OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Data-driven model for river flood forecasting based on a Bayesian network approach

Boutkhamouine, Brahim and Roux, Hélène and Pérès, François Data-driven model for river flood forecasting based on a Bayesian network approach. (2020) Journal of Contingencies and Crisis Management, 28 (3). 215-227. ISSN 0966-0879

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB

Official URL: https://doi.org/10.1111/1468-5973.12316

Abstract

Uncertainty analysis of hydrological models often requires a large number of model runs, which can be time consuming and computationally intensive. In order to reduce the number of runs required for uncertainty prediction, Bayesian networks (BNs) are used to graphically represent conditional probability dependence between the set of variables characterizing a flood event. Bayesian networks (BNs) are relevant due to their capacity to handle uncertainty, combine statistical data and expertise and introduce evidences in real-time flood forecasting. In the present study, a runoff–runoff model is considered. The discharge at a gauging station located is estimated at the outlet of a basin catchment based on discharge measurements at the gauging stations upstream. The BN model shows good performances in estimating the discharges at the basin outlet. Another application of the BN model is to be used as a reverse method. Knowing discharges values at the outlet of the basin, we can propagate back these values through the model to estimate discharges at upstream stations. This turns out to be a practical method to fill the missing data in streamflow records which are critical to the sustainable management of water and the development of hydrological models.

Item Type:Article
HAL Id:hal-03164840
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Laboratory name:
Funders:
Région Midi-Pyrénées (France) - Agglomération du Grand Tarbes (France) - Université de Toulouse (France)
Statistics:download
Deposited On:10 Mar 2021 10:17

Repository Staff Only: item control page