Coastal marsh environments exist at the intersection of human populations and the ocean. They provide economic output through commercial fisheries, tourism, and recreation and protect coastal communities during storm events. Coastal land managers and other stakeholders need vetted scientific information and user-driven tools to understand salt marshes’ vulnerability and to make informed decisions on management and policy actions to increase resiliency and protect vital habitats. This includes information regarding marsh extents, migration potential, and marsh productivity to understand impacts on critical species, designate future land use, and develop restoration strategies to mitigate marsh loss (e.g., thin layer placement, freshwater/sediment diversions). In making decisions regarding marshes, managers often rely on predictive models to assess vulnerabilities to changing conditions (e.g., climate, rising sea level) with associated uncertainty in model projections. Several marsh models are widely used to predict future marsh evolution, including (but not limited to) the Hydrodynamic-Marsh Equilibrium Model (HydroMEM), the Wetland Accretion Rate Model for Ecosystem Resistance (WARMER), Sea-Level Affecting Marshes Model (SLAMM), and NOAA’s Wetland Impacts and Migration Model (SLRWIMM). End users have expressed concerns and asked questions regarding the optimal selection of a marsh model tailored to a specific region, the interpretation of results, and the effective integration of these findings into their decision-making framework. Therefore, there is a need to evaluate the accuracy of existing marsh models and their utility to wetland managers and users through a coordinated approach that will enable more robust and reliable predictions.
Funder: U.S. Department of Commerce
Amount: $1,125,698
PI: Matthew Bilskie, College of Engineering