CONCEPTUALLY-BASED SHOT-NOISE MODELING OF STREAMFLOWS AT SHORT-TIME INTERVAL

A conceptual-stochastic approach to short time runoff data modelling i s proposed, according to the aim of reproducing the hydrological aspec ts of the streamflow process and of preserving as much as possible the dynamics of the process itself. This latter task implies preservation of streamflow characteristics at higher scales of aggregation and, wi thin a conceptual framework, involves compatibility with models propos ed for the runoff process at those scales. At a daily time scale the w atershed response to the effective rainfall is considered as deriving from the response of three linear reservoirs, respectively representin g contributions to streamflows of large deep aquifers, with over-year response tag, of aquifers which run dry by the end of the dry season a nd of subsurface runoff. The surface runoff component is regarded as a n uncorrelated point process. Considering the occurrences of effective rainfall events as generated by an independent Poisson process, the o utput of the linear system represents a conceptually-based multiple sh ot noise process. Model identification and parameter estimation are su pported by information related to the aggregated runoff process, in ag reement to the conceptual framework proposed, and this allows paramete r parsimony, efficient estimation and effectiveness of the streamflow reproduction. Good performances emerged from the model application and testing made with reference to some daily runoff series from Italian basins.