Uncertainty propagation from gridded precipitation datasets to streamflow simulations: application to the Reno River basin (Italy)

The development of gridded precipitation datasets has accelerated in recent decades, establishing them as crucial tools in hydrological analysis. This study aims to unravel the propagation of uncertainty in hydrological modelling from precipitation data to streamflow simulations. To this end, we examined the impact of using state-of-the-art datasets as model input for the Reno River basin in Italy. Our results show that (1) while seasonal precipitation patterns are similar, wet season and annual averages differ, particularly in the mountainous sub-basin; (2) the mountainous sub-basin exhibits large variability, with winter peak flows frequently underestimated; (3) uncertainties in precipitation propagate into the dry season, where variability is relatively greater than for the entire basin. We also examined the significance of addressing uncertainty in hydrological modelling at various scales. These findings underscore the influence of precipitation data uncertainty on hydrological calculations, particularly in regions with complex topography.