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- W2094187890 abstract "A model is developed for the prediction of river flows resulting from combined snowmelt and precipitation. The model employs a Kalman filter to reflect uncertainty both in the measured data and in the system model parameters. The forecasting algorithm is used to develop multi-day forecasts for the Sturgeon River, Ontario. The algorithm is shown to develop good 1-day and 2-day ahead forecasts, but the linear prediction model is found inadequate for longer-term forecasts. Good initial parameter estimates are shown to be essential for optimal forecasting performance. Key words: Kalman filter, streamflow forecast, multi-day, streamflow, Sturgeon River, MISP algorithm." @default.
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- W2094187890 date "1991-04-01" @default.
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- W2094187890 title "Multi-day flow forecasting using the Kalman filter" @default.
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- W2094187890 doi "https://doi.org/10.1139/l91-037" @default.
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