Applications of System Identification and Parameter Estimation in Water Quality Modeling

Applications of techniques of system identification and parameter estimation in water quality modeling are surveyed. This survey of the literature covers three areas: river water quality, lake water quality, and wastewater treatment plant modeling. The applications cited are classified according to the type of algorithm used for calibration, the type of model, and the field data used. Two broad distinctions are made between: (a) off-line and recursive methods of parameter estimation; and (b) internally descriptive (state-space) and black box (input/output) model types. In order to assist the classification, a number of estimation algorithms are very briefly introduced. Although there are clearly different lines of development in each area of water quality modeling, it is possible to identify problems common to all three areas. The major problems discussed concern the availability of field data, levels of noise in the data, and model structure identification