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Article Dans Une Revue E3S Web of Conferences Année : 2016

Assessing flood forecast uncertainty with fuzzy arithmetic

Résumé

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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hal-02535408 , version 1 (07-04-2020)

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