Understanding the eco-geomorphologic feedback of coastal marsh under sea level rise: vegetation dynamic representations, processes interaction, and parametric sensitivity

Abstract:

A growing number of coastal eco-geomorphologic modeling studies have been conducted to understand coastal marsh evolution under sea level rise (SLR). Although these models quantify marsh topographic change as a function of sedimentation and erosion, their representations of vegetation dynamics that control organic sedimentation differ. How vegetation dynamic schemes and parameter values contribute to simulation outcomes is still not quantified. Additionally, the sensitivity of modeling outcomes on parameter selection in the available formulations has not been rigorously tested to date, especially under the influence of an accelerating SLR. This knowledge gap severely limits modeling accuracy and the estimation of the vulnerability of coastal marshes under SLR. In this study, we selected the coastal marshland at the Delaware Bay, USA, as our study site and used coastal eco-geomorphologic models with different vegetation dynamic schemes to investigate the eco-geomorphologic feedbacks of coastal marshes and parametric sensitivity under SLR scenarios. We found that marsh accretion rate near the seaward boundary can keep pace with moderate and high rates of SLR, while interior marsh regions are vulnerable to a high rate of SLR. The simulations with different vegetation schemes exhibit diversity in elevation and biomass profiles and parametric sensitivity. We also found that the model parametric sensitivity varies with rates of future SLR. Vegetation-related parameters and sediment diffusivity, which are not well measured or discussed in previous studies, are identified as some of the most critical parameters. Our findings provide insights to appropriately choose modeling presentations of key processes and feedbacks for different coastal marsh landscapes under SLR, which has practical implications for coastal ecosystem management and protection.