Coastal Wetland Response To Sea-Level Rise In A Fluvial Estuarine System

Keywords

Apalachicola; fluvial estuarine system; Hydro-MEM; salt marsh; sea-level rise

Abstract

Coastal wetlands are likely to lose productivity under increasing rates of sea-level rise (SLR). This study assessed a fluvial estuarine salt marsh system using the Hydro-MEM model under four SLR scenarios. The Hydro-MEM model was developed to apply the dynamics of SLR as well as capture the effects associated with the rate of SLR in the simulation. Additionally, the model uses constants derived from a 2-year bioassay in the Apalachicola marsh system. In order to increase accuracy, the lidar-based marsh platform topography was adjusted using Real Time Kinematic survey data. A river inflow boundary condition was also imposed to simulate freshwater flows from the watershed. The biomass density results produced by the Hydro-MEM model were validated with satellite imagery. The results of the Hydro-MEM simulations showed greater variation of water levels in the low (20 cm) and intermediate-low (50 cm) SLR scenarios and lower variation with an extended bay under higher SLR scenarios. The low SLR scenario increased biomass density in some regions and created a more uniform marsh platform in others. Under intermediate-low SLR scenario, more flooded area and lower marsh productivity were projected. Higher SLR scenarios resulted in complete inundation of marsh areas with fringe migration of wetlands to higher land. This study demonstrated the capability of Hydro-MEM model to simulate coupled physical/biological processes across a large estuarine system with the ability to project marsh migration regions and produce results that can aid in coastal resource management, monitoring, and restoration efforts.

Publication Date

11-1-2016

Publication Title

Earth's Future

Volume

4

Issue

11

Number of Pages

483-497

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1002/2016EF000385

Socpus ID

84997531409 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84997531409

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