Hydrologic Generating Model Selection

by Keith William Hipel, Asst. Prof.; Dept. of Systems Design, Univ. of Waterloo, Waterloo, Ontario, Canada,
Angus Ian McLeod, Asst. Prof.; Statistics and Actuarial Sci. Group, Univ. of Western Ontario, London, Ontario, Canada,
Edward A. McBean, Assoc. Prof.; Dept. of Civil Engrg., Univ. of Waterloo, Waterloo, Ontario, Canada,


Serial Information: Journal of the Water Resources Planning and Management Division, 1979, Vol. 105, Issue 2, Pg. 223-242


Document Type: Journal Paper

Abstract: When modeling seasonal river flows for generating possible flow sequences for use in reservoir design, it is often necessary to first invoke a deterministic transformation to remove seasonality and thus eliminate the need for differencing. To select which stationary stochastic model to fit to the resulting transformed data, a two-stage decision-making process is recommended. The first stage consists of eliminating those models which do not possess a proper statistical fit to the data, while further discrimination can be done at the second stage by judging the remaining models according to the economic criteria of the particular reservoir disign. Simulation procedures are used to obtain designs using various hydrologic generating models for a hydroelectric reservoir complex on the South Saskatchewan River in Canada. Both Box-Jenkins and Fractional Gaussian noise processes are considered in the model selection studies. A new simulation procedure is developed for use with a Fractional Gaussian noise model.

Subject Headings: Hydrologic models | Data processing | Reservoirs | Gaussian process | Stationary processes | Hydraulic design | River flow | Seasonal variations | North America | Saskatchewan | Canada

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