Coastal responses to sea level rise (SLR) include inundation of wetlands, increased shoreline erosion, and increased flooding during storm events. Hydrodynamic parameters such as tidal ranges, tidal prisms, tidal asymmetries, increased flooding depths and inundation extents during storm events respond nonadditively to SLR. Coastal morphology continually adapts toward equilibrium as sea levels rise, inducing changes in the landscape. Marshes may struggle to keep pace with SLR and rely on sediment accumulation and the availability of suitable uplands for migration. Whether hydrodynamic, morphologic, or ecologic, the impacts of SLR are interrelated. To plan for changes under future sea levels, coastal managers need information and data regarding the potential effects of SLR to make informed decisions for managing human and natural communities. This review examines previous studies that have accounted for the dynamic, nonlinear responses of hydrodynamics, coastal morphology, and marsh ecology to SLR by implementing more complex approaches rather than the simplistic "bathtub" approach. These studies provide an improved understanding of the dynamic effects of SLR on coastal environments and contribute to an overall paradigm shift in how coastal scientists and engineers approach modeling the effects of SLR, transitioning away from implementing the "bathtub" approach. However, it is recommended that future studies implement a synergetic approach that integrates the dynamic interactions between physical and ecological environments to better predict the impacts of SLR on coastal systems.

Standard approaches to determining the impacts of sea level rise (SLR) on storm surge flooding employ numerical models reflecting present conditions with modified sea states for a given SLR scenario. In this study, we advance this paradigm by adjusting the model framework so that it reflects not only a change in sea state but also variations to the landscape (morphologic changes and urbanization of coastal cities). We utilize a numerical model of the Mississippi and Alabama coast to simulate the response of hurricane storm surge to changes in sea level, land use/land cover, and land surface elevation for past (1960), present (2005), and future (2050) conditions. The results show that the storm surge response to SLR is dynamic and sensitive to changes in the landscape. We introduce a new modeling framework that includes modification of the landscape when producing storm surge models for future conditions.

This work outlines a dynamic modeling framework to examine the effects of global climate change, and sea level rise (SLR) in particular, on tropical cyclone-driven storm surge inundation. The methodology, applied across the northern Gulf of Mexico, adapts a present day large-domain, high resolution, tide, wind-wave, and hurricane storm surge model to characterize the potential outlook of the coastal landscape under four SLR scenarios for the year 2100. The modifications include shoreline and barrier island morphology, marsh migration, and land use land cover change. Hydrodynamics of 10 historic hurricanes were simulated through each of the five model configurations (present day and four SLR scenarios). Under SLR, the total inundated land area increased by 87% and developed and agricultural lands by 138% and 189%, respectively. Peak surge increased by as much as 1 m above the applied SLR in some areas, and other regions were subject to a reduction in peak surge, with respect to the applied SLR, indicating a nonlinear response. Analysis of time-series water surface elevation suggests the interaction between SLR and storm surge is nonlinear in time; SLR increased the time of inundation and caused an earlier arrival of the peak surge, which cannot be addressed using a static ("bathtub") modeling framework. This work supports the paradigm shift to using a dynamic modeling framework to examine the effects of global climate change on coastal inundation. The outcomes have broad implications and ultimately support a better holistic understanding of the coastal system and aid restoration and long-term coastal sustainability.

A spatially-explicit model (Hydro-MEM model) that couples astronomic tides and Spartina alterniflora dynamics was developed to examine the effects of sea-level rise on salt marsh productivity in northeast Florida. The hydrodynamic component of the model simulates the hydroperiod of the marsh surface driven by astronomic tides and the marsh platform topography, and demonstrates biophysical feedback that non-uniformly modifies marsh platform accretion, plant biomass, and water levels across the estuarine landscape, forming a complex geometry. The marsh platform accretes organic and inorganic matter depending on the sediment load and biomass density which are simulated by the ecologicalmarsh component (MEM) of the model and are functions of the hydroperiod. Two sea-level rise projections for the year 2050 were simulated: 11 cm (low) and 48 cm (high). Overall biomass density increased under the low sea-level rise scenario by 54% and declined under the high sea-level rise scenario by 21%. The biomass-driven topographic and bottom friction parameter updates were assessed by demonstrating numerical convergence (the state where the difference between biomass densities for two different coupling time steps approaches a small number). The maximum coupling time steps for low and high sea-level rise cases were calculated to be 10 and 5 years, respectively. A comparison of the Hydro-MEM model with a parametric marsh equilibrium model (MEM) indicates improvement in terms of spatial pattern of biomass distribution due to the coupling and dynamic sea-level rise approaches. This integrated Hydro-MEM model provides an innovative method by which to assess the complex spatial dynamics of salt marsh grasses and predict the impacts of possible future sea level conditions.

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.