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The benefit of continuous modelling in hydrological studies is widely recognized since it provides the practitioner with effective hydrological outputs for risk assessment. However, this approach is still not common mainly because it needs as input simulated rainfall time series. Many rainfall generation methods exist yet there are still two main challenges: (i) many rainfall models are available without a clear suggestion on which is the most appropriate to use, (ii) most rainfall models are not user-friendly and require significant theoretical background to successfully be applied.In this contribution, we test eight rainfall models by evaluating the performances of the simulated rainfall time series when used as input for a specific continuous rainfall-runoff model, named COSMO4SUB (COntinuous Simulation MOdel For Small and Ungauged Basin), particularly designed for small and ungauged basins. The rainfall models selected here are: two versions of the Complete Stochastic Modelling Solution (CoSMoS-1s and 2s); three versions of Bootstrap-based models; the classical Bartlett Lewis and Neymann-Scott rectangular pulses models; and a mixed method based on monthly simulation and multifractal cascade disaggregation.The comparison was performed by analyzing runoff time series obtained with the COSMO4SUB model and using as input the rainfall time series simulated by the eight models and the observed one. We selected and investigated several general properties, such as the average number of flood events, the marginal distribution of peak, volume, duration and antecedent dry period before the flood, and their dependence structure.The comparison confirms the capability of all models to provide realistic flood events and allows identifying the models to be further improved and tailored for data scarce hydrological risk applications. |
