Modelling annual maximum daily rainfall with the STORAGE (STOchastic RAinfall GEnerator) model

oleh: Andrea Petroselli, Davide Luciano De Luca, Dariusz Młyński, Andrzej Wałęga

Format: Article
Diterbitkan: IWA Publishing 2022-04-01

Deskripsi

In this work, the capability of STORAGE (STOchastic RAinfall GEnerator) model for generating long and continuous rainfall series for the upper Vistula basin (southern Poland) is tested. Specifically, in the selected area, only parameters of depth–duration–frequency curves are known for sub-daily rainfall heights (which are usually estimated in an indirect way by using Lambor's equations from daily data), while continuous daily series with a sufficient sample size are available. Attention is focused on modelling the sample frequency distributions of daily annual maximum rainfall. The obtained results are promising for further elaborations, concerning the use of STORAGE synthetic continuous rainfall data as input for a continuous rainfall-runoff approach, to be preferred with respect to classical event-based modelling. HIGHLIGHTS STORAGE model as an effective tool in rainfall modelling.; Possibility of modelling rainfall with different characteristics.; Promising results in the upper Vistula basin, paving the way for a continuous approach.;