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Abstract : Providing forecasts for flow rates and water levels during floods have to be associated with uncertainty
estimates. The forecast sources of uncertainty are plural. For hydrological forecasts (rainfall-runoff) performed using
a deterministic hydrological model with basic physics, two main sources can be identified. The first obvious source is
the forcing data: rainfall forecast data are supplied in real time by meteorological forecasting services to the Flood
Forecasting Service within a range between a lowest and a highest predicted discharge. These two values define an
uncertainty interval for the rainfall variable provided on a given watershed. The second source of uncertainty is
related to the complexity of the modeled system (the catchment impacted by the hydro-meteorological phenomenon),
the number of variables that may describe the problem and their spatial and time variability. The model simplifies the
system by reducing the number of variables to a few parameters. Thus it contains an intrinsic uncertainty. This model
uncertainty is assessed by comparing simulated and observed rates for a large number of hydro-meteorological
events. We propose a method based on fuzzy arithmetic to estimate the possible range of flow rates (and levels) of
water making a forecast based on possible rainfalls provided by forcing and uncertainty model. The model
uncertainty is here expressed as a range of possible values. Both rainfall and model uncertainties are combined with
fuzzy arithmetic. This method allows to evaluate the prediction uncertainty range.