Application of Remote Sensing for Parameterization and Validation of a Coupled Hydrodynamic - Marsh Equilibrium Model for the Coastal Landscapes of the Northern Gulf of Mexico

To simulate the complex spatial patterns of tidal marsh responses to sea level rise requires linking local-scale vegetative growth and associated sediment feedbacks to estuary-wide hydrological processes. The strategy employed by the Ecological Effects of Sea Level Rise in the Northern Gulf of Mexico project (EESLR-NGOM) is to combine a high-resolution process-based model (i.e., Marsh Equilibrium Model) with a broad-scale hydrodynamics model (i.e., ADCIRC). Because of the large spatial extent of these heterogeneous wetland systems in the NGOM, remote sensing is required to initialize the model and to assess its performance. A LiDAR-derived digital elevation model (DEM) constrained by field-based real time kinematic (RTK) measures provide the topography of the marsh platform, adjacent upland berms, and the distribution of tidal creeks which influences the reciprocal dynamic between hydrologic flows and biomass accumulation. Statistical relationships between the aboveground biomass levels of the dominant species (i.e., big cordgrass - Spartina cynosuroides and black needlerush - Juncus roemerianus) and passive (e.g., Landsat and ASTER) and active (e.g., LiDAR and IfSAR) remote sensing provide the initial conditions of the vegetation across the salt marsh landscapes. The remotely-sensed patterns of biomass will also serve as a spatial validation of the coupled model. However, preliminary analyses of the remotely sensed and field data for the estuarine marsh vegetation at Apalachicola Bay revealed significant intra- and inter-annual differences in the biomass relationships. This high degree of spatio-temporal variation suggests that a more qualitative approach (e.g., high, medium, and low biomass levels) may be needed to interpret model accuracy.;