Issue |
E3S Web Conf.
Volume 7, 2016
3rd European Conference on Flood Risk Management (FLOODrisk 2016)
|
|
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Article Number | 18002 | |
Number of page(s) | 5 | |
Section | Forecasting and warning | |
DOI | https://doi.org/10.1051/e3sconf/20160718002 | |
Published online | 20 October 2016 |
Assessing flood forecast uncertainty with fuzzy arithmetic
1 CEREMA – DtecEMF 134, rue de BEAUVAIS CS 60039, 60280 Margny Lés Compiégne CEDEX, France
2 Service de Prévision des Crues Oise-Aisne – DREAL, Champagne-Ardenne 2, bd Gambetta, 60200 Compiégne, France
a Corresponding author: bertrand.de-bruyn@cerema.fr
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. The Flood Forecasting Service of Oise and Aisne rivers, in particular, monitors the upstream watershed of the Oise at Hirson. This watershed’s area is 310 km2. Its response time is about 10 hours. Several hydrological models are calibrated for flood forecasting in this watershed and use the rainfall forecast. This method presents the advantage to be easily implemented. Moreover, it permits to be carried out in real time (for making information available to the user as quickly as possible). It provides end users Flood Forecasting (crisis managers, public) valuable information that allows everyone to better prepare its possible actions (warning, crisis preparation, safekeeping of the furniture, etc.).
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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