HR: 1330h
AN: G23A-05    [Abstracts]
TI: Modeling Water Flow in the Everglades Wetlands Using Interferometric Synthetic Aperture Radar (InSAR)Observations
AU: Garcia-Martinez, R
EM: regarcia@miami.edu
AF: University of Miami, Department of Civil, Architectural and Environmental Engineering, Miami, FL 33124 United States
AU: Miralles-Wilhelm, F
EM: fmiralles@miami.edu
AF: University of Miami, Department of Civil, Architectural and Environmental Engineering, Miami, FL 33124 United States
AU: Wdowinski, S
EM: shimonw@rsmas.miami.edu
AF: University of Miami, Division of Marine Geology and Geophysics, 4600 Rickenbacker Causeway, Miami, FL 33149 United States
AB: New space-based Interferometric Synthetic Aperture Radar (InSAR) observations of the Everglades wetlands provide high spatial resolution maps of water level changes that are essential for improved modeling efforts of surface water sheetflow. In this study, we model the Everglades' Water Conservation Area 1 (WCA-1), which is used to restore, protect, and preserve water resources and wildlife in southern Florida. We use a 2-D surface flow finite element model that considers the vegetation cover as a spatially roughness variable, topography data and influence of peripheral canals. The model provides the water elevation and velocity field throughout the conservation areas, based on rainfall record, discharge inputs and outflows through managed hydraulic structures. Our study focuses on two InSAR observed water level change patterns in WCA-1 acquired during two seasons and different weather conditions. The first pattern describes water level changes in the spring of 1998, showing a radial change caused mainly due to flow along the peripheral canals. The second pattern describes longitudinal change occurring in the fall of 2004, in the peak of hurricanes season, which caused abrupt flow income into the conservation areas. In order to improve the model results, we use a two-step procedure to calculate the vegetation roughness coefficient, which varies both in space and time. The first step includes a Supervised Image Analysis classification of WCA-1 according to remotely sensed determined vegetation maps. The estimated values are assigned to the model for the initial run. In the second step, we use an iterative procedure adjusting the vegetation roughness coefficients until the modeled water level changes agree with the InSAR observations. This technique of coupling high spatial resolution InSAR images with numerical modeling allows improved predictive abilities in the WCA under different weather scenarios, thus helping water resources managers and operators in their decision making.
DE: 1860 Runoff and streamflow
DE: 1890 Wetlands
DE: 1899 General or miscellaneous
SC: Geodesy [G]
MN: 2005 Joint Assembly