Paper No. 196-4
Presentation Time: 9:00 AM
ADVANCING METHODS TO PARAMETERIZE EMERGENT VEGETATION VARIABLES FOR COASTAL IMPACT MODELS
Emergent wetland vegetation has been shown to mitigate coastal inundation and erosion hazards by reducing wave energy through friction (Shepard et al., 2011). Estuarine wetland habitats are seldom considered in coastal protection planning because predictive models require improved input data. Uncertainty remains in hydrodynamic wave models that quantify and forecast the protection potential of wetlands that are built upon broad assumptions and sparse data. These data are required to refine models and improve understanding of non-linear interactions of vegetation, waves, and sediment transport/deposition that shape coastal geomorphology. The vegetation parameters (biomass, stem density, rigidity, etc.) that affect wave dissipation vary considerably in space and time and are difficult, time-consuming and expensive to quantify. This study aims to advance current methodology to more efficiently measure vegetation parameters that will enable long-term forecasting of hydrodynamic wave models. This semi-automatic and rapid method will pair side-on photography with remote sensing and terrestrial LiDAR to quantify vegetation parameters and extrapolate these biophysical characteristics across the study area. Additionally, using multispectral side-on imagery we will create a taxonomic spectral library of vegetation to assist in long-term vegetation monitoring and remote sensing efforts. Hydrodynamic wave models will be analyzed for sensitivity to variations in vegetation parameters in order to isolate controlling characteristics reducing wave impacts alongshore. We have chosen to study Port Susan Bay (Stillaguamish Delta), a western Washington estuary that has experienced up to a kilometer of marsh retreat since the 1960s and exhibits highly stratified vegetation assemblages. This presentation will introduce our quantitative methodology and present preliminary results as we prepare for our first winter field season. We hope to characterize variability in vegetation biomass with winter senescence and wave transformation across a transition from non-vegetated tidal flat to dense tidal marsh.