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Event-based models are often used for flood prediction because they require fewer data than more complex models and account for a small number of parameters. We present the performance of such a model in simulating Mediterranean floods, with a focus on the initialization and on the impact of the rainfall uncertainties on the calibration of the model. The distributed event-based parsimonious Soil Conservation Service Lag-and-Route (SCS-LR) model was applied in the Real Collobrier catchment, France, which has a very high density of raingauges. The initial condition of the model was highly correlated with predictors, such as baseflow or soil water content. A reduction in the raingauge density can markedly change the calibration of the model. As the density of raingauges is generally low in most catchments, the uncertainties associated with rainfall measurement are thus expected either to mask the actual accuracy of the model, or to alter the model parameters.