Coastal Marsh Mapping & Analysis
Motivation
Coastal marshes are highly valued for the ecosystem services they provide, yet they are disappearing at an alarming rate worldwide due to seawater intrusions. Marshes also store a significant amount of carbon and nutrients that are released to the open ocean when wetland areas become completely submerged by rising sea water. This carbon and nutrient flux impacts ocean biology and biogeochemistry cycles and can impair coastal water quality. The submergence of coastal marshes also transforms them from sinks to sources of greenhouse gases, further accelerating climate change and rates of sea-level rise. Current global ocean climate models, such as the NASA GISS ModelE, do not include the carbon and nutrient flux from submerged coastal marshes and are potentially neglecting a critical positive feedback loop.
Erosion of marsh peat in Yellow Bar, Jamaica Bay due to sea level rise
Schematic of current and improved model representation
Research Goals & Objectives
In collaboration with NASA, the Di Vittorio Lab will assess the relative significance of carbon and nutrient fluxes into the ocean from coastal marsh losses using a combination of diverse datasets, including a large database of historical satellite imagery and ocean color data, in-situ and remotely-sensed tidal and land elevation data, marsh depth estimates from in-situ sediment cores, and reanalysis data and physically-based simulations of past and future sea-levels. This research will produce new data products that can be integrated into future NASA Ocean Biology and Biochemistry (OBB) studies and will provide new information and insights on the role of coastal marshes in the global carbon and nutrient cycles.
We will accomplish this overarching goal through the following research objectives:
1. Quantify historical areas of coastal marsh loss along the Atlantic and Gulf Coast over the past 40 years using satellite imagery.
2. Study patterns of change and identify relationships between areal losses and drivers of loss, including relative sea level rise, storm events, spatial inundation patterns, and land elevation changes for representative sites.
3. Quantify future areas of coastal marsh loss for the representative sites based on sea level and storm changes under multiple climate change scenarios.
4. Combine coastal marsh loss maps (past and future) with marsh depth and carbon concentration data to quantify the carbon fluxes that have entered (and will enter) some key coastal ecosystems over time.
5. Compare carbon fluxes that enter the ocean from coastal marshes to those that enter from rivers to perform an initial assessment of the relative significance of coastal marsh fluxes.
This three-year project was recently funded by the NASA Ocean Biology and Biogeochemistry Program through a $548,000 award (Proposal No 20-OBB20-0047) and will conclude in May 2024. The highly diverse research team that is leading this effort brings expertise in satellite-based classification algorithms, multivariate data analysis and statistical modeling, wetland ecology and biogeochemistry, physical oceanography, and coupled ocean and climate modeling. The team members are listed below.
1. Dr. Courtney Di Vittorio (PI, WFU)
2. Dr. Yasin Wahid Rabby (Postdoctoral Research Scholar, WFU)
3. Dr. Christian Braneon (Co-I, NASA)
4. Dr. Dorothy Peteet (Co-I, NASA)
5. Dr. Anastasia Romanou (Co-I, NASA)
Illustration of the general classification approach. Image a was presented in Watson et al. (2017) and highlights areas of loss in the Mary Donovan Marsh in Rhode Island. The images in b show the upland (orange), water (blue), and transitional (green) classes that were selected in Google Earth Engine and a sample Landsat image. Figure c presents a time series comparison of the MNDWI values that correspond with each class. The solid line shows the annual median value.