The variational technique of data assimilation using adjoint equations has been illustrated using a nonlinear oceanographic shallow water model. The technique consists of minimizing a cost function representing the misfit between the model and the data subject to the model equations acting as constraints. The problem has been transformed into an unconstrained one by the use of Lagrange multipliers. Particular emphasis has been laid on finite difference formulation of the algorithm. Several numerical experiments have been conducted using simulated data obtained from a control run of the model. Implications of this technique for assimilating asynoptic satellite altimeter data into ocean models have been discussed.