Flood forecasting with machine Learning, data Assimilation and Semi-pHysical modeling - IMT Mines Alès Access content directly
Conference Poster Year : 2012

Flood forecasting with machine Learning, data Assimilation and Semi-pHysical modeling

Abstract

ANR FLASH project (2009-2013) intends to capitalize on the advantages of machine learning methods in order to provide tools for real-time flash floods forecasting. In a first step, water level forecasts were provided based on rain estimation of rainfalls, leading to the design of a demonstrating software. In a second step, weather RADAR measurements will be taken in advantage, as for rainfall estimation than for directly inputs reflectivity to the model. Comparison between the 3-type of inputs (rain gauge rainfall, RADAR rainfall, COMEPHORE reanalysis) will be assessed.
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Dates and versions

hal-03341863 , version 1 (13-09-2021)

Identifiers

  • HAL Id : hal-03341863 , version 1

Cite

Yann Visserot, Guillaume Artigue, Pierre-Alain Ayral, Audrey Bornancin-Plantier, Anne Johannet, et al.. Flood forecasting with machine Learning, data Assimilation and Semi-pHysical modeling. ERAD 2012 - The 7th European Conference on radar in Meteorology and Hydrology, Jun 2012, Toulouse, France. 35, pp.178 - 189, 2012. ⟨hal-03341863⟩
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