Journal
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
Volume 28, Issue 6, Pages 1587-1599Publisher
SPRINGER
DOI: 10.1007/s00477-013-0813-z
Keywords
Flood frequency analysis; Peaks-over-threshold; Zero-inflated Poisson; Nonstationarity
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Funding
- Portuguese Science and Technology Foundation (FCT) [SFRH/BD/86522/2012]
- Fundação para a Ciência e a Tecnologia [SFRH/BD/86522/2012] Funding Source: FCT
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The peaks-over-threshold (POT) model with Poisson arrivals and generalized Pareto (GP) distributed exceedances remains a popular and useful tool for modelling hydrologic extremes. The use of the Poisson-GP model for flood frequency analysis requires the validation of the hypothesis that the distribution of the annual number of flood events may be described by a Poisson distribution. Such hypothesis is not always valid in practical applications. The present study concerns the use of an alternative distribution for modelling the annual number of floods-the zero-inflated Poisson (ZIP) distribution with two parameters. A ZIP-GP model for flood frequency analysis is proposed. This model is less restrictive than the Poisson-GP model since it allows for a more accurate description of the occurrence process in a POT framework if the fraction of years with no exceedances is significantly higher than the theoretical mass at zero of the Poisson distribution. Furthermore, a nonstationary model (NSZIP-GP) is presented, in which the parameters of the ZIP are allowed to change in time as a function of a covariate, which, even for stationary peak magnitudes, affects the annual maximum flood quantiles with a given non-exceedance probability. Applications of the ZIP-GP model to flood data from Northern Portugal and the evaluation of its performance relative to the Poisson-GP model, including assessments of quantile uncertainty, are presented. An illustrative application of the NSZIP-GP model, using the North Atlantic Oscillation as a covariate is also presented. The applications of both models include assessment of quantile uncertainty.
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