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Advances in real-time flood forecasting.
- Source :
-
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences [Philos Trans A Math Phys Eng Sci] 2002 Jul 15; Vol. 360 (1796), pp. 1433-50. - Publication Year :
- 2002
-
Abstract
- This paper discusses the modelling of rainfall-flow (rainfall-run-off) and flow-routeing processes in river systems within the context of real-time flood forecasting. It is argued that deterministic, reductionist (or 'bottom-up') models are inappropriate for real-time forecasting because of the inherent uncertainty that characterizes river-catchment dynamics and the problems of model over-parametrization. The advantages of alternative, efficiently parametrized data-based mechanistic models, identified and estimated using statistical methods, are discussed. It is shown that such models are in an ideal form for incorporation in a real-time, adaptive forecasting system based on recursive state-space estimation (an adaptive version of the stochastic Kalman filter algorithm). An illustrative example, based on the analysis of a limited set of hourly rainfall-flow data from the River Hodder in northwest England, demonstrates the utility of this methodology in difficult circumstances and illustrates the advantages of incorporating real-time state and parameter adaption.
Details
- Language :
- English
- ISSN :
- 1364-503X
- Volume :
- 360
- Issue :
- 1796
- Database :
- MEDLINE
- Journal :
- Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
- Publication Type :
- Academic Journal
- Accession number :
- 12804258
- Full Text :
- https://doi.org/10.1098/rsta.2002.1008