Bayesian estimation of intensity–duration–frequency curves and of the return period associated to a given rainfall event |
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Authors: | David Huard Alain Mailhot Sophie Duchesne |
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Institution: | (1) Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke St. West, Montreal, QC, H3A 2K6, Canada;(2) Institut National de la Recherche Scientifique, Centre Eau, Terre et Environnement, 490, de la Couronne, Quebec, QC, G1K 9A9, Canada |
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Abstract: | Intensity–duration–frequency (IDF) curves are used extensively in engineering to assess the return periods of rainfall events
and often steer decisions in urban water structures such as sewers, pipes and retention basins. In the province of Québec,
precipitation time series are often short, leading to a considerable uncertainty on the parameters of the probabilistic distributions
describing rainfall intensity. In this paper, we apply Bayesian analysis to the estimation of IDF curves. The results show
the extent of uncertainties in IDF curves and the ensuing risk of their misinterpretation. This uncertainty is even more problematic
when IDF curves are used to estimate the return period of a given event. Indeed, standard methods provide overly large return
period estimates, leading to a false sense of security. Comparison of the Bayesian and classical approaches is made using
different prior assumptions for the return period and different estimation methods. A new prior distribution is also proposed
based on subjective appraisal by witnesses of the extreme character of the event. |
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