2nd UF Water Institute Symposium Abstract

Submitter's Name Maria Librada Chu-Agor
Session Name Poster Session: Hydrologic, Biogeochemical and Ecological Processes 2
Category Hydrologic, biogeochemical and ecological processes
Poster Number 210
Author(s) Ma. Librada Chu-Agor,  Ag and Biological Engineering
  Rafael Muñoz-Carpena,  Agricultural and Biological Engineering Department, University of Florida
  Greg Kiker, Agricultural and Biological Engineering Department, University of Florida
  Alex Emanuelsson, Chalmers University of Technology, Gothenburg, Sweden
  Global sensitivity and uncertainty analysis of SLAMM for the purpose of habitat vulnerability assessment and decision making
  Climate change coupled with land use change was known to have adverse effects on coastal habitats, which are sanctuaries to endangered wildlife. In particular, sea level rise associated with climate change can drastically affect wetlands and beaches which are important habitats for shoreline dependent organisms. Recent studies used SLAMM (Sea Level Affecting Marshes Model) to simulate wetland conversion and shore-line modification for the purpose of habitat vulnerability assessment and decision making. However, there were concerns regarding the validity and suitability of the model due to the uncertainty involved in selecting many of the model’s empirical input parameters. The objectives of this study were to use a state-of-the-art screening and variance-based global sensitivity and uncertainty methods to: (1) identify the important input parameters that control the model’s output uncertainty (2) quantify the model’s global output uncertainty and apportion it to the direct and higher order contributions of the important parameters and (3) evaluate the consistency between model assumptions and model response. SLAMM was parameterized to simulate the changes in the coastal habitats of a selected site in the Eglin Air Force Base (Florida) for different IPCC sea level rise scenarios using data collected from different databases. The screening method of Morris for a qualitative ranking of the input parameters was then carried out followed by the variance-based method of Sobol for quantitative sensitivity and uncertainty analyses. The model structure was then evaluated by comparing the results of the uncertainty/sensitivity analyses with the response of the model. Preliminary results showed that elevation, tidal range, historical sea level rise trend, and accretion rate were the predominant parameters that influenced the uncertainty in the prediction of changes in coastal habitats. Results of the uncertainty/sensitivity analyses conformed to the conceptual basis of the model. This study represents an indispensible first step towards the integration of SLAMM with meta-population models to further assess habitat vulnerability for specific shoreline-dependent organisms.