This study focuses on the return period evaluation for design hyetographs, which is\nusually estimated by adopting a univariate statistical approach. Joint Return Period (JRP) and\ncopula-based multivariate analysis are used in this work to better define T-year synthetic rainfall\npatterns which can be used as input for design flood peak estimation by means of hydrological\nsimulation involving rainfall-runoff (RR) models. Specifically, a T-year Design Hyetograph (DH)\nis assumed to be characterized by its peak H, at the chosen time resolution Dt, and by the total\nrainfall height W, cumulated on its critical duration dCrit, which has been a priori fixed. As stated\nin technical literature, the choice of the expression for JRP depends on which event is deemed as\ncritical for the investigated system; the most important cases are: (i) all the variables must exceed a\ncertain magnitude to achieve critical conditions; or (ii) at least one variable must be greater than a\nthreshold; or (iii) critical conditions are induced by all the events with a joint Cumulative Density\nFunction (CDF) overcoming an assigned probability threshold. Once the expression for JRP was\nchosen, the relationship among multivariate T-year design hyetographs and T-year design flood peak\nwas investigated for a basin located in Calabria region (southern Italy). Specifically, for the selected\ncase study, a summary diagram was obtained as final result, which allows the main characteristics\nof T-year DHs to be estimated, considering both the univariate and the copula based multivariate\nanalysis, and the associated T-year design flood peaks obtained through the simulation with a\nRR model.
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