Prediction of Water Level in Tidal Inlet

A very important and difficult problem is operation of gates at the inlet of tidal lakes in order to control water quality and quantity. The gate operation must sufficiently satisfy both flood control and irrigation. As the first step to optimize a gate control, the water levels downstream of the gate are predicted by a combined model using regression theory and control theory. The prediction model consits of two parts. A regression equation is used to predict the water levels downstream of the gate by the sea levels. A Kalman filtering algorithm is employed to identify parameters used to construct the state equation in the second part. This method is applied to the prediction problems of water levels on the downstream side of the gate at the inlet of Lake Kahokufgata, Ishikawa, Japan. It is possible to predict the fluctuations of the water levels under the arbitrary gate operations with one or two hours ahead of time. The Kalman filtering algorithm with the first and second order Markov models are studied.