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

摘要

The present study describes the assimilation of river water levelobservations and the resulting improvement in flood forecasting.The Kalman Filter algorithm was built on top of a one-dimensional hydraulic modelwhich describes the Saint-Venant equations. The assimilation algorithm folds in two steps: the first one wasbased on the assumption that the upstream flow can be adjusted using athree-parameter correction; the second one consisted of directly correctingthe hydraulic state. This procedure was applied using a four-day sliding windowover the flood event. The background error covariances for water leveland discharge were represented with anisotropic correlation functions where thecorrelation length upstream of the observation points is larger than thecorrelation length downstream of the observation points.This approach was motivated by the implementation of a Kalman Filter algorithmon 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 thehydraulic state during the flood event leads to a significant improvement inthe water level and discharge in both analysis and forecast modes.