STORAGE (STOchastic RAinfall GEnerator): A User-Friendly Software for Generating Long and High-Resolution Rainfall Time Series

Abstract

The MS Excel file with VBA (Visual Basic for Application) macros named STORAGE (STOchastic RAinfall GEnerator) is introduced herein. STORAGE is a temporal stochastic simulator aiming at generating long and high-resolution rainfall time series, and it is based on the implementation of a Neymann–Scott Rectangular Pulse (NSRP) model. STORAGE is characterized by two innovative aspects. First, its calibration (i.e., the parametric estimation, on the basis of available sample data, in order to better reproduce some rainfall features of interest) is carried out by using data series (annual maxima rainfall, annual and monthly cumulative rainfall, annual number of wet days) which are usually longer than observed high-resolution series (that are mainly adopted in literature for the calibration of other stochastic simulators but are usually very short or absent for many rain gauges). Second, the seasonality is modelled using series of goniometric functions. This approach makes STORAGE strongly parsimonious with respect to the use of monthly or seasonal sets for parameters. Applications for the rain gauge network in the Calabria region (southern Italy) are presented and discussed herein. The results show a good reproduction of the rainfall features which are mainly considered for usual hydrological purposes.

Comparative Evaluation of the Rainfall Erosivity in the Rieti Province, Central Italy, Using Empirical Formulas and a Stochastic Rainfall Generator

“…Results of numerical tests carried out for the Colli sul Velino rain gauge station were presented and discussed. In particular, the observed rainfall data were compared with numerical results obtained using a synthetic rainfall generator model developed by De Luca et al [44][45][46][47][48]. Some peculiar features were observed.…”

“…Moreover, De Luca et al [46,47] proposed a parsimonious modelling of seasonality, which was adopted in this work. The goal is to avoid an over parameterization by using monthly or seasonal parameter sets.…”

The Benefit of Continuous Hydrological Modelling for Drought Hazard Assessment in Small and Coastal Ungauged Basins: A Case Study in Southern Italy

“…In this study the synthetic rainfall generator implemented in STORAGE software [34,35] has been used. In detail, the model constitutes a modified version of the Neyman-Scott Rectangular Pulses (NSRP) model [49,50].…”

“…In order to do that, in this work we first applied two recently developed hydrological models. The former is a synthetic rainfall generation model (STORAGE) [34,35] that was applied in a climate change scenario. The latter is a continuous rainfall-runoff model (COSMO4SUB) [36][37][38].…”

“…In detail, the application of STORAGE here performed consisted of the following steps. First, under the hypothesis of stationary process, STORAGE was calibrated according to [35], i.e., by employing the parameters of amount-duration-frequency (ADF) curves, mean values for MAP, mean annual number of wet days, and mean values of DJF, MAM, JJA, and SON rainfall depths.…”