Contributions statistiques aux prévisions hydrométéorologiques par méthodes d’ensemble

Abstract : In this thesis, we are interested in representing and taking into account uncertainties in medium term probabilistic hydrological prediction systems.These uncertainties mainly come from two sources: (1) from the imperfection of meteorological forecasts (used as inputs to these systems) and (2) from the imperfection of the representation of the hydrological process by the rainfall-runoff simulator (RRS) (at the heart of these systems).The performance of a probabilistic forecasting system is assessed by the sharpness of its predictions conditional on its reliability. The statistical approach we follow provides a guarantee of reliability if the assumptions it implies are complied with. We are also seeking to incorporate auxilary information to get sharper.We propose, for each source of uncertainty, a method enabling this incorporation: (1) a meteorological post-processor based on the statistical property of exchangeability and enabling to take into account several (ensemble or determistic) forecasts; (2) a hydrological post-processor using the RRS state variables through a Probit model arbitrating between two interpretable hydrological regimes and thus representing an uncertainty with heterogeneous variance.These two methods demonstrate adaptability on the various application cases provided by EDF and Hydro-Québec, which are partners and funders of the project. Those methods are moreover simpler and more formal than the operational methods while demonstrating similar performances.
Document type :
Theses
Complete list of metadatas

Cited literature [270 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-01566195
Contributor : Abes Star <>
Submitted on : Thursday, July 20, 2017 - 4:56:05 PM
Last modification on : Thursday, April 11, 2019 - 9:02:24 AM

File

59013_COURBARIAUX_2017_archiva...
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01566195, version 1

Citation

Marie Courbariaux. Contributions statistiques aux prévisions hydrométéorologiques par méthodes d’ensemble. Applications [stat.AP]. Université Paris-Saclay, 2017. Français. ⟨NNT : 2017SACLA003⟩. ⟨tel-01566195⟩

Share

Metrics

Record views

5087

Files downloads

605