Rainfall-runoff model parameter conditioning on regional hydrological signatures: application to ungauged basins in southern Italy

Parameter estimation for rainfall-runoff models in ungauged basins is a key aspect for a wide rangeof applications where streamflow predictions from a hydrological model can be used. The need formore reliable estimation of flow in data scarcity conditions is, in fact, thoroughly related to thenecessity of reducing uncertainty associated with parameter estimation. This study extends theapplication of a Bayesian procedure that, given a generic rainfall-runoff model, allows for theassessment of posterior parameter distribution, using a regional estimate of ‘hydrological signatures’available in ungauged basins. A set of eight catchments located in southern Italy was analyzed, andregionalized, and the first three L-moments of annual streamflow maxima were considered assignatures. Specifically, the effects of conditioning posterior model parameter distribution underdifferent sets of signatures and the role played by uncertainty in their regional estimates wereinvestigated with specific reference to the application of rainfall-runoff models in design floodestimation. For this purpose, the continuous simulation approach was employed and compared topurely statistical methods. The obtained results confirm the potential of the proposed methodologyand that the use of the available regional information enables a reduction of the uncertainty ofrainfall-runoff models in applications to ungauged basins.