What is it about?
The derived distribution theory is exploited to develop an estimate method for bivariate return period of raifall events. Gumbel copula is utilized to construct a bivariate distribution of rainfall volume and duration. Events are categorized with regard to the peak flow discharge of the generated runoff. The method reliability is verified by comparing the flood frequency distributions obtained by the derived distribution theory and conventional statistics of continuous simulations, for a small urban catchment in Northern Italy.
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Why is it important?
The derived distribution theory once more demonstrates to provide a suitable strategy to assess the return period in multivariate cases. Accounting for mutual dependence of rainfall variable yields better assessments of flood frequency distributions, than those achieved through the classical assumption of independence, commonly adopted in the semi-probabilistic approach. In contrast to traditional multivariate inference techniques, copula functions are recognized to provide this advance.
Perspectives
This technique could find application to practical design problems of conveyance canals in small-medium size urban catchment, avoiding the development of complex continuous simulation models. An effective strategy to assess the rainfall return periods in a conceptually correct manner is suggested.
Doc Matteo MB Balistrocchi
Brescia University
Read the Original
This page is a summary of: Derivation of flood frequency curves through a bivariate rainfall distribution based on copula functions: application to an urban catchment in northern Italy's climate, Hydrology Research, February 2017, IWA Publishing,
DOI: 10.2166/nh.2017.109.
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