Informing conservation planning using sea-level rise and
storm surge impact estimates in the Galveston Bay and
Jefferson County, Texas area
Ben Gilmer¹
Jorge Brenner²
Jonathan Sheets²
The Nature Conservancy¹
Global Marine Initiative
Seattle, Washington, 98101
The Nature Conservancy²
Texas Chapter
Corpus Christi, Texas, 78401
A report produced for the Gulf of Mexico Alliance
Funding for this model application was provided by The Nature Conservancy, who also provided
extensive GIS processing in support of this analysis. Funding for TNC was provided through a grant from
the Gulf of Mexico Foundation to support the Habitat Conservation & Restoration Team, and the
Mississippi Department of Marine Resources to support the Community Resilience Team, part of the
Governor’s Gulf of Mexico Alliance.
January 2012
Introduction
Coastal communities across the Gulf of Mexico are increasingly vulnerable to coastal hazards including
sea level rise (Weiss et al. 2011; Karl et al. 2009; IPCC 2007). The Gulf of Mexico contains 20,000 km² of
land below 1.5 meters in elevation (Titus and Richman 2001) and is one of the most vulnerable regions
to sea level rise (SLR) in the continental U.S. (Weiss et al. 2011; Thieler and Hammar-Klose 1999). Local
planners and property owners have generally not decided how they will act in response to SLR (Titus et
al. 2009) nor have they developed future shoreline management strategies to address SLR (CCSP 2009).
These increasing hazards threaten not only the human-built infrastructure and coastal communities, but
also natural habitats and ecosystems. Wetlands are among the Gulf of Mexico’s most economically and
ecologically important habitats and comprise thirty-one percent (28,372 mi²) of land within the U.S. Gulf
coastal watershed (NOAA 2006). These habitats provide many benefits for human and natural
communities including storm surge protection, erosion prevention, pollutant removal and fish and
wildlife habitat (NOAA 2011). An example of the economic importance of marsh systems can be
illustrated in the annual commercial shellfish harvest within the Gulf’s coastal wetlands; for 2009 alone,
the harvest value was $474 million (National Marine Fisheries Service 2010). The Gulf of Mexico’s
wetlands have experienced significant declines in recent decades (NOAA 2011) and accelerated SLR
projections are expected to further increase the rate and magnitude of wetland loss (Nicholls 2004). At
current rates of loss, one-third of Louisiana’s coastal wetlands will be lost by the year 2050 (America’s
Energy Coast 2009).
Planning for and responding to a global threat such as SLR ultimately falls to regional and local decision
makers. These decision makers need the critical information necessary to support choices for managing
human and natural communities in the face of the coastal changes that are underway (CCSP 2009; NRC
2009; Najjar et al. 2000).
The Galveston Bay area is a highly developed region that accounts for the second largest recreational
boating industry in the nation and 40% of the nation’s petrochemical production, and constitutes the
second largest port in the US. Substantial habitat loss has occurred due to coastal development,
shoreline erosion, and land subsidence around Galveston Bay. These shoreline changes make this area
increasingly vulnerable to SLR and storm surge inundation. Identifying and addressing the risks posed by
SLR and other climate-related threats to ecosystems and infrastructure is of utmost importance to
sustain a healthy flow of benefits to the coastal communities (CHF 2010).
Through a participatory stakeholder process, the project team and Galveston Bay and Jefferson County
regional stakeholders identified ongoing and future conservation planning efforts that were best suited
to be informed by SLR and storm surge projections, socioeconomic indicators, and marsh migration
scenarios. Through this effort, the project team and stakeholders decided to explore the following
questions:
1. What are the potential impacts of a 1 meter sea level rise to irregularly- and regularly-flooded
marshes in the study area?
2. Which communities are potentially most at risk to hurricane storm surge, and how might sealevel rise increase present-day risk to storm surge?
3. Which communities might be most or least resilient to future changes based on socioeconomic
indicators, inundation exposure, and marsh viability?
2
4. How might SLR impacts and future marsh habitat distribution inform land acquisition and
management planning?
Our study estimates the potential impacts of SLR and storm surge to human communities and natural
habitats, with emphasis in coastal marsh, in the Galveston Bay region to allow decision makers to more
easily develop adaptation strategies that foster coastal resilience in the face of a changing climate.
These analyses are examples that are intended to help current conservation planning and management
decisions account for future changes and to provide examples of how Sea Level Affecting Marshes
Model SLAMM, SLR, storm surge, and socioeconomic data can be used in to support these efforts.
Study area
The Galveston Bay region (Figure 1) contains
a complex system of marshes, sand flats,
seagrass beds, and oyster reefs. These
habitats provide nursery and spawning
grounds for crab, shrimp, oyster and fish
species, and protection for coastal
communities during storm events. This bay
system provided the second most productive
fishery in the U.S. until Hurricane Ike landed
in 2008. Galveston Bay produced more
oysters than any other estuary in the nation
(until Hurricane Ike), and constituted the
largest commercial harvest of blue crabs of
any estuary in Texas. It also accounts for
more than one-half of Texas’s recreational
fishing revenues (CHF 2010). Given the
prevalence, sensitivity, and economic and ecological importance of regularly- and irregularly-flooded
marshes in the Galveston Bay region, this study
focused on these habitats, which collectively Figure 1. Galveston Bay study area.
cover over 65,000 hectares (161,000 acres)
within the study area. Regularly-flooded marshes experience constant tidal flow and therefore contain
higher salinity soils while irregularly flooded marshes typically experience greater salinity and climatic
variability. The variability between regularly- and irregularly-flooded marsh createses differentiated
populations of flora and fauna that are driven by their respective tolerance and dependence on salinity
and water table levels. For more details regarding our study area, see Lester and Gonzalez (2002).
Methods
The methods used in this study follow an overarching project framework for informing ongoing and
future conservation planning efforts through SLR and storm surge projections, socioeconomic indicators,
and marsh migration scenarios. This framework is outlined in Figure 2. The methods described herein
detail our approach for assessing socioeconomic and ecological risk to SLR and storm surge, coastal
habitats’ relation to vulnerable human communities, and management options needed to support
conservation planning for climate-enhanced coastal change.
3
Conservation and
Resiliency Assessment
Framework
What is at risk of
SLR and storm
surge?
Ecological
Where are coastal
habitats that
benefit human
communities?
What are
conservation and
management
options?
Existing
management
areas
Socioeconomic
Future priority
areas
Figure 2. Conservation and Resiliency Assessment Framework.
Sea-level rise scenarios
The Sea-Level Affecting Marshes Model (SLAMM) was employed for the Galveston Bay region to
simulate potential changes in tidal marsh area and other coastal habitat types in response to SLR.
SLAMM accounts for the dominant processes involved in wetland conversion and shoreline
modifications during long-term SLR (Clough et al. 2010) and has been used to estimate impacts of SLR in
the Gulf of Mexico and in other regions of the U.S. (e.g. Craft et al. 2009;
http://www.gulfofmexicoalliance.org/working/restoration/technology_development/technology_devel
opment.html ). SLAMM incorporates information on land elevations, land cover, tide ranges, land
subsidence rates, sedimentation and erosion rates and SLR to model the future spatial distribution of
marsh habitat based on specified SLR scenarios. The land cover classes used by SLAMM in our study
area include: tidal fresh marsh, tidal swamp, swamp, regularly-flooded marsh, inland open water,
irregularly-flooded marsh, developed dry land, inland-fresh marsh, undeveloped dry land, estuarine
open water, and open ocean. The wetland classes are based on habitat classifications defined by the
National Wetland Inventory and non-wetland land cover classes come from the National Land Cover
Dataset.
For a thorough accounting of SLAMM model processes and the underlying assumptions and equations,
see Clough et al. (2010). For details regarding SLAMM parameterization and data usage specific to the
Grand Bay region analysis used in this study, see Clough and Polaczyk (2011) and these scenarios can be
viewed at www.slammview.org. Though multiple SLR scenarios were run for the Galveston Bay region
using SLAMM, for this study the project team decided to only use the eustatic 1 meter SLR scenario for
the years 2025, 2050, 2075, 2100 given that several recent studies have indicated that sea levels are
likely to approach 1 meter by the year 2100 (Nicolls 2011; Vermeer and Rahmstorf 2009).
Storm-surge scenarios
4
The project team partnered with ARCADIS US, Inc. to generate storm surge scenarios for the Galveston
Bay region. Multiple storm surge simulations were generated using the Advanced Circulation (ADCIRC)
model (ARCADIS 2011), though only the following two scenarios were selected for this study: 1) a storm
surge scenario similar to Hurricane Ike which struck the Galveston Bay region in September of 2008 and
2) a storm surge scenario similar to Hurricane Ike with 1 meter of SLR. For more information on the
methodology and results of these simulations, see ARCADIS (2011).
Identification of conservation targets and risk analyses
The project team facilitated a participatory workshop with Galveston Bay regional staff on April 6th,
2011, hosted by the Galveston Bay Estuary Program’s Natural Resource Uses Team, in order to identify
ongoing and future conservation planning efforts that might best be informed by the SLR, storm surge,
and marsh migration projections provided by SLAMM. After the project team and stakeholder group
discussed and visualized the draft results from the SLAMM analysis, the project team and stakeholders
identified three core questions to further explore in order to better inform their conservation planning
and management efforts. The questions were as follows (restated from the Introduction):
1. What are the potential impacts of a 1 meter sea level rise to irregularly- and regularly-flooded
marshes in the study area?
2. Which communities are potentially most at risk to hurricane storm surge, and how might sealevel rise increase present-day risk to storm surge?
3. Which communities might be most or least resilient to future changes based on socioeconomic
indicators, inundation exposure, and marsh viability?
4. How might SLR impacts and future marsh habitat distribution inform land acquisition and
management planning?
Based on these questions, the project team identified the following four analyses to better inform the
stakeholder questions: 1) Marsh Change and Viability Analysis, 2) Community Risk Analysis, 3)
Community Resilience Analysis, and 4) Long-term Marsh Management Analysis. The SLAMM SLR
scenarios, storm surge scenarios, and U.S. census data were the primary input datasets for these
analyses, in addition to local management data for the Galveston Bay region.
1. Marsh Change and Viability Analysis
The project team and stakeholders wanted to identify the existing irregularly- and regularly-flooded
marshes that are most likely to persist into the future, and those that are most threatened to be lost to
SLR. SLAMM was used to calculate where marshes were predicted to migrate, persist, or lose
distribution for the time period between 2009 and 2100 under a 1 meter SLR scenario, and a viability
estimate was determined for each existing marsh polygon by summarizing persistence and loss values
per marsh. The marsh advancement zone, as used in this study, refers to the path through which
marshes are predicted to move landward under a 1m scenario through 2100. Additionally, to better
relate marsh viability to socioeconomic data in subsequent analyses (see Community Risk Analysis), and
to illustrate aggregated marsh viability at the human community level, a marsh viability analysis was also
calculated at the census block group scale. The latter block group level calculation was determined via
the following equation:
Viability per block group = (Marsh Loss – Marsh Persistence) + Marsh Gain
Marsh viability was then classified from “Low to High” based on a 5-class Natural Breaks classification to
help show maximum differences in marsh viability per census block group. The Natural Breaks
5
classification method is a “binning” method that groups similar values that maximize the differences
between classes (de Smith et al. 2009).
In summary, the marsh change and viability calculations are reported in two geographic units: per
existing marsh polygon and summarized per census block group. The process and methods for the
Marsh Change and Viability Analysis at the marsh scale are detailed in Figure 3, and the Marsh Change
and Viability Analysis methods at the block group scale are detailed in Figure 4.
Extract
irregularly- and
regularly-flooded
marsh land cover
classes from
SLAMM
scenarios
Delineate
individual marsh
complexes
Map marsh
advancement
zones for 20092100
Calculate change
in marsh
distribution, per
marsh, 20092100
Classify marsh
loss/gain/persistence to
illustrate potential marsh
viability
Figure 3. Approach for marsh change and viability analysis at individual marsh scale.
Extract irregularly- and
regularly-flooded marsh
land cover classes from
SLAMM scenarios
Marsh viability
calculation at the block
group scale:
Calculate marsh loss,
gain, and persistence
from 2009 to 2100
Viability per block
group = Marsh Loss –
Marsh Persistence +
Marsh Gain
Classify block groups to
illustrate marsh viability
Figure 4. Approach for marsh change and viability analysis at the block group scale.
2. Community Risk Analysis
Most state and local coastal hazard risk assessments in the U.S. are focused on current hazard risk, and
do not incorporate potential enhanced risks due to climate change impacts such as SLR (Shepard et al.
2012; Frazier et al. 2010). Following methods similar to those used in a recent study by Shepard et al.
(2012), we identified communities facing the highest risk of storm surge and SLR. Granger (2003) and
Shepard (2012) conceptualize risk as: Risk (i) = Hazard (i) X Elements at Risk (i) X Vulnerability, where (i)
is a particular hazard scenario. Furthermore, “exposure” is a function of the Hazard X Elements at Risk
portion of the risk equation (Granger 2003). We used this conceptual risk framework to identify
communities that face the highest risk to hurricane storm surge, and provide examples of how sea-level
rise can increase present-day risk to storm surge.
6
The process and methods used to
characterize exposure and risk
are outlined in Figure 5.
Exposure was calculated by
classifying all inundated block
groups into “high,” “medium,”
and “low,” based on the
percentage of each block group
inundated per storm surge or SLR
scenario. Block groups with less
than 5% and more than 0.1% of
inundation were classified as
“low”; less than 15% and more
than 5% were “medium” and
greater
than
15%
were
considered to be of “high”
exposure.
The Social Vulnerability Index
(SoVI) data was provided by the
Hazards
and
Vulnerability
Research
Institute
at
the
University of South Carolina
(http://webra.cas.sc.edu/hvri/pro
ducts/sovi.aspx). HVRI describes
the SoVI as follows: “SoVI
measures the social vulnerability
COMMUNITY RISK
EXPOSURE
VULNERABILITY
Classify inundated block
groups
Classify Social
Vulnerability Index
(SoVI)
Create inundation raster: extract
estuarine water land cover class
from SLAMM scenarios or create
storm surge inundation raster from
ADCIRC simulation outputs
Calculate percentage of
census block group
inundated
of U.S. counties to environmental Figure 5. Community Risk Analysis methodology framework
hazards. The index is a
comparative metric that facilitates the examination of the differences in social vulnerability among
counties. SoVI is a valuable tool for policy makers and practitioners. It graphically illustrates the
geographic variation in social vulnerability. It shows where there is uneven capacity for preparedness
and response and where resources might be used most effectively to reduce the pre-existing
vulnerability. SoVI® also is useful as an indicator in determining the differential recovery from disasters.
The index synthesizes 31 socioeconomic variables, which the research literature suggests contribute to
reduction in a community’s ability to prepare for, respond to, and recover from hazards. The data are
culled from national data sources, primarily those from the United States Census Bureau.” The SoVI
used in this study is available at the block group scale and downloadable from here:
http://www.csc.noaa.gov/digitalcoast/data/sovi/. In this analysis, “High” social vulnerability was
categorized as the top 20% and “Low” is the lowest 20%, while “Medium” is the middle 60%. For more
information about SoVI, see http://webra.cas.sc.edu/hvri/products/sovi.aspx.
Finally, the Community Risk index was calculated by classifying the exposure index with the SoVI into a
1-5 (low to high) ranking system where blocks groups that experienced high exposure and high social
vulnerability (e.g. “5”), were considered highest risk, while block groups with medium exposure and
medium social vulnerability were considered medium risk (e.g. “3”), and so forth. The Community Risk
Analysis framework is outlined in Figure 4.
7
3. Community Resilience Analysis
The Community Resilience Analysis combined the Community Risk Analysis and Marsh Viability Analysis
to identify communities that might be least (or most) resilient based on a community’s social
vulnerability, exposure to storm surge, and the long-term
COMMUNITY
viability of marsh systems within each block group. Marsh
RESILIENCE
systems offer many ecosystem services to human
communities such as preventing shoreline erosion, storm
surge buffering, increasing water quality, and providing
Marsh Change
fish habitat (Shepard et al. 2011). This analysis assumes
Community Risk
and Viability
that communities are more resilient if they have lower
Index
Index
social vulnerability, are less exposed to storm surge
inundation and have marsh systems that can either
maintain or increase in size with 1 meter of sea level rise
by the year 2100. There are many locally-dependent
Exposure
factors that make a community more or less resilient to
natural hazards, and some of these nuances cannot be
captured with census block group level data, nor do viable
marsh systems alone create more resilient human
Vulnerability
communities. This analysis should be interpreted as a
demonstration of how coastal hazard risk information can
be combined with ecosystem viability data to inform
conservation planning activities that benefit both human and natural communities.
Figure 6. Community Resilience Analysis framework.
Furthermore, the census data used in this analysis reflects conditions for the year 2000, the year for
which this data was most recently available. This analysis is limited in that it compared socioeconomic
conditions for the year 2000 with future inundation scenarios without modeling how the social
landscape might change over the next 80 years. Projecting future socioeconomic conditions was beyond
the scope of this work, and other published studies have had similar temporal limitations (e.g.
Hallegatte et al. 2011, Frazier et al. 2010, and Zhang 2001). Ultimately, this analysis is intended to help
coastal managers and decision makers plan for and respond to future changes, by illustrating how future
climate-enhanced coastal hazards can impact communities throughout the Galveston Bay region. The
Community Resilience Analysis used in this study is one example of how socioeconomic and ecological
information can be integrated with coastal hazards data to characterize community resilience.
The Community Resilience Analysis framework is outlined in Figure 6. Using an indexing method similar
to that which was used in the Community Risk Analysis, the combined marsh viability and community
risk indices were classified on a 1-5, low to high, scale using an if-then logic model where communities
with low risk and high marsh viability would be considered “most resilient” (e.g. “5”) and communities
with high risk and low marsh viability would be considered “least resilient” (e.g. “1”). It is also important
to note that only block groups that currently contain marsh distribution were considered in this analysis.
4. Long-term Marsh Management Analysis
The project team performed a high level gap analysis to better inform existing and future land
acquisition and management planning efforts to better account for SLR impacts. Federal, state, and TNC
management areas were analyzed to illustrate existing marsh distribution lying within existing
management areas, in addition to the amount of marsh advancement zone (the path through which
marshes are predicted to move landward under a 1m scenario through 2100) within and outside of
8
existing management areas. Next, marsh advancement zones immediately adjacent to existing
management areas were selected as priority protection areas in case existing management areas could
be expanded to include these advancement zones, which might allow for the landward migration of
marsh systems. The methods and process used for this analysis are outlined in Figure 7.
Long-term Marsh
Management
Needs
Existing
Management
Areas
Existing and
Future Marsh
Distribution
Existing Marsh
Future Marsh
Advancement
Figure 7. Long-term marsh management analysis framework
9
Results
Sea-level rise scenarios
Irregularly flooded marshes are expected to significantly decrease between 2009 and 2100, while
regularly flooded marshes are expected to greatly increase, often replacing irregularly-flooded marshes
throughout the study area. SLAMM predicts land cover changes to be less severe between 2009-2050,
with more drastic shifts occurring between 2050 and 2100. Regularly-flooded marshes in the study area
are expected to increase by 21,755 hectares (53,759 acres) between 2009 and 2100 and irregularlyflooded marshes are expected to decline by 33,450 hectares (82,658 acres). Furthermore, 35,979
hectares (88,907) of existing land is projected to convert to estuarine water by 2100.
The full results for the SLAMM analysis are detailed in Clough and Polaczyk (2011) and gains and losses
are summarized in Figure 8 below for the most commonly occurring land cover types.
Undeveloped Dryland
Categories
Tidal Flat
2100
Estuarine Water
2075
2050
Irregularly Flooded Marsh
2025
Regularly Flooded Marsh
-100,000
-60,000
-20,000
20,000
60,000
100,000
Acres
Figure 8. Potential land cover change for the Galveston Bay region under a 1 meter sea-level rise scenario between 2004 and
2100.
Storm surge scenarios
Figure 9 illustrates the inundation extent for the 3 storm surge scenarios, as taken from ARCADIS (2011).
The storm surge analysis found that the 2008 storm surge scenario inundated an estimated 233,875
hectares (577,918 acres) of land. The 2100 storm surge scenario with 1 meter of SLR inundated an
estimated 293,823 hectares (726,053 acres), which is an increase of 25% percent from the 2008
scenario, indicating that 1 meter of SLR can increase near term storm surge exposure by a factor of 25%.
More details regarding the predicted storm surge impacts can be found in ARCADIS (2011).
10
Figure 9. Plot of inundation extents for storm surge scenarios.
Conservation and Risk Analyses
1. Marsh Change and Viability Analysis
Marsh distribution in 2009 was calculated to be 65,382 hectares (161,562 acres). Total marsh
advancement zone (the landward path beyond existing marsh through which marshes are predicted to
move) under a 1 meter SLR scenario from 2009 to 2100 was projected to be 39,299 hectares (97,111
acres). Importantly, the marsh advancement zone does not include existing marsh and is only a
calculation of projected marsh advancement beyond 2009 distribution. These results indicate that areas
beyond marsh need to be managed for marshes to sustain in the future; for comparison, the area of the
predicted marsh advancement zone is roughly 60% of the size of existing marsh distribution throughout
the study area.
The most viable marsh systems were largely found in the Jefferson County and eastern Galveston Bay
portions of the study area (Figures 10 and 11). Also, as seen in Figure 12, marsh systems in the East Bay
portion of the study area will require substantial room to migrate to sustain through the year 2100. At
11
the block group community scale, marsh systems on the Bolivar Peninsula and at Texas City were least
viable, while the most viable marsh systems were in Jefferson County and the Trinity River area (Figure
13). Overall marsh change between 2004 and 2100 results in 11,695 hectares (28,899 acres) of marsh
habitat lost.
Figure 10. Change analysis of all marshes 2009-2100.
12
Figure 11. Marsh viability per existing marsh (1m SLR).
Figure 12. Existing marsh with total advancement zone (2004 through 2100).
13
Figure 13. Marsh viability analysis at the block group scale.
2. Community Risk Analysis
The Social Vulnerability Index (Figure 14) illustrates that some of the most vulnerable human
communities were found on Galveston Island, Baytown, Channelview, and the Bolivar Peninsula (among
other communities). Within the study area, 59 block groups were found to be of high social
vulnerability, followed by 317 that were classified as medium vulnerability, and 133 were of low social
vulnerability.
Figures 15, 16, and 17, show the percentage of each block group inundated under each scenario, in
addition to the compounding impacts of SLR onto a present-day storm surge exposure. As seen in Table
1, 155 block groups are projected to face between 75 and 100% inundation under a Hurricane Ike storm
surge scenario with 1 meter of SLR, compared with only 84 block groups that face the same risk under
the Hurricane Ike storm alone. The SLR-only inundation scenario found 195 block groups projected to
face 1 to 5 % inundation, with only 1 block group experiencing over 50% inundation.
Table 1. Number of block groups inundated per scenario
Percent of block
group
inundated
none
1 to 5
6 to 25
26 to 50
51 to 75
76 to 100
1
meter
SLR
275
195
34
4
1
0
2008
storm
surge
289
22
54
29
31
84
2008 storm
surge plus 1m
SLR
209
31
37
37
40
155
14
The Bolivar Peninsula, Smith Point, Galveston Island, Jefferson County and Texas City areas are most
exposed under all three scenarios with 195 block groups experiencing over 50% inundation under the
SLR plus storm surge scenario. The Community Risk Index can be seen in Figures 18, 19, and 20. Some
of the most at-risk communities to a 1 meter SLR scenario are Crystal Beach on the Bolivar Peninsula,
Galveston Island, and the Bay Oaks Harbor neighborhood (Figure 18). Figure 20 shows the impact of SLR
in increasing storm surge risk throughout the study area. Notably, several communities (such as the
southern Liberty County area) that are at low risk to a 1 meter 2100 SLR scenario, face the highest risk to
storm surge under both the 2008 and 2100 storm surge scenarios.
Figure 14. Social Vulnerability Index.
15
Figure 15. Exposure to a 1 meter SLR scenario.
Figure 16. Exposure to a storm surge from Hurricane Ike (2008; no SLR).
16
Figure 17. Exposure to a storm surge from Hurricane Ike plus 1 meter of SLR (2100).
17
Figure 18. Community Risk Index (1m SLR scenario).
Figure 19. Community Risk Index (Hurricane Ike, no SLR).
18
Figure 20. Community Risk Index (Hurricane Ike plus 1 meter of SLR).
3. Community Resilience Analysis
Areas that were projected to experience substantial marsh loss under the 1 meter SLR scenario, had
high social vulnerability, and faced high exposure to a 2008 Hurricane Ike storm surge simulation were
found to be least resilient in the Community Resilience Analysis (Figure 21). Conversely, those
communities that contained more viable marshes, lower social vulnerability and less exposure to storm
surge, were found to be most resilient. Only 101 block groups were considered for this analysis, as the
other 408 block groups did not contain marsh distribution in 2009. Of these 101 block groups, 6 were
found to be least resilient, while 3 were found to be most resilient based on this analysis. 92 block
groups were categorized as between medium-low and medium high resiliency. In particular, the
Community Resilience Analysis found Crystal Beach, Green Lake (near Tiki Island), and
Chocolate/Christmas Bay to be among the least resilient communities in the study area, while some of
the most resilient communities are in Kemah, Beach City, Trinity Bay, and Smith Point/Anahuac areas.
19
Figure 21. Community Resilience Analysis.
4. Long-term Marsh Management Analysis
Though regularly-flooded marsh systems have the potential to increase in various parts of the study
area, the Long-term Marsh Management Analysis found that the vast majority of these marsh
advancement zones are outside of management areas (Figures 22 and 23). Our results found that
35,824 hectares (88,525 acres) of existing marsh distribution were found to be within management
areas while 29,617 hectares (73,185 acres) were outside of management areas. Under a 1 meter SLR
scenario, 7,986 hectares (19,735 acres) of marsh advancement zone are projected to be within existing
management areas while 31,312 hectares (77,375 acres) are estimated to be outside of these
management areas (Table 2).
Table 2. Existing and future marsh management gap analysis.
Marsh type
Area within existing management areas (ha)
Area outside of existing management areas (ha)
Existing marsh
35,824 (88,525 acres)
29,617 (73,185 acres)
Marsh advancement zone
7,986 (19,735 acres)
31,312 (77,375 acres)
20
Importantly, only 20% of future marsh advancement zone are within existing management areas, while
80% remain outside of existing management areas. Several key land acquisition or conservation
management areas could be expanded to account for future marsh distribution, and these
recommended areas are illustrated in Figures 24-26. Federal management areas that could be
expanded include the Anahuac National Wildlife Refuge and the Brazoria National Wildlife Refuge, as
these wildlife refuges are adjacent to some of the most substantial advancement zones in the study area
(Figure 24). State management areas that are most critical for expansion include the Galveston Island
State Park, the J.D. Murphree Wildlife Management Area, and the Candy Abshier Wildlife Management
Area (Figure 25). The Nature Conservancy’s (and partners) management areas are also adjacent to key
marsh advancement zones which are illustrated in Figure 26. These management areas include the High
Island Area, the West Galveston Bay easement (w/ Galveston Bay Foundation), and the Elm Grove area
on the Bolivar Peninsula.
Figure 22. Management areas in the Galveston Bay region.
21
Figure 23. Management areas with existing marsh, and marsh advancement zones.
Figure 24. Priority marsh protection areas adjacent to federally managed areas.
22
Figure 25. Priority marsh protection areas adjacent to state managed areas.
Figure 26. Priority marsh protection areas adjacent to TNC managed areas.
23
Recommendations and Conclusion
Our study suggests that SLR impacts should be incorporated into ongoing conservation planning and
management activities within the Galveston Bay region. Specifically, key parcels of land adjacent to
existing management areas could be acquired and/or sustainably managed to allow for the landward
migration of vulnerable marsh habitats. Between 2004 and 2100, over 20,000 hectares (52,000 acres) of
land are predicted to contain critical marsh refuge for both irregularly- and regularly-flooded marshes.
These areas should be prioritized for conservation and/or acquisition and we highlight priority areas that
are adjacent to existing federal, state, and TNC management areas.
This analysis also shows that human communities throughout the Galveston Bay region face serious risks
to SLR and storm surge, and that storm surge impacts from “today’s” hurricane will be substantially
amplified by climate-enhanced SLR and storm surge in the future. Our study also suggests that
infrastructure and land use development planning should factor in the impacts of SLR and storm surge
as many developable lands, based on SLR and storm surge projections, and building regulations are
predicted to be at risk of permanent inundation due to SLR. Furthermore, this study suggests that all
land use planning decisions should not only factor in future inundation zones, but also critical marsh
advancement zones and their relation to socially vulnerable communities, for which these ecosystems
provide myriad services ranging from shoreline protection to fish nurseries for nearby human
communities.
The analyses and results presented here are intended to inform decision makers within the Galveston
Bay region of the potential impacts of SLR and storm surge and to support current and future
conservation planning and management decisions. Through a participatory stakeholder process, the
project team and stakeholders identified key management questions and employed spatial analyses to
illustrate how future changes can be factored into near-term and ongoing planning activities to allow
them to better account for future changes. Our study identifies vulnerable coastal ecosystems and
human communities and the potential impacts of SLR and storm surge in the Galveston Bay region to
allow decision makers to more easily develop adaptation strategies that foster coastal resilience in the
face of a changing climate.
24
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