Understanding Ecosystem Response and Infrastructure Vulnerability to Sea-Level Rise for Gulf Islands National Seashore
USGS researchers will will survey elevation and vegetation in wetlands and vegetated dunes on Horn, Petite Bois, and Ship Islands; Correct the best available lidar-based digital elevation model; estimate inundation for the Gulf Islands National Seashore under various water levels and relative sea-level rise scenarios; and quantify and predict potential marsh migration for the Gulf Islands National Seashore for several alternative relative sea-level rise scenarios.
The Science Issue and Relevance: During this century, accelerated sea-level rise (SLR) will impact habitats across the entire coastal zone, including oyster reefs, intertidal mudflats, and estuarine marshes, along with upslope habitats, such as forested wetlands, freshwater marshes, and upland forests and grasslands. Natural resource managers require information on how these important coastal ecosystems may change over time to assist with future-focused land management and stewardship. This is especially the case for coastal parks, preserves, and sites in the National Park Service (NPS) System.
High-resolution elevation data provide a foundational layer needed to understand regional hydrology and ecology under present and future conditions. Over the past 20 years, light detection and ranging (lidar) technology has transformed our ability to monitor elevation and topography through time via the development of periodic high-resolution digital elevation models (DEMs). However, elevation bias is typically unknown in wetlands, and can be substantial, especially in densely vegetated areas. While DEM products often provide an elevation uncertainty in the product metadata, these estimates typically are not representative of vertical uncertainty in wetlands. Understanding elevation uncertainty in lidar data and accounting for the error is an important first step for: 1) producing or refining static or hydrodynamic models to estimate contemporary and future water surface levels, and 2) predicting future ecologic shifts, such as upslope migration of tidal marsh.
In addition to understanding the ecosystem response to SLR, it is equally important to understand the vulnerability of cultural resources on public lands to these changing conditions. For example, contemporary and future nuisance flooding is expected to be a major problem for infrastructure in low-lying coastal areas. A corrected DEM can be used to develop static inundation models that provide a first-cut approximation for predicting flooding on low-lying public lands and highlight areas for upslope wetland migration.
Methodology for Addressing the Issue: This project is funded by the NPS through the Inflation Reduction Act. The focal area for this project will be the Mississippi Unit of the Gulf Islands National Seashore (GUIS). For this unit, the project will include the following objectives:
1. Survey elevation and vegetation in wetlands and vegetated dunes on Horn, Petite Bois, and Ship Islands.
2. Correct the best available lidar-based DEM.
3. Using the corrected DEM, estimate inundation for the GUIS under various water levels and relative SLR scenarios.
4. Quantify and predict potential marsh migration for the GUIS for several alternative relative SLR scenarios.
Future Steps: Beyond the deliverables of this project, the corrected DEMs for the Mississippi Unit of the GUIS will provide an important data source that can provide monitoring information for the NPS and be used for subsequent modeling efforts (e.g., hydrodynamic marsh modeling or hurricane impact modeling).
USGS researchers will will survey elevation and vegetation in wetlands and vegetated dunes on Horn, Petite Bois, and Ship Islands; Correct the best available lidar-based digital elevation model; estimate inundation for the Gulf Islands National Seashore under various water levels and relative sea-level rise scenarios; and quantify and predict potential marsh migration for the Gulf Islands National Seashore for several alternative relative sea-level rise scenarios.
The Science Issue and Relevance: During this century, accelerated sea-level rise (SLR) will impact habitats across the entire coastal zone, including oyster reefs, intertidal mudflats, and estuarine marshes, along with upslope habitats, such as forested wetlands, freshwater marshes, and upland forests and grasslands. Natural resource managers require information on how these important coastal ecosystems may change over time to assist with future-focused land management and stewardship. This is especially the case for coastal parks, preserves, and sites in the National Park Service (NPS) System.
High-resolution elevation data provide a foundational layer needed to understand regional hydrology and ecology under present and future conditions. Over the past 20 years, light detection and ranging (lidar) technology has transformed our ability to monitor elevation and topography through time via the development of periodic high-resolution digital elevation models (DEMs). However, elevation bias is typically unknown in wetlands, and can be substantial, especially in densely vegetated areas. While DEM products often provide an elevation uncertainty in the product metadata, these estimates typically are not representative of vertical uncertainty in wetlands. Understanding elevation uncertainty in lidar data and accounting for the error is an important first step for: 1) producing or refining static or hydrodynamic models to estimate contemporary and future water surface levels, and 2) predicting future ecologic shifts, such as upslope migration of tidal marsh.
In addition to understanding the ecosystem response to SLR, it is equally important to understand the vulnerability of cultural resources on public lands to these changing conditions. For example, contemporary and future nuisance flooding is expected to be a major problem for infrastructure in low-lying coastal areas. A corrected DEM can be used to develop static inundation models that provide a first-cut approximation for predicting flooding on low-lying public lands and highlight areas for upslope wetland migration.
Methodology for Addressing the Issue: This project is funded by the NPS through the Inflation Reduction Act. The focal area for this project will be the Mississippi Unit of the Gulf Islands National Seashore (GUIS). For this unit, the project will include the following objectives:
1. Survey elevation and vegetation in wetlands and vegetated dunes on Horn, Petite Bois, and Ship Islands.
2. Correct the best available lidar-based DEM.
3. Using the corrected DEM, estimate inundation for the GUIS under various water levels and relative SLR scenarios.
4. Quantify and predict potential marsh migration for the GUIS for several alternative relative SLR scenarios.
Future Steps: Beyond the deliverables of this project, the corrected DEMs for the Mississippi Unit of the GUIS will provide an important data source that can provide monitoring information for the NPS and be used for subsequent modeling efforts (e.g., hydrodynamic marsh modeling or hurricane impact modeling).