Open-File Report 2013–1163

Submergence Vulnerability Index Development and 

Application to Coastwide Reference Monitoring System 

Sites and Coastal Wetlands Planning, Protection and 

Restoration Act Projects

Prepared in cooperation with the Coastal Wetlands Planning, Protection and Restoration Act

U.S. Department of the Interior

U.S. Geological Survey

Submergence Vulnerability Index 

Development and Application to Coastwide 

Reference Monitoring System Sites and 

Coastal Wetlands Planning, Protection and 

Restoration Act Projects

By Camille L. Stagg, Leigh Anne Sharp, Thomas E. McGinnis, and Gregg A. Snedden

Prepared in cooperation with the Coastal Wetlands Planning, Protection and 

Restoration Act

Open-File Report 2013–1163

U.S. Department of the Interior

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

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

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

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Suggested citation:

Stagg, C.L., Sharp, L.A., McGinnis, T.E., and Snedden, G.A., 2013, Submergence Vulnerability Index development 

and application to Coastwide Reference Monitoring System Sites and Coastal Wetlands Planning, Protection 

and Restoration Act projects: U.S. Geological Survey Open-File Report 2013–1163, 12 p., http://pubs.usgs.gov/

of/2013/1163/. 
iii

Contents

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

Introduction ....................................................................................................................................................1

Data Collection ..............................................................................................................................................4

RSET Data ..............................................................................................................................................4

Elevation Survey Data .........................................................................................................................5

Vertical Accretion Data ......................................................................................................................5

Hydrologic Data ....................................................................................................................................5

Index Description ..........................................................................................................................................5

Implementation and Evaluation ..................................................................................................................8

References Cited .........................................................................................................................................11

Figures

1. Map showing the Louisiana coast with Coastwide Reference Monitoring 

System (CRMS) sites displayed according to the 2007 wetland classification..................2

2. Diagram showing conceptual model depicting how environmental processes 

(white boxes) and soil-development processes (grey boxes) interact to 

influence wetland elevation and sustainability .......................................................................3

3. Diagram showing conceptual model of Submergence Vulnerability Index (SVI), 

where wetland vulnerability is based on a projection of the relative vertical 

position of the wetland within the hydrologic frame..............................................................3

4. Diagram showing conceptual diagram of the Rod Surface Elevation Table 

(RSET) and feldspar marker horizons........................................................................................5

5. Schematic showing schematic of the continual water-level recorder used to 

calculate water elevation in centimeters (cm) relative to the North American 

Vertical Datum of 1988 (NAVD88)...............................................................................................6

6. Graph showing an example of a site-scale assessment of submergence 

vulnerability for site CRMS0544 by using the Submergence Vulnerability 

Index (SVI)......................................................................................................................................7

7. Graph showing submergence Vulnerability Index scores for an individual site 

(CRMS0544 project site) located within a restoration project..............................................8

8. Graph showing multiple scale comparison of Submergence Vulnerability 

Index (SVI) scores between an individual site (CRMS0544) and all sites within 

the same basin, all sites within the same wetland classification, and all sites 

coastwide.......................................................................................................................................8

9. Map showing coastwide spatial distribution of wetland submergence 

vulnerability represented by Submergence Vulnerability Index (SVI) scores 

for Coastwide Reference Monitoring System (CRMS) sites containing at least 

5 years of elevation-change data ..............................................................................................9

10. Graphs showing A) Distribution of coastwide Submergence Vulnerability Index 

(SVI) scores. B) Shallow subsidence rates separated by hydrologic basin: 

Atchafalaya Basin (AT), Barataria Basin (BA), Breton Sound (BS), CalcasieuSabine Basin (CS), Mermentau Basin (ME), Mississippi River Delta (MR), 

Lake Pontchartrain Basin (PO), Terrebonne Basin (TE) and Teche-Vermilion 

Basin (TV).....................................................................................................................................10
iv

Table

1. Overview of soil and hydrologic data parameters included in the Submergence 

Vulnerability Index model............................................................................................................4

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

kilometer (km) 0.5400 mile, nautical (nmi) 

meter (m) 1.094 yard (yd) 

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

yard (yd) 0.9144 meter (m)

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

°F=(1.8×°C)+32

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

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Elevation, as used in this report, refers to distance above the vertical datum.
Submergence Vulnerability Index Development and 

Application to Coastwide Reference Monitoring System 

Sites and Coastal Wetlands Planning, Protection and 

Restoration Act Projects 

By Camille L. Stagg,1 Leigh Anne Sharp,2 Thomas E. McGinnis,2 and Gregg A. Snedden1

Abstract

Since its implementation in 2003, the Coastwide 

Reference Monitoring System (CRMS) in Louisiana has 

facilitated the creation of a comprehensive dataset that 

includes, but is not limited to, vegetation, hydrologic, and 

soil metrics on a coastwide scale. The primary impetus for 

this data collection is to assess land management activities, 

including restoration efforts, across the coast. The aim of the 

CRMS analytical team is to provide a method to synthesize 

this data to enable multiscaled evaluations of activities in 

Louisiana’s coastal wetlands. Several indices have been 

developed to facilitate data synthesis and interpretation, 

including a Floristic Quality Index, a Hydrologic Index, and 

a Landscape Index. This document details the development 

of the Submergence Vulnerability Index, which incorporates 

sediment-elevation data as well as hydrologic data to 

determine the vulnerability of a wetland based on its ability to 

keep pace with sea-level rise. The objective of this document 

is to provide Federal and State sponsors, project managers, 

planners, landowners, data users, and the rest of the coastal 

restoration community with the following: (1) data collection 

and model development methods for the sediment-elevation 

response variables, and (2) a description of how these response 

variables will be used to evaluate CWPPRA project and 

program effectiveness.

Introduction

In response to widespread and severe land loss along 

the northern Gulf of Mexico coast in Louisiana (Couvillion 

and others, 2011), the Coastal Wetlands Planning, Protection 

and Restoration Act of 1990 was passed to conserve, restore, 

create, or enhance coastal wetlands. In 2003, the Coastwide 

Reference Monitoring System (CRMS) was initiated to 

provide a framework for assessing the effectiveness of the 

restoration projects implemented through CWPPRA (fig. 

1). The CRMS network provides ecological data not only 

from sites located within project boundaries but also from 

sites located across the coastal zone of Louisiana, thereby 

allowing for multiscale comparisons to evaluate restoration 

efforts on a project-specific level or an ecosystem or 

landscape scale (Steyer and others, 2003, 2006).

In order to synthesize the numerous ecological 

parameters that are measured at CRMS sites, a Floristic 

Quality Index (Cretini and others, 2011), a Hydrologic 

Index (Snedden and Swenson, 2012), and a Landscape 

Index (current document) were created. These indices, in 

conjunction with other pertinent ecological metrics, provide 

a mechanism to quantitatively assess the effectiveness of 

restoration activities and overall ecosystem health. This 

document describes the development and potential use 

of the Submergence Vulnerability Index (SVI), which 

incorporates ecological parameters associated with soil 

building, wetland elevation dynamics, and local relative 

water-level trends. 

The SVI assesses a site’s vulnerability to submergence 

because of sea-level rise, which results from the feedbacks 

among flooding regime, surface elevation, and surface 

accretionary processes. Wetland sustainability is 

maintained through regular flooding events that provide 

sediments and nutrients and flush phytotoxins from the 

soil, thereby stimulating primary production, which in turn 

increases sedimentation and accretion (Mendelssohn and 

Seneca, 1980; Nyman and others, 1993; Cahoon and others, 

2006; Nyman and others, 2006). This positive feedback 

loop results in the maintenance of wetland elevation, which 

in turn influences flood regime (fig. 2). Therefore, for the 

purposes of this index, a site is considered vulnerable to 

submergence if the elevation change rate is too low to offset 

local sea-level rise (fig. 3).

1

U.S. Geological Survey.

2

State of Louisiana, Coastal Protection and Restoration Authority, Lafayette.
Figure 1. Louisiana coast with Coastwide Reference Monitoring System (CRMS) sites displayed according to the 2007 wetland classification (SasseCalcasieu-Sabine Basin; ME, Mermentau Basin; TV, Teche-Vermilion Basin; AT, Atchafalaya Basin; TE, Terrebonne Basin; BA, Barataria Basin; PO, LaBreton Sound; MR, Mississippi River Delta) 

AT

BA

CS

ME

PO

TV

TE

0 2 0 4 0 6 0 MIL E S

0 2 0 4 0 6 0 K IL O ME T E R S

Louisiana

Study area

SwampFreshIntermediateBrackishSaline

CRMS sites by wetland classification

EXPLANATION
Introduction 3

Salinity

Flooding depth/duration

Nutrients

Decomposition

Biomass accumulation

Sedimentation and erosion Soil elevation

Altered river flows

(freshwater and sediment)

Nutrient input

(europhication)

Subsidence

(shallow and deep)

Sea-level rise/tides

Disturbance

(herbivory, fire)

Elevated

atmospheric

carbon dioxide

Plant growth/turnover

Storms

Figure 2. Conceptual model depicting how environmental processes (white boxes) and soil-development processes (grey boxes) 

interact to influence wetland elevation and sustainability (from Cahoon and others, 2009).

Local relative water level trend

SVI Score = 80 

Positive wetland elevation trajectory

Negative wetland elevation trajectory

Elevation, in centimeters above the

North American Vertical Datum of 1988

Time, in years 

Wetland0

Percentile rank

(SVI score)

0 

100 

SVI Score = 10 

Water b0

Water a0

Less flooding = less vulnerable

Figure 3. Conceptual model of Submergence Vulnerability Index (SVI), where wetland vulnerability is based on a projection of the 

relative vertical position of the wetland within the hydrologic frame. Left Y-axis represents wetland and water elevation. Wetland0

represents the initial wetland elevation; Water a0

 and Water bo represent the upper and lower bounds of the current hydrologic frame, 

respectively. The right Y-axis represents the relative position of the projected wetland within the projected hydrologic frame as a 

percentile ranking of the wetland elevation compared to the water elevations. The x-axis represents time from the most recent wetland 

and water elevation measurements to 5 years in the future. The green line represents a potential scenario, where a wetland with a 

positive elevation trajectory is projected to have an elevation that is ranked in the 80th percentile of water-level observations. The red 

dashed line is an example of a potential scenario, where a wetland with a negative elevation trajectory is projected to have an elevation 

that is ranked among the 10th percentile of water-level observations. Higher scores represent wetlands that are flooded less often and 

are less vulnerable to submergence. In contrast, lower scores represent wetlands that are flooded more often and are more vulnerable 

to submergence.
4 Submergence Vulnerability Index Development and Application to CRMS Sites and CWPPRA Projects

Other coastal vulnerability assessments have been 

developed on global (Harrison, 1975; Gornitz, 1991) and 

local (Cahoon and others, 2006) scales. Because finescale processes such as plant production, organic matter 

decomposition, and sediment deposition are largely 

responsible for local changes in wetland elevation, sitespecific assessments of wetland vulnerability are important 

(Cahoon and others, 2006). The SVI represents the interaction 

between site-specific measurements of surface-elevation 

dynamics and site-specific relative sea-level rise (defined 

in this document as local relative water-level trend) and 

therefore is not constrained by the differences in temporal and 

spatial scaling that are present when using regional, longterm historical records of sea-level rise (as in Cahoon and 

others, 2006). 

The objective of this document is to provide Federal and 

State sponsors, project managers, planners, landowners, data 

users, and the rest of the coastal restoration community with 

the following: (1) data collection and model development 

methods for the sediment-elevation response variables, and 

(2) a description of how these response variables will be used 

to evaluate CWPPRA project and program effectiveness. 

New response variables may be added, or current response 

variables may be removed, as data become available and as 

our understanding of restoration success indicators develops. 

Data Collection

The SVI incorporates several parameters representative 

of soil-building processes and elevation-change dynamics 

to determine the vulnerability of a site to submergence 

from increasing water levels (table 1). Elevation change, 

vertical accretion, and water elevation measured at each site 

are used along with regional estimates of global eustatic 

sea-level rise (ESLR) (Solomon and others, 2007) to make 

direct comparisons of wetland surface elevation to local 

relative water-level trends. A brief description of data 

collection methodology is given for each parameter included 

in the SVI model (table 1). Complete descriptions of the 

methods and sampling design for collecting elevation data in 

emergent wetlands at CRMS sites can be found in Folse and 

others (2008).

RSET Data

The Rod Surface Elevation Table method (RSET) 

(Cahoon and others, 2002) provides high-precision, 

repeatable measurements of relative sediment elevation. The 

RSET method, as implemented within the CRMS network, 

measures surface-elevation change in 6-month intervals and 

provides cumulative elevation change (CEC) data over time. 

Simultaneous measures of vertical accretion relative to an 

artificial soil marker horizon provide information on surficial 

processes. The difference between vertical accretion and CEC 

is shallow subsidence (Cahoon and others 1995; fig. 4). Thus, 

this methodology allows not only for site-specific comparisons 

of elevation-change trajectories to local water-level trends 

but also for a greater understanding of site-specific processes 

influencing elevation change.

One RSET benchmark is located at each CRMS site 

(with the exception of floating marshes and perpetually 

flooded, flocculent swamps). From the RSET benchmark, 

surface elevation is measured at nine points in four directions 

to calculate elevation change at 6-month intervals. CEC is 

defined as elevation change since station establishment. Mean 

elevation is calculated for each of the four directions, and 

an elevation-change trajectory is generated for each site by 

using a linear regression of CEC versus time. Five years of 

surface-elevation change data are required for calculation of 

an SVI score. Although RSET data can be interpreted sooner, 

extending the data completeness criterion to 5 years includes 

more temporal variation and also allows for a consistent 

comparison to the water-level record (Cahoon and others, 

2006), which is defined by the most recent 5 years of data.

Table 1. Overview of soil and hydrologic data parameters included in the Submergence Vulnerability Index model.

[cm, centimeter; y, year; NAVD 88, North American Vertical Datum of 1988]

Soil and hydrologic

data parameter Units Data source Method

Cumulative elevation change cm y-1 Site-specific measurement Rod Surface Elevation Table (RSET).

Vertical accretion cm y-1 Site-specific measurement Feldspar marker horizon plots.

Shallow subsidence cm y-1 Calculation from site-specific measurements Vertical accretion–cumulative 

elevation change.

Water elevation cm NAVD 88 Site-specific measurement Continual water-level recorder.

Eustatic sea-level rise cm y-1 Global scale data (Solomon and others, 2007)

Local relative water-level trend cm y-1 Calculation from site-specific measurements 

and literature values for global scale data

Shallow subsidence + eustatic

sea-level rise.
Elevation Survey Data

The height of the RSET benchmark rod and initial 

wetland elevation were determined during site construction 

by using Real-Time Kinematic (RTK) Survey methods and 

tied into the North American Vertical Datum of 1988 (NAVD 

88), according to the CPRA contractor’s guide to minimum 

standards (Coastal Protection and Restoration Authority, 

2011). Initial wetland elevation (Wetland0), is defined as the 

mean of at least 20 (40 in Spartina patens marshes) elevation 

data points (6–12 meters (m) apart) from an individual 

CRMS site. 

Vertical Accretion Data

At each RSET station, vertical accretion is measured in 

three replicate feldspar plots as the amount of material above 

the feldspar-marker horizon identified on a cryogenic core. In 

order to make comparisons of vertical accretion rates among 

sites and calculate accretion rates on scales larger than site-level 

(for example, basinwide or coastwide accretion rates), new 

marker horizons are established at 2-year intervals, to maintain 

the same temporal scale between sites. Marker horizons are 

recurrently sampled until they no longer provide accretion data; 

however, to maintain comparable temporal scales between sites, 

only short-term (3-year) accretion rates are included in the SVI 

model. In this model, rate calculations are limited to 3 years, 

because consistent data collection declines after this period of 

time. Accretion rates are calculated from replicate feldspar plots 

by using a linear regression of accretion versus time.

Hydrologic Data

Hydrologic data are collected continually at all CRMS 

sites. Water level, temperature, specific conductivity, and 

salinity data are collected hourly from surface water at 

permanent monitoring stations with continual recording 

instruments (fig. 5). The continual recording instruments are 

calibrated, deployed, and monitored according to specifications 

in Folse and others (2008). The water-level benchmark (top of 

continual recorder post) is surveyed by using RTK technology, 

and water levels are tied into the NAVD 88. The sensor rests 

on top of a fixed hexagonal bolt (1/4 inch (in.) x 3 in. or 5 in.), 

so that the elevation of the sensor relative to the benchmark 

can be determined by survey methods (Folse and others, 2008). 

Mean daily water levels are used to define the hydrologic 

frame for each site. The current hydrologic frame is defined 

as the most recent 5-year record of mean daily water levels, 

known as a Gulf Epoch (National Oceanic and Atmospheric 

Administration, 2008), and each year within the hydrologic 

record must meet a 70 percent data completeness criterion. The 

Gulf Epoch is a Modified Tidal Datum Epoch that incorporates 

only the most recent 5 years of hydrologic data. Modified 

Tidal Datum Epochs are used in anomalous areas, such as the 

northern Gulf of Mexico, where extreme rates of relative sealevel change occur because of localized isostatic influences, 

such as subsidence, glacial rebound, or tectonic activity 

(National Oceanic and Atmospheric Administration, 2008).

Index Description

The SVI assesses a site’s susceptibility to submergence 

and allocates a score according to the position of the projected 

wetland elevation relative to the projected hydrologic frame 

(figs. 2, 6). Sites with more frequent flooding receive lower 

scores and are considered more vulnerable to submergence.

Figure 4. Conceptual diagram of the Rod Surface Elevation Table 

(RSET) and feldspar marker horizons (from Cahoon and Lynch, 

2010).

Root zone

RSET

(~3–25 meters deep) Feldspar marker

horizon (surface)

Vertical

accretion

Marker

horizon

Elevation

change

Zone of

shallow subsidence

Deep

subsidence

Data Collection 5
All screws, bolts, washers, and nuts are to be hot-dipped, galvanized 

Hexagonal screw

(1⁄4 in. × 13⁄4 in.)

Treated timber board

(2 in. × 4 in. × 10 ft)

Hexagonal bolt (5 8 in. × 6 in.) 

with nut, flat washers,

and lock washer 

Nail: 16 Penny

 (used as elevation mark)

Treated timber post

(4 in. × 4 in. × 16 ft or 20 ft)

Mud line

Hexagonal bolt (1⁄4 in. × 3 in. or 5 in.)

 with nut, flat washers, and lock washers 

PVC pipe (2 in. diameter or 4 in. diameter)

3⁄4 in. Holes in PVC pipe 

Data logger with cable

Mean high

water line 

PVC pipe (1 in. diameter)

Brass lock

Electrical box

Hexagonal screw

(1⁄4 in. × 13⁄4 in.)

Hexagonal screw

(1⁄4 in. × 13⁄4 in.)

6 Submergence Vulnerability Index Development and Application to CRMS Sites and CWPPRA Projects

Figure 5. Schematic of the continual water-level recorder used to calculate water elevation in centimeters (cm) relative to the North 

American Vertical Datum of 1988 (NAVD88) (from Folse and others, 2008).
Index Description 7

Wetland elevation is projected 5 years into the future by 

using the following linear model:

Y x Wetland CEC Wetland t = + β β * 0 (1)

where

Wetlandt Y

βCEC

x

Wetland0 β

Wetlandt represents the projected wetland elevation, Y

βCEC

x

Wetland0 β

is the slope of the wetland surface trajectory 

and represents the rate of annual 

cumulative elevation change calculated 

from RSET data, 

Wetlandt Y

βCEC

x

Wetland0 β

is equal to 5 years, and

Wetlandt Y

βCEC

x

Wetland0 β is the intercept and represents the initial 

wetland elevation. 

The hydrologic frame is projected by using the following 

linear model, which is applied to each individual water-level 

observation in the current hydrologic frame:

1 0

N Y x wateri LRWLT wateri t = + β β * (2)

where

wate t Y r i

βLRWLT

x

wate 0 β r i

1 t

N Ywater i

is an individual observation of projected mean 

t daily water level, Ywater i

βLRWLT

x

wate 0 β r i

1 t

N Ywater i

is the slope and represents the local relative 

water level trend, 

wate t Y r i

βLRWLT

x

wate 0 β r i

1 t

N Ywater i

is equal to 5 years, 

wate t Y r i

βLRWLT

x

wate 0 β r i

1 t

N Ywater i

is the intercept and represents the individual 

observation of mean daily water level in 

the current hydrologic frame, and

wate t Y r i

βLRWLT

x

wate 0 β r i

1 t

N Ywater i represents the consolidated dataset 

of all individual projected mean 

daily water levels which define the 

projected hydrologic frame with N total 

observations.

The local relative water-level trend, which may be 

interpreted as a temporally restricted rate of local sea-level 

rise, is calculated as the sum of shallow subsidence and global 

eustatic sea-level rise. Shallow subsidence is the difference 

between accretion and CEC (Cahoon and others, 1995), which 

are site-specific measurements. Eustatic sea-level rise is set to 

the global mean of 0.31 centimeters per year (Solomon and 

others, 2007). Eustatic sea-level rise rates will be refined as 

better estimates become available. 

The position of the projected wetland relative to the 

projected hydrologic frame determines the SVI score. 

Specifically, the SVI score is defined in equation 3 as the 

percentile rank of the projected wetland elevation within the 

projected water-level distribution:

100 1 * 2

P n n N

  = −     (3)

where 

n

wate t Y r i

1 t

N Ywater i

is the rank of the value of the projected 

wetland elevation,

n

wate t Y r i

1 t

N Ywater i

, within the 

projected hydrologic frame,

n

wate t Y r i

1 t

N Ywater i, that 

contains N total observations.

The SVI scores are interpreted such that sites with higher 

scores are flooded less and are less vulnerable to submergence 

within the next 5 years. For example (fig. 6), a ranking in the 

62d percentile represents a wetland with an elevation that is 

higher than 62 percent of the water level observations over a 

5-year period. In other words, only 38 percent of the waterlevel observations are greater than the wetland elevation, 

indicating that the wetland will only be flooded 38 percent of 

the time. The underlying assumption is that wetlands situated 

at lower elevations within the hydrologic frame are more 

Figure 6. An example of a sitescale assessment of submergence 

vulnerability for site CRMS0544 by using 

the Submergence Vulnerability Index 

(SVI). Specific model parameters are 

provided as follows: Cumulative elevation 

change (CEC) = 0.73 (cm y-1); accretion 

= 0.43 (cm y-1); shallow subsidence = 

0.29 (cm y-1); eustatic sea-level rise (ESLR) 

= 0.31 (cm y-1); site relative water level 

trend = 0.02 (cm y-1); SVI score = 62.17. 

CRMS0544

SVI score = 62.17

Time, in years

Elevation, in centimeters above the

North A

merican

Vertical Datum of 1988 

Percentile rank

0

10

20

30

40

50

60

70

90

62.7

10

90th percentile water level

10th percentile water level

Mean water level

Cumulative elevation change (CEC)

95 percent confidence band

EXPLANATION

2012 2013 2014 2015 2016 2017
8 Submergence Vulnerability Index Development and Application to CRMS Sites and CWPPRA Projects

vulnerable to future changes in sea level and submergence, 

than wetlands situated at higher elevations (Kirwan and others, 

2012). This assumption is supported by an expansive body 

of research, which has demonstrated that excessive flooding 

adversely impacts wetland plant growth (DeLaune and others, 

1983; Mendelssohn and McKee, 1988) ultimately disrupting 

the positive feedback between organic matter accumulation, 

sedimentation, and elevation sustainability (Morris and others, 

2002). In contrast, increasing the elevation of the marsh 

surface can result in better drainage (King and others, 1982) 

and increased productivity (Stagg and Mendelssohn, 2010), 

thereby resulting in an optimal level of flooding, where the 

critical feedbacks between vegetation and flooding result in 

elevation maintenance and resilience (Odum and others 1979; 

Morris and others, 2002; Kirwan and Murray, 2008; Stagg and 

Mendelssohn, 2011). 

Although the relations between vegetation production 

and flooding were used to develop the concept of the SVI, it is 

important to emphasize that the objective of this index is not to 

identify thresholds of collapse or productivity but to evaluate 

the intensity of flooding that is likely to occur based on the 

wetland-elevation trajectory and local water-level trends. 

Therefore, to achieve a complete assessment of a wetland, 

this index should be used in conjunction with supplemental 

data (for example, plant production, nutrient availability, 

species richness, among others) that will contribute to the 

understanding of the overall ecological status of the system.

Implementation and Evaluation

The primary objective of the CRMS analytical index 

development effort is to provide a mechanism to assess the 

effectiveness of CWPPRA projects. Restoration projects can 

be evaluated by comparing the SVI scores of CRMS sites 

within project boundaries to CRMS reference sites (fig. 7). 

Additionally, the coastwide distribution of CRMS sites 

allows SVI scores to be used for multiscaled evaluations. 

For example, a CRMS project site can be compared to other 

CRMS sites across multiple scales including all sites within 

the basin, all sites within the same wetland classification, or all 

sites across the coast (fig. 8). 

Similarly, a coastwide assessment can compare all 

restoration sites to all reference sites. This approach will allow 

the coastal restoration community to assess the effectiveness 

of particular restoration projects, regional trends, and the 

overall effectiveness of a coastwide restoration plan. The SVI 

can also be used to perform a general coastwide assessment 

to identify areas of vulnerability. These general assessments 

can be used to focus study and restoration strategy planning. 

In a demonstration of a coastwide assessment, the SVI was 

calculated by using data from 153 CRMS sites that satisfied all 

of the data completeness criteria (fig. 9). 

The scores were distributed relatively evenly along the 

scale with a median score of 54, with 25 percent of the sites 

scoring below a score of 23 and 25 percent of sites scoring 

above 72 (fig. 10A). Spatially, however, the scores were not 

evenly distributed across the coast. Regions that are highly 

susceptible to submergence can be highlighted so that the 

Figure 7. Submergence Vulnerability Index scores for an 

individual site (CRMS0544 project site) located within a restoration 

project. This individual site score was compared to all other 

Coastwide Reference Monitoring System (CRMS) sites located 

within in the same wetland classification and hydrologic basin 

within the project boundary (CRMS project sites) or outside of the 

project boundary (CRMS reference sites). Error bars represent 

standard errors.

Figure 8. Multiple scale comparison of Submergence 

Vulnerability Index (SVI) scores between an individual site 

(CRMS0544) and all sites within the same basin, all sites within 

the same wetland classification, and all sites coastwide. The 

lower and upper limits of the box plot represent the first and 

third quartile, respectively. The solid middle line represents the 

median and the dashed line represents the mean. The error bars 

represent the 10th and 90th percentiles.

Time, in years

Submergence Vulnerability Index (SVI) score

0

20

40

60

80

100

CRMS project sites

CRMS reference sites

CRMS0544 project site

EXPLANATION

1 2 3 4 5 6 Teche-Vermilion Basin Intermediate

wetland classification 

Coastwide

Submergence Vulnerability Index (SVI) score

0

20

40

60

80

100

CRMS0544

SVI = 62.17

EXPLANATION
Figure 9. Coastwide spatial distribution of wetland submergence vulnerability represented by Submergence Vulnerability Index (SVI) scores for CoaMonitoring System (CRMS) sites containing at least 5 years of elevation-change data. Sites with SVI score calculations are located in the Calcasieu BBasin (ME), Teche-Vermilion Basin (TV), Atchafalaya Basin (AT), Terrebonne Basin (TE), Barataria Basin (BA), Lake Pontchartrain Basin (PO), Breton SRiver Delta (MR).

AT

BA

CS

ME

PO

TV

TE

Submergence Vulnerability Index scores

High: 100

Low: 0

EXPLANATION

Louisiana

Study area

0 2 0 4 0 6 0 MIL E S

0 3 0 6 0 K IL O ME T E R S
10 Submergence Vulnerability Index Development and Application to CRMS Sites and CWPPRA Projects

Figure 10. A) Distribution of coastwide Submergence Vulnerability Index (SVI) scores. The lower and upper limits of the box plot 

represent the first and third quartile, respectively. The solid middle line represents the median, and the dashed line represents the mean. 

The error bars represent the 10th and 90th percentiles. B) Shallow subsidence rates separated by hydrologic basin: Atchafalaya Basin 

(AT), Barataria Basin (BA), Breton Sound (BS), Calcasieu-Sabine Basin (CS), Mermentau Basin (ME), Mississippi River Delta (MR), Lake 

Pontchartrain Basin (PO), Terrebonne Basin (TE) and Teche-Vermilion Basin (TV).

Submergence Vulnerability Index (SVI) scores 

0

20

40

60

80

100

Hydrologic basin

Shallo

w subsidence, in cm y-1

-2

-1

0

1

2

3

4

5

Coastwide scores

A

B

AT BA BS CS ME MR PO TE TV
References Cited 11

causes of vulnerability may be determined. For example, the 

terminally impounded Mermentau (ME; fig. 10B) Basin on 

the Chenier Plain had the most sites within the lower quartile 

of the score distribution (scores <24). In addition to high 

rates of subsidence (fig. 10B), water levels in the Mermentau 

Basin area are managed for agriculture, thereby resulting in 

high water levels compared to wetland surface elevation. 

Submergence in other hydrologic basins of the coast was due 

to high rates of shallow subsidence (Breton Sound, CalcasieuSabine Basin, and Pontchartrain Basins). 

Assessing a site’s vulnerability to submergence can 

be an initial and critical step in assessing ecosystem health, 

project effectiveness, and planning and implementation 

of adaptive management. Furthermore, incorporating 

supplemental data describing other abiotic and biotic 

processes known to influence wetland elevation (Cahoon and 

others, 2006) can illuminate the mechanisms contributing to 

submergence vulnerability on a site-specific scale and inform 

management decisions.

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