Estimating the parameters of a monthly hydrological model using hydrological signatures
Ana Clara de Sousa Matos,
Francisco Eustáquio Oliveira e Silva,
Gustavo de Oliveira Corrêa
Abstract:In the most common Bayesian framework for estimating the parameters of a hydrological model (time domain), the specification of the likelihood function can be challenging. In addition, scarcely gauged regions might be hard to model, due to the lack of sufficient timeseries to calibrate the model. To circumvent these problems, the present study seeks to evaluate the applicability of hydrological signatures and Approximate Bayesian Computation methods to estimating the parameters and analyzing the uncertainty of… Show more
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