Uncertainty analysis and simulation modeling for Lake Okeechobee research prioritization

Abstract

A decision analytic framework and the USEPA mechanistic water quality model WASP4 were used to prioritize research and monitoring needs to address the water quality management objective, reduce algal blooms to an acceptable level in Lake Okeechobee. With the WASP4 model as a scientific assessment framework, proposed research and monitoring projects should be evaluated for their effectiveness in reducing WASP4 prediction uncertainty. Sensitivity analysis based on either model calculations or expert judgment may be used to estimate the reduction in prediction uncertainty associated with proposed projects. A utility-based approach can then be developed to select from among proposed research and monitoring projects. Selected projects may be expected to provide scientific information to reduce model prediction uncertainty for the use of the model in decision making.