Bayesian Frequency Analysis

by Wilson H. Tang, (M.ASCE), Assoc. Prof. of Civ. Engrg.; Univ. of Illinois at Urbana-Champaign, Urbana, Ill.,

Serial Information: Journal of the Hydraulics Division, 1980, Vol. 106, Issue 7, Pg. 1203-1218

Document Type: Journal Paper

Discussion: Devi Rema (See full record)
Discussion: Rao Donthamsetti V. (See full record)
Closure: (See full record)

Abstract: The traditional frequency analysis attempts to fit a specific probability model on the basis of limited data, from which the flood level corresponding to a given return period is determined. Because of: (1) Scatter of observed data about the theoretical probability model; (2) uncertainty of extrapolation from limited measured record; and (3) uncertainty in selecting the correct model, the flood level corresponding to a given return period should be a random variable. Through a Bayesian regression analysis the above uncertainties can be used in evaluating the resulting probability distribution of the flood level. Alternatively, the return period associated with a given flood level may also be treated as a random variable whose distribution can also be evaluated. The model uncertainty may be then incorporated in evaluating hydrologic risk of a system over its expected life time.

Subject Headings: Data processing | Hydrologic models | Uncertainty principles | Bayesian analysis | Probability | Flood frequency | Frequency analysis |

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