Abstract：The solution of inverse problem usually requires nonlinear optimization of an objective function describing the difference between measured and simulated data. Most optimization algorithms used for parameter estimation in groundwater hydrology are gradient-type methods that have the disadvantages of being very sensitive to the initial guesses of parameters and being prone to converge to local minima. Compared with traditional optimization algorithms，simulated annealing algorithm is recognized to have better capability to find the global optimal solution. The inverse problem of identifying aquifer parameters is treated as a combinational optimization problem. The simulated annealing is presented to identify the transmissivity and storage coefficient for a two-dimensional unsteady state groundwater flow model. The ill-posedness of the inverse problem as characterized by instability and non-uniqueness is overcome by using simulated annealing algorithm. The effectiveness and flexibility of presented inversion technique are evaluated and compared with descent search methods.
