FLORIDA AQUIFER VULNERABILITY ASSESSMENT

Florida Aquifer Vulnerability Assessment (FAVA) is a developing model intended to use geographic information system (GIS) data to predict the vulnerability of Florida’s major aquifer systems to contamination. Model development is currently in the preliminary stages consisting of five countywide projects. The overall intent of FAVA is the development of a tool for environmental, regulatory and planning professionals to facilitate the protection of Florida’s ground-water resources. FAVA differs from the Environmental Protection Agency DRASTIC model in that the newer technique is GIS-based and accounts for Florida’s karstic terrane. Current methods employed in FAVA model development include Weights of Evidence, Fuzzy Logic and a Travel Time method. While all three methods yield similar results in the lower and higher ranges of vulnerability, the mid-ranges differ, as do methods for model validation. Each of the methods utilize the following spatial layers: thickness of confining unit, soil permeability, and the percentage of an area covered by karst features.

Weights of Evidence quantifies relationships between spatial layers with actual contaminant occurrences in order to support a hypothesis. Using these calculated relationships, interactions can be analyzed to yield a data-driven predictive model.

A Fuzzy Logic model, utilizing the same spatial layers, however, will be estimated subjectively using expert knowledge to approximate the relative importance of each feature, similar to the foundation for the DRASTIC model. Fuzzy memberships can then be combined using a range of operators to calculate a knowledge-driven predictive model.

The Travel Time method, explained in its simplest form, is the estimated time it takes surface water to reach the top of the saturated zone of an aquifer. This estimate is calculated by adding the time it takes for a unit of water to migrate through the soil vadose zone, the near surface vadose zone geology and the confining unit (if present). The output is then multiplied by a factor to account for karst feature density. Areas with short travel times would then be classified as highly vulnerable in the predictive FAVA model.