Systematic Identification of DO-BOD Model Structure

by Bruce Beck, Research Fellow; Control Div., Dept.of Engrg., Univ. of Cambridge, Cambridge, England,
Peter Young, Professorial Fellow; Centre for Resource and Environmental Studies, Australian National Univ., Canberra, Australia,

Serial Information: Journal of the Environmental Engineering Division, 1976, Vol. 102, Issue 5, Pg. 909-927

Document Type: Journal Paper

Discussion: Bowles David S. (See full record)
Closure: (See full record)

Abstract: The Extended Kalman Filter (EKF) provides a logical statistically based extension to those existing approaches to model fitting based on deterministic model response error (surface) minimization. Its crucial feature as a basis for identification, however, is the recursive nature of the algorithm which permits the estimation of possible variations in the model parameters. Depending upon whether such estimated variations are realistic or not, bearing in mind the physical nature of the dynamic system, it is possible to formulate criteria for model adequacy. This approach to model identification was applied to the problem of modeling DO-BOD interaction in a freshwater river system based on daily field data. It was found that the basic model structure, as defined by a dynamic version of the Streeter-Phelps equations, was inadequate and, in the case of the river considered, it was necessary to introduce additional sustained sunlight terms to account for the effects of floating algal populations.

Subject Headings: Errors (statistics) | Data processing | Hydrologic models | Terrain models | Dynamic models | Structural models | Kalman filters | Filters

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