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Assessing flood forecast uncertainty with fuzzy arithmetic

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.
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Contributor : Vanessya Laborie <>
Submitted on : Tuesday, April 7, 2020 - 3:52:30 PM
Last modification on : Friday, January 29, 2021 - 2:20:07 PM


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Bertrand de Bruyn, Laurence Fayet, Vanessya Laborie. Assessing flood forecast uncertainty with fuzzy arithmetic. E3S Web of Conferences, EDP Sciences, 2016, 7, pp.18002. ⟨10.1051/e3sconf/20160718002⟩. ⟨hal-02535408⟩



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