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Channel friction is an important parameter in hydraulic analysis. A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed. Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the solution is hardly affected. In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state. For the nonlinear equations, computations of sensitivity matrices are time-costly. Two simplified measures can reduce computing time, but not influence the results. One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.
Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the solution is hardly affected. , Kalman Filter with unknown parameter vector is effective only at unsteady state. For the nonlinear equations, computations of sensitivity matrices are time-costly. Two simplified measures can reduce computing time, but not influence the results. One is to reduce sensitivity matrix analysis time , the other is to substitute for sensitivity matrix.