2008Journal of Hohai UniversityRequires access

Application of Kalman filter technique in real-time flood forecasting

Zhou Quan

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Abstract

Based on the Kalman filter,a technique applied in the real-time updating of flood forecasting,an alternate updating method was developed.Two Kalman filter equations of state,one for water level and one for discharge,were established and calculated alternately,and the different state variables in the filter calculation were updated jointly.A case study in part of the main stream of the Yangtze River indicates that the proposed method would help maintain the stability of hydrodynamic models for single rivers through local updating,and it is practical and effective in improving the accuracy of real-time forecasting.

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What this paper is about

Based on the Kalman filter,a technique applied in the real-time updating of flood forecasting,an alternate updating method was developed.Two Kalman filter equations of state,one for water level and one for discharge,were established and calculated alternately,and the different state variables in the filter calculation were updated jointly.A case study in part of the main stream of the Yangtze River indicates that the proposed method would help maintain the stability of hydrodynamic models for single rivers through local updating,and it is practical and effective in improving the accuracy of real-time forecasting.

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Available abstract

Based on the Kalman filter,a technique applied in the real-time updating of flood forecasting,an alternate updating method was developed.Two Kalman filter equations of state,one for water level and one for discharge,were established and calculated alternately,and the different state variables in the filter calculation were updated jointly.A case study in part of the main stream of the Yangtze River indicates that the proposed method would help maintain the stability of hydrodynamic models for single rivers through local updating,and it is practical and effective in improving the accuracy of real-time forecasting.

Key concepts: Kalman filter, Ensemble Kalman filter, Flood forecasting, Yangtze river, Computer science, Filter (signal processing), Stability (learning theory), Extended Kalman filter

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