Adaptive Parameter Estimation for Multisite Streamflow Forecastingby Haitham M. Awwad, Texas A & M Univ, College Station, United States,
Juan B. Valdés, Texas A & M Univ, College Station, United States,
Abstract: An adaptive procedure for parameter identification and noise statistics estimation for multisite streamflow forecasting is presented in this work. The model is a multivariate ARMAX model, formulated in a state-space form, with the Kalman filter used to obtain the optimal forecasts and updates of the states. Model parameters, as well as noise statistics, are updated on-line in an adaptive manner along with the states.
Subject Headings: Parameters (statistics) | Streamflow | Adaptive systems | Forecasting | Filters | Kalman filters
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