Parameter uncertainties of conceptual rainfall runoff (CRR) models, which are related to data and/or model structure are modeled using a fuzzy set approach. Fuzzy logic appears to be a suitable alternative to probability theory for dealing with such uncertainties. A fuzzy conceptual rainfall-runoff (FCRR)framework is proposed herein to deal with these uncertainties: every element of the CRR is assumed to be uncertain, taken here as fuzzy. After fuzzifying the CRR system, different operational modes are formulated using fuzzy rules. Furthermore, fuzzy parameter estimation is also discussed. The methodology is illustrated using the experimental two-parameter (TWOPAR) model. It is shown that the fuzzy logic framework enables the decision maker to gain insight about the model sensitivity with respect to the elements constituting the CRR model and, compared to crisp parameter estimates, fuzzy parameter estimates also appear to be more robust