A coupled rainfall-runoff and runoff-routing model for adaptive real-time flood forecasting

H. Habaïeb, P. A. Troch, F. P. De Troch

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations


This paper describes an adaptive hydrologic modelling technique for real-time flood forecasting. The modelling approach is based on a linear stochastic time-varying representation of the rainfall-runoff process and on the Muskingum routing method formulated as an optimal linear filtering problem. The most general stochastic rainfall-runoff model used for linear forecasting is known as the transfer function noise model. An on-line identification procedure based on an extension of the recursive Instrumental Variable estimator is discussed. The routing procedure, based on the Muskingum method, is written in a state-space representation. This allows real-time updating of the state and the system parameters by means of Kalman filtering. The described method is used to forecast extreme flood events for the River Ourthe (drainage basin: approx 3626 km2), one of the main tributaries of the River Meuse, Belgium. The method is compared with stationary modelling procedures and its superiority based on objective forecasting criteria is demonstrated.

Original languageEnglish (US)
Pages (from-to)47-61
Number of pages15
JournalWater Resources Management
Issue number1
StatePublished - Mar 1991


  • Kalman filter
  • Real-time flood forecasting rainfall-runoff model
  • instrumental variable estimator
  • on-line identification
  • runoff routing
  • transfer functions

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Water Science and Technology


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