Annual stream flow simulation by ARMA processes and prediction by Kalman filter

Algeria is a semi-arid country where water resources are not sufficient to cope with the important socio-economic development demands. Any sustainable development strategy is basically dependent on a rigorous management of water resources potential, which presents a true challenge to be tackled for such countries. Classic mathematical models based on time invariability and ignorance of the stochastic and non-linear nature of hydrological variables are not sufficient for simulation and prediction studies. The present study subscribes to the stochastic hydrological processes modeling and prediction in case of time-varying linear systems through adaptive Kalman filter (KF) methodology. It focuses upon stream flows as a water resources component, which is directly related to the socio-economic development meanwhile it opts for Kalman filter as principal tool of work. The main objective is the application of (KF) technique to model and predict annual streamflow volumes in Northern Algeria and the obtained results are satisfactory.