wave 

parameters along the entire coastline of the atoll islands are relatively small. However, because 

run-up is a function of the cross-shore slope of the beachface, there is high spatial variability in 

run-up and combined set-up and run-up, as shown by the large error bars (showing ±1 SD) in 

figures 12–13. The highest mean values (±1 SD) in top 2 percent run-up are 0.42 m to 0.51 m 

higher with +1.0 m of SLR than at present and 0.76 m to 0.99 m higher with +2.0 m of SLR. In 

order to better understand how the spatially varying nature of wave heights and wavelengths 

resulting from the spatially heterogeneous morphology of the atolls resulted in spatially varying 

set-up and run-up around the islands, the combined effects of wave set-up and run-up for both 

the current (+0.00 m) and the highest (+2.00 m) SLR scenarios are shown in appendix 2. 

Although the resulting wave-driven water levels (combined set-up and run-up) around the islands 

are also heterogeneous, there is a general trend of higher levels on the portion of the islands 

closer to the reef crest or the lagoon, likely related to greater set-up influencing depth-limited 

wave heights on the reef flat. The highest mean values (±1 SD) for the change in wave-driven 

water levels are 0.96 m to 0.99 m higher with +1.0 m of SLR than at present and 1.91 m to 2.00 

m higher with +2.0 m of SLR (figs. 12–13). 

In all cases, modeled wave set-up, run-up, and combined wave-driven water levels for all 

SLR scenarios were greater for North Pacific winter conditions than for summer conditions. This 

dominance of maximum wave-driven water levels by winter storm conditions for each SLR 

scenario, in conjunction with the fact that the statistics for wave conditions were chosen to 

represent those conditions that would be experienced during an average year, resulted in the 

inundation, land cover class, and habitat class mapping efforts being focused on only North 

Pacific winter conditions.

Inundation Mapping

Across all SLR scenarios, the extent of inundation predicted under the passive modeling 

approach covered less area than the inundation extent forecasted by the modeling approach that 

includes wave-driven water levels (figs. 14–18, table 4). Under the passive modeling approach, 

each of the five SLR scenarios yielded a similar general spatial pattern, with inundation 

progressing inland from the coast in the shape of concentric rings. At the highest SLR scenarios, 

water levels began to exceed the coastal berm in places on Sand (fig. 14), Eastern (fig. 16), and 

Laysan Islands (fig. 17) and extend inland over low-lying areas as overwash sheets. The 

overwash at Laysan at the higher SLR scenarios also resulted, assuming no infiltration and 

unlimited seawater volumes, in raising the hypersaline lake levels and increasing inundation 

around the lake’s mudflats and surrounding vegetation. The introduction of seawater and marine 

biota into the lake by overwash would change the lake’s salinity and potentially impact the 

hypersaline-adapted aquatic species on Laysan. For Sand, Eastern, and Laysan Islands, passive 

inundation at +1.50 m SLR was less than 10 percent of the islands’ terrestrial areas and less than 

20 percent at +2.00 m SLR. On the lowest-lying island, Spit, however, the area inundated by 

passive SLR increased dramatically at much lower SLR scenarios: the area inundated doubled 

from 34 percent at +1.00 m SLR to 72 percent at +1.50 m SLR and exceeded 99 percent at +2.00 

m SLR. 

When passive SLR was combined with wave set-up and run-up to compute the dynamic 

total water levels, similar patterns of concentric inundation occurred at SLR scenarios less than 

+1.00 m. For the base scenarios (SLR = +0.00 m), the dynamic wave-driven inundation 

modeling predicted inundation extents on the order of twice as great as the passive scenarios, 
22

Figure 12. Plots of the mean changes in significant wave height (H, in meters), peak 

wave period (T, in seconds), and mean wavelength (L, in meters) and the resulting 

set-up (ETA, in meters), top 2 percent run-up (R2, in meters), and total wave-driven 

water levels (TWL, in meters) at all model grid locations adjacent to the four islands 

for the five sea-level rise (SLR) scenarios (+0.00 m, +0.50 m, +1.00 m, +1.50 m, and 

+2.00 m) relative to present sea level during North Pacific winter conditions. Blue 

represents data from Laysan Island; green represents data from Eastern Island; red 

represents data from Sand Island; and magenta represents data from Spit Island.

except at Laysan, where the amount of inundation, although small relative to the area of the 

island, went up more than an order of magnitude (from 0.1 percent to 1.8 percent). Projected 

inundation doubled from the +0.00 m to the +0.50 m SLR scenario for all islands except Spit, 

where wave-driven inundation caused the projected inundation to quadruple to more than 44 

percent of the island’s area. Between +0.50 m and +1.00 m SLR, the influence of the low 

topography on inundation results in the projected inundation to increase by 54 percent at Spit, 

whereas the other islands only show an increase on the order of 5 to 14 percent. Thus, the 

dynamic model that includes total water levels from wave-driven processes projects Spit Island 

to have approximately the same area inundated at +1.00 m SLR (98.1 percent) as is projected by 

the passive modeling at +2.00 m SLR (99.8 percent). 

On Sand, Eastern, and Laysan Island, at the higher SLR scenarios of +1.50 and +2.00 m, 

the dynamic inundation patterns start to diverge considerably from passive inundation patterns, 

as wave-driven water levels begin to exceed the existing coastal berm and extend considerable 

distances inland over low-lying areas (figs. 14–17). At +1.50 m SLR, wave-driven water levels 
23

Figure 13. Plots of the mean changes in significant wave height (H, in meters), peak 

wave period (T, in seconds), and mean wavelength (L, in meters) and the resulting 

set-up (ETA, in meters), top 2 percent run-up (R2, in meters), and total wave-driven 

water levels (TWL, in meters) at all model grid locations adjacent to the four islands 

for five sea-level rise (SLR) scenarios (+0.00 m, +0.50 m, +1.00 m, +1.50 m, and 

+2.00 m) relative to present sea level during summer trade-wind conditions. Blue 

represents data from Laysan Island; green represents data from Eastern Island; red 

represents data from Sand Island; and magenta represents data from Spit Island.

on Laysan breach the dunes in two locations along the east coast, including one location where 

wave-driven water levels penetrated to the lake zone. The inundated area from these two 

breaches intersected the two topographic depressions flooded by the storm event of February 

2011 (Kristof and others, 2011) and exhibit patterns similar to what was observed during that 

large storm event. At +2.00 m SLR, Eastern Island shows the greatest difference between the 

passive and dynamic inundation modeling, the passive model suggesting an inundation extent of 

19 percent, but the dynamic model predicting a loss of 91 percent of the island’s area. 

Land Cover and Habitat Inundation

The relative distribution of land cover classes defined from remote sensing varied by from 

island to island (tables 5–12; appendix 3). Similarly, the use of various land covers as wildlife 

habitat also varies by species and by island (tables 13 and 14). Sand Island’s land cover includes 

predominantly human structures, including paved runways (126.5 ha), and grass/herbaceous 
24

Figure 14. Map of inundation at Sand Island due to both passive (left) and dynamic 

(right) models for the five sea-level rise (SLR) scenarios (+0.00 m, +0.50 m, +1.00 

m, +1.50 m, and +2.00 m) relative to present sea level. 

cover. On Eastern Island, grass/herbaceous cover (55.9 ha) and partially vegetated former 

runway (32.4 ha) encompass the largest land areas. Spit and Laysan Islands, on the other hand, 

feature primarily bare ground (129.3 ha) and interspersed vegetation, including bunch grass, 

herbaceous species, vines, and ground cover. The changes in land cover classes follow similar 

patterns to the changes due to inundation, with all islands losing more of the existing land area at 

lower values of SLR under the dynamic modeling compared to the passive modeling (tables 5–

12). A feature that highlights one of the issues of this modeling is the high percentages of the 

“beach” class lost in all SLR scenarios. This is a result of the assumption that the land cover 

classes are static and inundation due to either the passive or dynamic model scenarios will not 

result in lateral and vertical migration of these features. However, it is clear from the geologic 

record that SLR results in the recession of the shoreline, in which the beach generally retains its 

form as it migrates inland and upwards with SLR unless stopped by some fixed feature, such as 

beachrock or infrastructure. Thus the high rates of beach loss are unlikely because land cover 

response to inundation is not static; these rates are rather a reflection of the methodology used in 

the static habitat modeling described above. Depending on the island and modeling scenario, 

major losses also are seen in bare ground, grass/herbaceous cover, and in the partially vegetated 

former runways on Sand and Eastern Islands (tables 5–12). 

As projected SLR increases, the percentages of areas classified as vegetated (excluding 

beach, bare ground, partially vegetated runway, and human structures) being inundated on Sand 

Island increase by an order of magnitude, from 1 and 4 percent for the passive and dynamic 

models, respectively, at +1.00 m SLR to 11 and 43 percent, respectively, at +2.00 m SLR 
25

Figure 15. Map of inundation at Spit Island due to both passive (left) and dynamic (right) 

models for the five sea-level rise (SLR) scenarios (+0.00 m, +0.50 m, +1.00 m, 

+1.50 m, and +2.00 m) relative to present sea level.

(fig. 19). Similar large increases are also projected for Eastern Island, from 0 and 8 percent 

inundated at +1.00 m SLR for the passive and dynamic models, respectively, to 12 and 87 

percent, respectively, at +2.00 m SLR (fig. 21). Spit Island, because of its low elevations, retains 

only 25 percent of its vegetated cover classes at +1.50 m SLR for the passive model and loses all 

of them at +2.00 m SLR; all of its vegetated cover classes are lost at +1.50 m SLR in the 

dynamic model (fig. 20). By passive modeling, Sand Island is projected to lose less than 1 

percent of the area classified as human structures at +1.50 m SLR and only 3 percent at +2.00 m 

SLR. The dynamic modeling, however, suggests that 3 percent of the area classified as human 

structures will be inundated at +1.00 m SLR, and almost a third (30 percent) at +2.00 m SLR. 

Laysan, because of its relatively steep nature, undergoes little change under the passive 

modeling, losing less than 2 percent of its bare ground even at +2.00 SLR. Just less than 4 

percent of bare ground on Laysan is predicted to be inundated at +1.50 m SLR in the dynamic 

model, but almost 20 percent, or approximately half an order of magnitude more, at +2.00 SLR 

(fig. 22). Overall, the dynamic modeling predicts, on average, approximately one-half to a full 

order of magnitude greater inundation of the different land cover classes for a given SLR 

scenario than is predicted by the passive modeling. 

The land cover classes defined for Midway Atoll and Laysan Island are used as wildlife 

breeding habitat by 25 species, including two endangered endemic passerine species 

(Acrocephalus familiaris kingi, Telespiza cantans), an endangered duck (Anas laysanensis), 20 

other species of Pacific seabirds, the green turtle (Chelonia mydas), and the endangered 

Hawaiian monk seal (Monachus schauinslandi). Island-specific species distributions are given in 
26

Figure 16. Map of inundation at Eastern Island due to both passive (left) and dynamic 

(right) models for the five sea-level rise (SLR) scenarios (+0.00 m, +0.50 m, +1.00 

m, +1.50 m, and +2.00 m) relative to present sea level.

table 13, and the use of various land-cover classes as habitat is given in table 14.. The 

distribution of the land cover classes over the four islands is given in table 15. The wildlife 

habitats included within a land cover class for each island can be used, in conjunction with the 

data provided in figures 19–22 and tables 5–12, to provide insight into potential habitat loss or 

inundation impacts to breeding wildlife under both passive and dynamic SLR scenarios. 

Breeding bird habitat (discussed in detail below) includes all land cover categories except beach, 

wetland, and human structures. 

On Sand Island, the percentage of breeding bird habitat (312. 6 ha) vulnerable to 

inundation at +1.00 m SLR is 0 and 4.5 percent, respectively, for the passive and dynamic 

models (tables 5 and 9). At +2.00 m SLR on Sand Island (fig. 19), passive inundation floods 7.6 

percent of nesting bird habitat, while dynamic inundation floods 39.9 percent (tables 5 and 9). At 

Spit Island, bird-breeding habitat (3.9 ha) vulnerable to inundation at +1.00 m SLR is 2.6 and 

94.9 percent, respectively, for the passive and dynamic models (tables 6 and 10). At +2.00 m 

SLR on Spit Island (fig. 19), passive inundation floods 67.2 percent of nesting bird habitat, while 

dynamic inundation is 100 percent (tables 6 and 10, fig. 20). For Eastern Island, losses in 

breeding bird habitat (125.4 ha) are also projected, with 0.1 and 6.9 percent inundated at +1.00 m 

SLR for the passive and dynamic models, respectively (table 7 and 11). At +2.00 m SLR on 

Eastern Island, passive inundation floods 10.9 percent of nesting bird habitat, while dynamic 

inundation is 90.1 percent (tables 7 and 11, fig. 21). The breeding bird habitat inundation 

patterns for Laysan Island with mapped colonies and nest distribution data are reported by 

Berkowitz and others (2012). 
27

Figure 17. Map of inundation at Laysan Island due to both passive (left) and dynamic 

(right) models for the five sea-level rise (SLR) scenarios (+0.00 m, +0.50 m, +1.00 

m, +1.50 m, and +2.00 m) relative to present sea level.

Discussion 

It is apparent that the passive “bathtub” inundation models for sea level rise (SLR) at atolls 

predict less inundation than the dynamic model that includes wave-driven water levels. This is 

especially true at higher SLR scenarios, in which SLR reduces wave breaking over the atolls’ 

reef crests, resulting in larger wave heights and longer wave periods at the present-day shoreline, 

which, in turn, result in greater wave-driven run-up and inundation. These larger run-up values, 

combined with the background SLR and the relatively low-lying nature of the atoll islands, result 

in greater inundation for a given SLR scenario than predicted by the passive modeling. These 

differences between the passive and dynamic models can be viewed two ways. First, more of the 

atoll islands are projected to be inundated at a given sea level scenario by incorporating wavedriven processes than is predicted by the passive “bathtub” models. In addition, because global 

sea level is rising, the five scenarios used here basically can be viewed as spanning a spectrum of 

time in the future, in that a +0.50 m SLR scenario will happen sooner in the future than a +1.00 

m SLR scenario. If SLR is therefore somewhat interchangeable with time, then the dynamic 

model results provided here suggest that a given percentage of the atoll islands and their 

associated land cover and wildlife habitats will be inundated at lower values of SLR and thus 

sooner in the future than predicted by the passive “bathtub” models. 
28

Figure 18. Plot of percentage of land area inundated on the four islands due to both 

passive (dashed lines) and dynamic (solid lines) models for the five sea-level rise 

(SLR) scenarios (+0.00 m, +0.50 m, +1.00 m, +1.50 m, and +2.00 m) relative to 

present sea level.

The results from this modeling study also call attention to the influence of island 

geomorphology on susceptibility to sea-level rise and wave-induced impacts. Although including 

wave-driven processes in modeling inundation generally predicted as much as an order of 

magnitude greater inundation than with the passive “bathtub” methodology, Midway’s Sand, 

Spit, and Eastern Islands were modeled to undergo much greater inundation for a given value of 

sea-level rise using both types of models than Laysan Island. Midway’s islands, on a classic atoll 

with islands on the shallow atoll rim and a deep central lagoon, are subjected to smaller 

nearshore wave heights and shorter wavelengths as a result of depth-limited breaking of incident 

deep-water waves on the shallow reef crests of the atoll’s rim. However, because predicted rates 

of sea-level rise will outstrip new vertical reef flat accretion, the protection of the island’s 

shorelines by depth-limited breaking will be significantly reduced by sea-level rise, resulting in 

much greater wave heights and wavelengths on the atoll’s reef flats than at present. As shown 

here, larger nearshore wave heights and longer wavelengths would lead to higher wave-driven 

water levels along the islands’ shorelines and thus greater inundation. Laysan, on the other hand, 

which is characterized by a deep (20–30 m) atoll rim and a central island, allows larger deepwater wave heights to propagate closer to shore than at Midway. Because of this, Laysan is 

shaped more like a high-energy island with steeper coastal topography and a higher mean 

elevation than the islands on a classic atoll. This more energetic nearshore wave environment 
29

Figure 19. Plot of percentage of land cover classes inundated on Sand Island due to 

both passive (left) and dynamic (right) models for the five sea-level rise (SLR) 

scenarios (+0.00 m, +0.50 m, +1.00 m, +1.50 m, and +2.00 m) relative to present 

sea level.

and resulting steeper and higher coastal topography results in Laysan Island undergoing much 

less inundation for a given sea-level rise scenario than Midway’s Sand, Spit, and Eastern Islands. 

Together, these modeling results and observations demonstrate that classic atolls with islands on 

the shallow atoll rim are more susceptible to the combined effects of sea-level rise and wavedriven inundation than islands on atolls characterized by a deep atoll rim. 

The wave-driven dynamic inundation models provide insight into the potential inundation 

that would occur at multiple times during the average year. This is in contrast to a once-in-adecade inundation event that might allow vegetation and breeding wildlife populations to recover 

quickly because of its infrequency relative to the rate of vegetation regeneration or wildlife 

population dynamics (annual breeding cycle). Rather, the use of the top 5 percent of wave 

conditions predicts events that would occur a few times every year and thus become a part of the 

natural annual cycle, potentially influencing wildlife distribution or reproductive success of 

highly philopatric species, which persistently return to the same breeding site and therefore are 

vulnerable to habitat inundation (Hatfield and others, 2012). As discussed previously, the 

inundation extents and associated changes in land cover and associated habitats and species 

provided in this report are not presented as exact values, but rather as values to be compared 

relative to one another for the different SLR scenarios. For additional details on species 

vulnerability to sea-level rise and storm events at Laysan Island, see Berkowitz and others 

(2012). 

The effort described here is the first attempt at providing insight into how passive, GISbased models of SLR impacts on atolls compare to dynamic models that include wave-driven 
30

Figure 20. Plot of percentage of land cover classes inundated on Spit Island due to both 

passive (left) and dynamic (right) models for the five sea-level rise (SLR) scenarios 

(+0.00 m, +0.50 m, +1.00 m, +1.50 m, and +2.00 m) relative to present sea level.

processes. As discussed earlier, there are a number of issues regarding how these inundation 

extents were modeled. These issues include the assumptions in the run-up methodology used 

here, projection of the inundation limits inland, interactions of the run-up with beach 

morphology and hydrogeology, and potential changes in the future atmospheric and 

oceanographic forcing. These issues could be addressed in order to model dynamic inundation 

more accurately. Models that better simulate infragravity wave motions (“surf beat”, with 

periods on the order of 30–300 s), which dominate run-up, and compute run-up water depths and 

volumes more accurately could be nested in the models developed here to better constrain 

dynamic inundation and volumes of seawater overwash. Ground-penetrating radar surveys and 

coring efforts could better constrain the islands’ sedimentology and stratigraphy. Such data 

would be necessary to accurately model the geomorphic evolution of the islands under the SLR 

scenarios using the models that include a dynamic geomorphic response to changes in waves and 

water levels. Such information on sedimentology, stratigraphy, and structure would also be 

necessary, in conjunction with the emplacement of groundwater monitoring wells, to accurately 

model the influence of SLR and dynamic inundation on the freshwater resources that sustain the 

islands’ vegetation, as well as influence seep and lake water levels (see Tribble, 2008). 

Conclusions 

Meteorologic and oceanographic forcing were used to model dynamic wave-driven water 

levels and inundation at Midway Atoll and Laysan Island in the Northwestern Hawaiian Islands 

for five different sea-level rise (SLR) scenarios and compare the results to passive inundation 
31

Figure 21. Plot of percentage of land cover classes inundated on Eastern Island due to 

both passive (left) and dynamic (right) models for the five sea-level rise (SLR) 

scenarios (+0.00 m, +0.50 m, +1.00 m, +1.50 m, and +2.00 m) relative to present 

sea level.

modeling of the same islands. Key findings from these modeling efforts and subsequent analyses 

include: 

1. The modeled dynamic wave set-up, run-up, and total wave-driven water levels for all 

SLR scenarios were greater for North Pacific winter swell conditions than for the summer tradewind waves. At higher SLR scenarios, less wave breaking on the reef crests resulted in larger 

waves and longer wavelengths on the islands’ shorelines. Although wave-driven set-up 

decreased at higher SLR scenarios, the increases in wave height and wavelength at higher SLR 

scenarios resulted in greater wave-driven run-up and thus higher total water levels along the 

islands’ shorelines. 

2. Across all SLR scenarios (+0.00, + 0.50, + 1.00, + 1.50, and + 2.00 m), the extent of 

inundation predicted under the passive modeling approach covered less area than the inundation 

extent forecasted by the dynamic modeling approach. For the higher SLR scenarios, the dynamic 

inundation patterns start to diverge considerably from passive inundation patterns, as wavedriven water levels began to exceed existing coastal berms and extend considerable distances 

inland over low-lying areas. 

3. The changes in land cover classes follow similar patterns to the overall patterns of 

inundation, with all islands losing more of the existing land cover at lower values of future SLR 

under the dynamic modeling than suggested by the passive modeling. Overall, the dynamic 

modeling predicts, on average, almost one-half to a full order of magnitude greater inundation of 

the different land cover classes for a given SLR scenario than is predicted by the passive 

modeling. 
32

Figure 22. Plot of percentage of land cover classes inundated on Laysan Island due to 

both passive (left) and dynamic (right) models for the five sea-level rise (SLR) 

scenarios (+0.00 m, +0.50 m, +1.00 m, +1.50 m, and +2.00 m) relative to relative 

to present sea level.

4. Assuming that sea level will continue to rise over the next century, the dynamic model 

results that include wave-driven processes presented here suggest that a given percentage of the 

atoll islands and their associated habitats will be episodically inundated at lower values of SLR 

and thus sooner in the future than predicted by the passive “bathtub” models.

5. Observations and the modeling results presented here suggest that classic atolls with 

islands on the shallow atoll rim are more susceptible to the combined effects of sea-level rise and 

wave-driven inundation than atolls characterized by a deep atoll rim. 

The dynamics of SLR and wave-driven inundation on low-lying atoll islands are complex 

in nature. The results presented here can provide information to identify the areas of 

vulnerability specific to each island. These models help display the relative impacts expected to 

occur, given the current knowledge of these complex systems, and may improve understanding 

of potential effects on natural resources needed for planning management of the atoll islands in 

the face of changing climate and sea level. 

Acknowledgments

This work was funded by the U.S. Geological Survey’s Pacific Coastal and Marine Science 

Center (USGS-PCMSC), the U.S. Geological Survey’s Pacific Islands Ecological Research 

Center (USGS-PIERC), and the U.S. Fish and Wildlife Service’ Inventory and Monitoring 

Program (USFWS-I&M) under Interagency Agreement F11RG00376 (“Predicting the Impact of 

Storm Waves and Sea-Level Rise within the Papahānaumokuākea Marine National Monument”). 
33

We would like to thank Jean Kenyon (USFWS), the USFWS Hawaiian and Pacific Islands 

National Wildlife Refuge Complex, and the Papahānaumokuākea Marine National Monument 

for their overarching support of this project. Edwin Elias (Deltares) provided guidance and help 

with the Delft3D modeling. Jamie Carter (NOAA) and Karen Courtot (USGS-PIERC) 

contributed technical assistance. Bruce Richmond and Andrew Stevens (USGS-PCMSC) 

contributed numerous excellent suggestions and a timely review of our work. 

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Service, 35 p.

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Hawaii.

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37

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Additional Digital Information

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For more information on the U.S. Geological Survey’s Pacific Island Ecosystem Research

Center, please see: http://www.usgs.gov/ecosystems/pierc/

 

Regarding this report, please contact: 

Curt D. Storlazzi (USGS Pacific Coral Reef Project chief): cstorlazzi@usgs.gov
38

Tables 

Table 1. Descriptions of the land cover classes in the study area. Land cover class General description Dominant species included

Tree/shrub Contiguous tree or shrub cover, multiple native 

and non-native species of 2–20 meters tall

Casuarina equisetifolia, Chenopodium oahuense, Coccoloba uvifera, Cocos 

nucifera, Hibiscus tiliaceus, Pluchea carolinensis, Scaevola taccada, Tournefortia 

argentea,

Mixed shrub

Low-density shrub cover with surrounding bare

ground or low vegetation, multiple native or nonnative species typically less than 2 m tall

Pluchea indica, Chenopodium oahuense, Coccoloba uvifera, Hibiscus tiliaceus, 

Pluchea carolinensis, Scaevola taccada, Tournefortia argentea

Grass/herbaceous cover

High-density grass, bunch grass, and 

herbaceous cover; multiple native and nonnative species

Bidens alba, Cynodon dactylon, Eleusine indica, Eragrostis variabilis, Euphorbia 

heterophylla, Eustachys petraea, Fimbristylis cymosa, Lepidium virginicum, 

Lepturus repens, Lobularia maritima, Pseudognaphalium sandwicensium, Psilotum 

nudum, Solanum nelsonii, Verbesina encelioides

Vine/ground cover

Low-lying vines and low herbaceous 

groundcover, multiple native and non-native 

species generally less than 0.25 m tall

Vine: Boerhavia repens, Ipomoea indica, Ipomoea pes-caprae; Ground cover: 

Portulaca lutea, Tribulus cistoides

Partially vegetated former 

runway Dilapidated runway with some vegetation Fimbristylis cymosa, Tribulus cistoides, Verbesina encelioides

Wetland vegetation Wetland plant species surviving in saturated 

conditions

Cyperus laevigatus, Cyperus pennatiformis var. bryanii, Heliotropium currasavicum, 

Sesuvium portulacastrum

Bare ground Bare ground inland of beach (without wave 

swash) used by nesting birds Unvegetated

Hard pan* Former guano mining site with no vegetation or 

minimal low vegetation Fimbristylis cymosa, Portulaca spp., Sporobolus pyramidatus

Beach

Coastal band subject to tidal inundation and 

wave swash under typical conditions; generally 

sand, coral or rock not suitable for bird nesting

Unvegetated

Wetland Standing water, and seasonally inundated 

unvegetated mudflats Unvegetated

Human structures Runways, buildings, roads, seawalls, etc. Unvegetated

*Classified based on field maps (U.S. Fish and Wildlife Service data).

Table 2. Monthly mean wave heights, wave periods, wave directions, wind 

speeds, and wind directions for the study area. [Statistics based on U.S. Army Corps of Engineers (2011) hindcast data for the years 1981–2004 at 28° 00’ N, 174° 

00’ W; Std Dev, standard deviation; m, meters; s, seconds] Time Period Mean

Wave Height

(m)

Std.Dev.

Wave Height

(m)

Mean

Wave Period

(s)

Std.Dev.

Wave Period

(s)

Wave

Direction

(°)

Mean

Wind Speed

(m/s)

Std.Dev.

Wind Speed

(m/s)

Wind

Direction

(°)

January 4.61 1.69 12.5 2.0 317 9.5 3.7 264

February 4.35 1.54 12.5 2.0 316 8.9 3.5 253

March 3.69 1.23 12.2 2.1 324 7.8 3.0 75

April 2.85 0.88 10.8 2.0 354 7.3 2.8 85

May 2.26 0.63 9.9 1.9 4 6.6 2.4 79

June 1.80 0.44 9.7 2.3 59 5.6 2.1 95

July 1.89 0.44 9.5 2.2 107 6.6 2.1 87

August 1.82 0.44 9.9 2.4 115 6.0 2.2 94

September 2.11 0.70 10.2 2.1 6 5.9 2.3 96

October 2.78 0.97 10.9 2.1 354 7.0 2.8 79

November 3.47 1.29 11.6 2.1 349 7.9 3.4 66

December 4.01 1.37 12.4 2.0 327 8.3 3.4 16

Winter

(Dec-Feb) 4.32 1.56 12.4 2.0 320 8.9 3.6 262

Spring

(Mar-May) 2.94 1.11 11.0 2.2 342 7.2 2.8 81

Summer

(Jun-Aug) 1.84 0.44 9.7 2.3 102 6.1 2.2 92

Fall

(Sep-Nov) 2.79 1.16 10.9 2.2 354 6.9 3.0 83
39

Table 3. Monthly top 5 percent wave heights, wave periods, wave directions, 

wind speeds, and wind directions for the study area.

[Statistics based on U.S. Army Corps of Engineers (2011) hindcast data for the years 1981–2004 at 28° 00’ N, 174° 

00’ W; Std Dev, standard deviation; m, meters; s, seconds] Time Period Mean

Wave Height

(m)

Std.Dev.

Wave Height

(m)

Mean

Wave Period

(s)

Std.Dev.

Wave Period

(s)

Wave

Direction

(°)

Mean

Wind Speed

(m/s)

Std.Dev.

Wind Speed

(m/s)

Wind

Direction

(°)

January 8.99 1.07 15.2 1.5 305 17.6 1.2 271

February 8.61 1.43 15.1 1.7 305 16.9 1.5 269

March 7.08 0.91 15.3 1.9 309 14.4 1.4 319

April 5.28 0.70 12.4 2.0 359 13.4 1.1 53

May 3.94 0.48 11.3 1.8 346 11.6 0.8 56

June 2.96 0.33 10.3 2.1 357 10.1 0.7 65

July 2.99 0.22 8.9 1.2 84 10.8 0.6 76

August 3.03 0.42 10.4 2.1 111 10.1 0.6 83

September 4.20 0.64 12.7 1.7 341 10.8 1.0 94

October 5.51 0.83 12.7 1.7 4 13.3 1.1 50

November 7.01 1.02 13.7 2.0 7 15.4 1.3 36

December 7.65 1.10 14.8 1.9 318 16.0 1.3 297

Winter

(Dec-Feb) 8.53 1.23 15.0 1.7 307 16.9 1.4 273

Spring

(Mar-May) 6.06 0.97 14.2 2.0 316 13.4 1.3 38

Summer

(Jun-Aug) 3.00 0.33 9.8 1.9 71 10.4 0.7 77

Fall

(Sep-Nov) 6.06 1.00 13.3 2.0 4 14.0 1.4 43

Table 4. Areal extent and change in area for all islands due to both passive and 

dynamic scenarios of sea-level rise. 

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Island Area

(ha)

Area

inundated

(ha)

Change

(%)

Area

inundated

(ha)

Change

(%)

Area

inundated

(ha)

Change

(%)

Area

inundated

(ha)

Change

(%)

Area

inundated

(ha)

Change

(%)

Passive 

Sand 460.0 1.7 -0.4 3.9 -0.8 6.9 -1.5 12.0 -2.6 43.5 -9.5

Spit 5.8 0.3 -4.7 0.7 -11.4 2.0 -34.0 4.2 -72.0 5.8 -99.8

Eastern 138.4 1.5 -1.1 3.5 -2.5 7.4 -5.4 12.8 -9.2 26.2 -18.9

Laysan 412.0 0.4 -0.1 3.1 -0.9 6.7 -2.0 10.8 -3.2 15.5 -4.6

Dynamic

Sand 460.0 3.7 -0.8 7.9 -1.7 29.4 -6.4 76.8 -16.7 180.2 -39.2

Spit 5.8 0.7 -11.4 2.6 -44.6 5.7 -98.1 5.8 -100.0 5.8 -100.0

Eastern 138.4 3.4 -2.5 7.7 -5.6 19.5 -14.1 60.3 -43.5 126.0 -91.0

Laysan 412.0 6.1 -1.8 10.5 -3.1 15.5 -4.6 22.1 -6.5 58.0 -17.2
40

Table 5. Areal extent and change in land cover classes on Sand Island due to passive sealevel rise scenarios. 

[m, meters; ha, hectares] 

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class Area

(ha)

Area

inundate

d 

(ha)

Change

(%)

Area

inundated

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Tree/shrub 126.

0 0 0 0 0 0 0 0 0 7.4 -5.9

Mixed shrub* 0 0 0 0 0 0 0 0 0 0 0 

Grass/herbaceous cover 109.

8 0 0 0 0 0 0 0 0 6.0 -5.5

Vine/ground cover 44.4 0 0 0 0 0 0 0 0 4.8 -10.8

Partially vegetated former 

runway 4.3 0 0 0 0 0 0 0 0 1.6 -37.2

Wetland vegetation 0 0 0 0 0 0 0 0 0 0 0 

Bare ground 28.1 0 0 0 0 0 0 0.3 -1.1 4.1 -14.6

Hard pan* 0 0 0 0 0 0 0 0 0 0 0 

Beach 18.9 1.5 -7.9 3.4 -18.0 6.2 -32.8 10.8 -57.1 15.1 -79.9

Wetland 2.1 0 0 0 0 0 0 0 0 0.2 -9.5

Human structures 126.

5 0.2 -0.2 0.5 -0.4 0.7 -0.6 0.9 -0.7 4.3 -3.4

Total area 460.

1 1.7 -0.4 3.9 -0.8 6.9 -1.5 12.0 -2.6 43.5 -9.5

*Landcover classes absent from this island.

Table 6. Areal extent and change in land cover classes on Spit Island due to passive sealevel rise scenarios. 

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class

Are

a 

(ha)

Area

inundate

d 

(ha)

Change

(%)

Area

inundated

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Tree/shrub 0.4 0 0 0 0 0 0 0.1 -25.0 0.4 -100.0

Mixed shrub* 0 0 0 0 0 0 0 0 0 0 0 

Grass/herbaceous cover 0.4 0 0 0 0 0 0 0.1 -25.0 0.4 -100.0

Vine/ground cover 0 0 0 0 0 0 0 0 0 0 0 

Partially vegetated former 

runway* 0 0 0 0 0 0 0 0 0 0 0 

Wetland vegetation 0 0 0 0 0 0 0 0 0 0 0 

Bare ground 3.1 0 0 0 0 0.1 -3.2 2.1 -67.7 3.1 -100.0

Hard pan* 0 0 0 0 0 0 0 0 0 0 0 

Beach 1.9 0.3 -15.8 0.7 -36.8 1.9 -100.0 1.9 -100.0 1.9 -100.0

Wetland 0 0 0 0 0 0 0 0 0 0 0 

Human structures* 0 0 0 0 0 0 0 0 0 0 0 

Total area 5.8 0.3 -5.2 0.7 -12.1 2.0 -34.5 4.2 -72.4 5.8 -100.0

*Landcover classes absent from this island.
41

Table 7. Areal extent and change in land cover classes on Eastern Island due to 

passive sea-level rise scenarios.

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class Area

(ha)

Area

inundate

d 

(ha)

Change

(%)

Area

inundated

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Tree/shrub 8.9 0 0 0 0 0 0 0 0 1.1 -12.4

Mixed shrub* 0 0 0 0 0 0 0 0 0 0 0 

Grass/herbaceous cover 55.9 0 0 0 0 0 0 0 0 4 -7.2

Vine/ground cover 15.9 0 0 0 0 0 0 0 0 2 -12.6

Partially vegetated former

runway 32.4 0 0 0 0 0 0 0 0 1.5 -4.6

Wetland vegetation 0 0 0 0 0 0 0 0 0 0 0 

Bare ground 12.3 0 0 0 0 0.1 -0.8 1.8 -14.6 5.1 -41.5

Hard pan* 0 0 0 0 0 0 0 0 0 0 0 

Beach 12.9 1.5 -11.6 3.5 -27.1 7.3 -56.6 10.9 -84.5 12.5 -96.9

Wetland 0 0 0 0 0 0 0 0 0 0 0 

Human structures 0 0 0 0 0 0 0 0 0 0 0 

Total area 138.

3 1.5 -1.1 3.5 -2.5 7.4 -5.4 12.7 -9.2 26.2 -18.9

*Landcover classes absent from this island.

Table 8. Areal extent and change in land cover classes on Laysan Island due to 

passive sea-level rise scenarios. 

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class Area

(ha)

Area

inundated 

(ha)

Change

(%)

Area

inundated

(ha)

Change 

(%)

Area

inundated 

(ha)

Change 

(%)

Area

inundated 

(ha)

Change 

(%)

Area

inundated 

(ha)

Change 

(%)

Tree/shrub 13.0 0 0 0 0 0 0 0 0 0 0 

Mixed shrub 26.3 0 0 0 0 0 0 0 0 0 0 

Grass/herbaceous cover 74.8 0 0 0 0 0 0 0 0 0 0 

Vine/ground cover 58.0 0 0 0 0 0 0 0 0 0 0 

Partially vegetated former 

runway* 0 0 0 0 0 0 0 0 0 0 0 

Wetland vegetation 13.8 0 0 0 0 0 0 0 0 0 0 

Bare ground 129.3 0.1 0 0.3 -0.2 0.4 -0.3 0.6 -0.5 1.6 -1.3

Hard pan 3.1 0 0 0 0 0 0 0 0 0 0 

Beach 19.4 0.4 -1.9 2.8 -14.5 6.3 -32.3 10.1 -52.3 13.8 -71.3

Wetland*

,

† 74.2 0 0 0 0 0 0 0 0 0 0 

Human structure 0 0 0 0 0 0 0 0 0 0 0 

Total area 412.0 0.4 -0.1 3.1 -0.8 6.7 -1.6 10.8 -2.6 15.5 -3.8

*Landcover classes absent from this island.

†

Includes unvegetated mudflats that were exposed at the time of classification.
42

Table 9. Areal extent and change in land cover classes on Sand Island due to dynamic sealevel rise scenarios. 

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class Area

(ha)

Area

inundated 

(ha)

Change

(%)

Area

inundated 

(ha)

Change 

(%)

Area

inundated 

(ha)

Change 

(%)

Area

inundated 

(ha)

Change 

(%)

Area

inundated 

(ha)

Change 

(%)

Tree/shrub 126.0 0 0 0 0 3.9 -3.1 15.0 -11.9 43.3 -34.4

Mixed shrub* 0 0 0 0 0 0 0 0 0 0 0 

Grass/herbaceous 

cover 109.8 0 0 0 0 4.1 -3.7 14.0 -12.8 43.3 -39.4

Vine/ground cover 44.4 0 0 0 0 2.8 -6.3 7.7 -17.3 19.2 -43.2

Partially vegetated 

former runway 4.3 0 0 0 0 0.9 -20.9 1.1 -25.6 2.0 -46.5

Wetland vegetation 0 0 0 0 0 0 0 0 0 0 0 

Bare ground 28.1 0 0 0.3 -1.1 2.3 -8.2 6.6 -23.5 17.0 -60.5

Hard pan* 0 0 0 0 0 0 0 0 0 0 0 

Beach 18.9 3.3 -17.5 6.9 -36.5 12.5 -66.1 16.3 -86.2 18.2 -96.3

Wetland 2.1 0 0 0 0 0 0 0.1 -4.8 0.3 -14.3

Human structures 126.5 0.4 -0.3 0.7 -0.6 3.0 -2.4 16.1 -12.7 37 -29.2

Total area 460.1 3.7 -0.8 7.9 -1.7 29.5 -6.4 76.9 -16.7 180.3 -39.2

*Landcover classes absent from this island.

Table 10. Areal extent and change in land cover classes on Spit Island due to dynamic sealevel rise scenarios. 

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class

Are

a 

(ha)

Area

inundate

d 

(ha)

Change

(%)

Area

inundated

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Tree/shrub 0.4 0 0 0 0 0.3 -75.0 0.4 -100.0 0.4 -100.0

Mixed shrub* 0 0 0 0 0 0 0 0 0 0 0 

Grass/herbaceous cover 0.4 0 0 0 0 0.4 -100.0 0.4 -100.0 0.4 -100.0

Vine/ground cover 0 0 0 0 0 0 0 0 0 0 0 

Partially vegetated 

former runway* 0 0 0 0 0 0 0 0 0 0 0 

Wetland vegetation 0 0 0 0 0 0 0 0 0 0 0 

Bare ground 3.1 0 0 0.8 -25.8 3 -96.8 3.1 -100.0 3.1 -100.0

Hard pan* 0 0 0 0 0 0 0 0 0 0 0 

Beach 1.9 0.7 -36.8 1.8 -94.7 1.9 -100.0 1.9 -100.0 1.9 -100.0

Wetland 0 0 0 0 0 0 0 0 0 0 0 

Human structures* 0 0 0 0 0 0 0 0 0 0 0 

Total area 5.8 0.7 -12.1 2.6 -44.8 5.6 -96.6 5.8 -100.0 5.8 -100.0

*Landcover classes absent from this island.
43

Table 11. Areal extent and change in land cover classes on Eastern Island due to dynamic 

sea-level rise scenarios. 

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class Area

(ha)

Area

inundate

d 

(ha)

Change

(%)

Area

inundated

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Tree/shrub 8.9 0 0 0 0 0.6 -6.7 3.2 -36.0 7.9 -88.8

Mixed shrub* 0 0 0 0 0 0 0 0 0 0 0 

Grass/herbaceous cover 55.9 0 0 0 0 3.2 -5.7 20.8 -37.2 48.6 -86.9

Vine/ground cover 15.9 0 0 0 0 1.2 -7.5 6.3 -39.6 13.7 -86.2

Partially vegetated former 

runway 32.4 0 0 0 0 0.7 -2.2 9.7 -29.9 31.5 -97.2

Wetland vegetation 0 0 0 0 0 0 0 0 0 0 0 

Bare ground 12.3 0 0 0.4 -3.3 2.9 -23.6 7.6 -61.8 11.3 -91.9

Hard pan* 0 0 0 0 0 0 0 0 0 0 0 

Beach 12.9 3.4 -26.4 7.3 -56.6 10.8 -83.7 12.6 -97.7 12.9 -100.0

Wetland 0 0 0 0 0 0 0 0 0 0 0 

Human structures 0 0 0 0 0 0 0 0 0 0 0 

Total area 138.

3 3.4 -2.5 7.7 -5.6 19.4 -14 60.2 -43.5 125.9 -91.0

*Landcover classes absent from this island.

Table 12. Areal extent and change in land cover classes on Laysan Island due to dynamic 

sea-level rise scenarios. 

[m, meters; ha, hectares]

Sea level: +0.00 m Sea level: +0.50 m Sea level: +1.00 m Sea level: +1.50 m Sea level: +2.00 m

Land cover class Area

(ha)

Area

inundate

d 

(ha)

Change

(%)

Area

inundated

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Area

inundate

d 

(ha)

Chang

e 

(%)

Tree/shrub 13.0 0 0 0 0 0 0 0 0 0.1 -0.8

Mixed shrub 26.3 0 0 0 0 0 0 0 0 2.0 -7.6

Grass/herbaceous cover 74.8 0 0 0 0 0 0 0.1 -0.1 6.9 -9.3

Vine/ground cover 58.0 0 0 0 0 0 0 0.1 -0.1 3.7 -6.3

Partially vegetated former 

runway* 0 0 0 0 0 0 0 0 0 0 0 

Wetland vegetation 13.8 0 0 0 0 0 0 0 0 1.2 -8.4

Bare ground 129.

3 0.4 -0.3 0.6 -0.5 1.5 -1.1 4.9 -3.8 25.2 -19.5

Hard pan 3.1 0 0 0 0 0 0 0 0 0 0 

Beach 19.4 5.7 -29.4 9.9 -51.0 14.0 -72.2 17.0 -87.8 18.8 -96.6

Wetland*

,

† 74.2 0 0 0 0 0 0 0 0 0 0 

Human structures 0 0 0 0 0 0 0 0 0 0 0 

Total area 412.

0 6.1 -1.5 10.5 -2.5 15.5 -3.8 22.1 -5.4 57.9 -14.1

*Landcover classes absent from this island.

†

Includes unvegetated mudflats that were exposed at the time of classification.
44

Table 13. Distribution of species by island.

Species Scientific name Sand Spit Eastern Laysan

Black-footed Albatross Phoebastria nigripes X X X X 

Laysan Albatross Phoebastria immutabilis X X X X 

Short-tailed Albatross Phoebastria albatrus X 

Bonin Petrel Pterodroma hypoleuca X X X X 

Bulwer's Petrel Bulweria bulwerii X 

Wedge-tailed 

Shearwater Puffinus pacificus X X X 

Christmas Shearwater Puffinus nativitatis X X 

Tristram's Storm-petrel Oceanodroma tristrami X 

Red-tailed Tropicbird Phaethon rubricauda rubricauda X X X X 

White-tailed Tropicbird Phaethon lepturus dorotheae X 

Masked Booby Sula dactylatra personata X X 

Brown Booby Sula leucogaster plotus X X 

Red-footed Booby Sula sula rubripes X X X 

Great Frigatebird Fregata minor palmerstoni X X X 

Little Tern Sternula albifrons X 

Least Tern Sternula antillarum X 

Gray-backed Tern Onychoprion lunatus X X X 

Sooty Tern Onychoprion fuscata oahuensis X X 

Brown Noddy Anous stolidus pileatus X X X X 

Black Noddy Anous minutus marcusi X X X 

White Tern Gygis alba candida X X X X 

Laysan Teal Anas laysanensis X X X 

Laysan Finch Telespiza cantans X 

Nihoa Millerbird* Acrocephalus familiaris kingi X 

Hawaiian monk seal Monachus schauinslandi X X X X 

Hawaiian green turtle† Chelonia mydas X X X X 

*

Individuals translocated to Laysan Island in September 2011 and 2012 with successful breeding in 2012 

(Farmer and others, 2012; Vetter, 2012). 

†

Hawaiian green turtle population comprises a unique genetic stock (Balazs and Chaloupka, 2004).
45

Table 14. Species use by land cover classes. Species Tree/

shrub

Mixed 

shrub

Grass/ 

herbaceous 

cover

Vine/ 

ground 

cover

Partially 

vegetated 

former runway

Wetland 

vegetation

Bare 

ground

Hard 

pan

Beach Wetland Human 

structures

Black-footed Albatross X X X X X X X 

Laysan Albatross X X X X X X X X 

Short-tailed Albatross X X 

Bonin Petrel X X X X 

Bulwer's Petrel X 

Wedge-tailed Shearwater X X X X X 

Christmas Shearwater X X X X X 

Tristram's Storm-petrel X X X X X 

Red-tailed Tropicbird X X X 

White-tailed Tropicbird X 

Masked Booby X X X X 

Brown Booby X X X 

Red-footed Booby X X 

Great Frigatebird X X 

Little Tern X X X 

Least Tern X X X 

Gray-backed Tern X X X X 

Sooty Tern X X X X 

Brown Noddy X X X X X X 

Black Noddy X X X 

White Tern X X 

Laysan Teal X X X X 

Laysan Finch X X X X 

Nihoa Millerbird* X X X X 

Hawaiian monk seal X X 

Hawaiian green turtle X X 

*Expected and confirmed habitat use from newly translocated populations to Laysan Island.
46

Table 15. Land cover classes by island. [Some land cover classes may exist on islands but are not included in tables 5-12

when the class covers an area less than 0.1 hectare]

Land Cover Sand Spit Eastern Laysan

Tree/shrub X X X X 

Mixed shrub* X 

Grass/herbaceous cover X X X X 

Vine/ground cover X X X 

Partially vegetated former runway X X 

Wetland vegetation X 

Bare ground X X X X 

Hard pan X 

Beach X X X X 

Wetland X X 

Human structures X 

*Mixed shrub not classified at Midway Atoll due to limitations in image resolution and field-mapping data. 
47

Appendix 1. Maps of Significant Wave Height Around the 

Atoll Islands. 

Appendix 1.1. Map of significant wave height, in meters, around Laysan Island for present-day sea level during North 

Pacific winter conditions.
48

Appendix 1.2. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for present-day sea level during North Pacific winter conditions.
49

Appendix 1.3. Map of significant wave height, in meters, around Laysan Island for present-day sea level during 

summer trade-wind conditions.
50

Appendix 1.4. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for present-day sea level during summer trade-wind conditions.
51

Appendix 1.5. Map of significant wave height, in meters, around Laysan Island for sea level +0.25 m above present 

during North Pacific winter conditions.
52

Appendix 1.6. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +0.25 m above present during North Pacific winter conditions.
53

Appendix 1.7. Map of significant wave height, in meters, around Laysan Island sea level +0.25 m above present 

during summer trade-wind conditions.
54

Appendix 1.8. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +0.25 m above present during summer trade-wind conditions.
55

Appendix 1.9. Map of significant wave height, in meters, around Laysan Island for sea level +0.50 m above present 

during North Pacific winter conditions.
56

Appendix 1.10. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +0.50 m above present during North Pacific winter conditions.
57

Appendix 1.11. Map of significant wave height, in meters, around Laysan Island sea level +0.50 m above present 

during summer trade-wind conditions.
58

Appendix 1.12. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +0.50 m above present during summer trade-wind conditions.
59

Appendix 1.13. Map of significant wave height, in meters, around Laysan Island for sea level +1.00 m above present 

during North Pacific winter conditions.
60

Appendix 1.14. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +1.00 m above present during North Pacific winter conditions.
61

Appendix 1.15. Map of significant wave height, in meters, around Laysan Island sea level +1.00 m above present 

during summer trade-wind conditions.
62

Appendix 1.16. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +1.00 m above present during summer trade-wind conditions.
63

Appendix 1.17. Map of significant wave height, in meters, around Laysan Island for sea level +1.50 m above present 

during North Pacific winter conditions.
64

Appendix 1.18. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +1.50 m above present during North Pacific winter conditions.
65

Appendix 1.19. Map of significant wave height, in meters, around Laysan Island sea level +1.50 m above present 

during summer trade-wind conditions.
66

Appendix 1.20. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +1.50 m above present during summer trade-wind conditions.
67

Appendix 1.21. Map of significant wave height, in meters, around Laysan Island for sea level +2.00 m above present 

during North Pacific winter conditions.
68

Appendix 1.22. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +2.00 m above present during North Pacific winter conditions.
69

Appendix 1.23. Map of significant wave height, in meters, around Laysan Island sea level +2.00 m above present 

during summer trade-wind conditions.
70

Appendix 1.24. Map of significant wave height, in meters, around Sand Island (top) and Spit and Eastern Islands 

(bottom) for sea level +2.00 m above present during summer trade-wind conditions.
71

Appendix 2. Maps of Combined Effects of Wave-Driven Setup and Run-up around the Atoll Islands. 

Appendix 2.1. Map of combined effects of wave-driven set-up and run-up around Sand Island at current sea level 

(+0.00 m) and sea level +2.00 m above present.
72

Appendix 2.2. Map of combined effects of wave-driven set-up and run-up around Spit Island at current sea level 

(+0.00 m) and sea level +2.00 m above present.
73

Appendix 2.3. Map of combined effects of wave-driven set-up and run-up around Eastern Island at current sea level 

(+0.00 m) and sea level +2.00 m above present.
74

Appendix 2.4. Map of combined effects of wave-driven set-up and run-up around Laysan Island at current sea level 

(+0.00 m) and sea level +2.00 m above present.
75

Appendix 3. Maps of Land Cover Classes on the Atoll 

Islands. 

Appendix 3.1. Map of land cover classes on Sand Island. Land cover classes (table 1) can exist on islands but not 

be visible in the land cover maps when the class covers an area less than 0.1 hectare. 
76

Appendix 3.2. Map of land cover classes on Spit Island. Land cover classes (table 1) can exist on islands but not be 

visible in the land cover maps when the class covers an area less than 0.1 hectare. 
77

Appendix 3.3. Map of land cover classes on Eastern Island. Land cover classes (table 1) can exist on islands but not 

be visible in the land cover maps when the class covers an area less than 0.1 hectare. 
78

Appendix 3.4. Map of land cover classes on Laysan Island. Land cover classes (table 1) can exist on islands but not 

be visible in the land cover maps when the class covers an area less than 0.1 hectare.