Bayesian Estimation of Design Floods under Regional and Subjective Prior Information

Robert Kirnbauer, Sylvia Schnatter and Dieter Gutknecht
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Robert Kirnbauer: Technische Universitaet Wien, Institut fuer Hydraulik, Gewaesserkunde und Wasserwirtschaft
Sylvia Schnatter: Technische Universitaet Wien, Institut fuer Hydraulik, Gewaesserkunde und Wasserwirtschaft
Dieter Gutknecht: Technische Universitaet Wien, Institut fuer Hydraulik, Gewaesserkunde und Wasserwirtschaft

A chapter in Probability and Bayesian Statistics, 1987, pp 285-294 from Springer

Abstract: Abstract Usually design floods are estimated as certain quantiles of a cumulative distribution function (CDF) fitted to a sample of yearly maxima of floods observed at a gauging station. If such observations do not exist at a site where a hydraulic structure is to the built, the hydrologist can collect flood data for several years during the planning phase. This small new sample, however, will not be sufficient for estimating the design flood by means of common flood statistics but it fits as one source of information to be combined with some prior information within the BAYESIAN estimation procedure. Prior information can be taken from long time flood records observed at stations of the same region to be incorporated in a data-based a-priori density function of the parameters.

Keywords: Probability Density Function; Likelihood Function; Cumulative Distribution Function; Prior Information; Recurrence Interval (search for similar items in EconPapers)
Date: 1987
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DOI: 10.1007/978-1-4613-1885-9_30

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