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Data Assimilation in River Ice Forecasting

Author(s): Steven F. Daly

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Keywords: No Keywords

Abstract: This study presents a state-space model for forecasting ice conditions and the resulting stages in rivers. The model incorporates a hydraulic component, a thermal and ice transport component, and an ice-cover progression component. The Kalman filter procedure is used to update the model with observed stages and observed position of the upstream leading edge of the ice cover. The model thereby arrives at an efficient and optimal estimate of the river ice and hydraulic conditions. The state-space model can also recursively estimate the effective channel roughness using the augmented Kalman filter procedure to account for changes in the channel roughness produced by the river ice cover and other effects. By way of an example, the state-space model is applied to the Missouri River downstream of Oahe Dam, located in Pierre, South Dakota, USA. Outflow from the dam, which is used for peaking power production, can vary between 0and 55,000 cfs in a matter of minutes to meet the demands of the electric-power grid.

DOI:

Year: 2002

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