An Illustration of Model Structure Identi cation

The purpose of this article is to discuss the importance of uncertainty analysis in water quality modeling, with an emphasis on the identi cation of the correct model speci cation. A wetland phosphorus retention model is used as an example to illustrate the procedure of using a ltering technique for model structure identi cation. Model structure identi cation is typically done through model parameter estimation. However, due to many sources of error in both model parameterization and observed variables and data, error-in-variable is often a problem. Therefore, it is not appropriate to use the least squares method for parameter estimation. Two alternative methods for parameter estimation are presented. The rst method is the maximum likelihood estimator, which assumes independence of the observed response variable values. In anticipating the possible violation of the independence assumption, a second method, which coupled a maximum likelihood estimator and Kalman lter model, was presented. Furthermore, a Monte Carlo simulation algorithm is presented as a preliminary method for judging whether the model structure is appropriate or not. Key Terms: Everglades, Kalman lter, maximum likelihood estimator, modeling/statistics, phosphorus, uncertainty analysis, water quality, wetlands.