Correction of upstream flow and hydraulic state with data assimilation in the context of flood forecasting

S Ricci (1) , A Piacentini (1) , Olivier Thual (1, 2) , E Le Pape (3) , G Jonville (1)

1 CERFACS - Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique
2 IMFT - Institut de mécanique des fluides de Toulouse
3 SCHAPI - Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations

The present study describes the assimilation of river water level observations and the resulting improvement in flood forecasting. The Kalman Filter algorithm was built on top of a one-dimensional hydraulic model which describes the Saint-Venant equations. The assimilation algorithm folds in two steps: the first one was based on the assumption that the upstream flow can be adjusted using a three-parameter correction; the second one consisted of directly correcting the hydraulic state. This procedure was applied using a four-day sliding window over the flood event. The background error covariances for water level and discharge were represented with anisotropic correlation functions where the correlation length upstream of the observation points is larger than the correlation length downstream of the observation points. This approach was motivated by the implementation of a Kalman Filter algorithm on top of a diffusive flood wave propagation model. The study was carried out on the Adour and the Marne Vallage (France) catchments. The correction of the upstream flow as well as the control of the hydraulic state during the flood event leads to a significant improvement in the water level and discharge in both analysis and forecast modes.

Mots clés: data assimilation hydraulics

Domaines: Milieux et Changements globaux

S Ricci, A Piacentini, Olivier Thual, E Le Pape, G Jonville. Correction of upstream flow and hydraulic state with data assimilation in the context of flood forecasting. Hydrology and Earth System Sciences Discussions, 2011, ⟨10.5194/hess-15-3555-2011⟩. ⟨hal-01244055⟩