Abstract
AbstractDiscrete sensitivity analysis (DSA) is a method that efficiently estimates the derivatives of a numerically approximated objective function with respect to a set of parameters at a fraction of the cost of using finite differences. Coupled with an optimization algorithm, this method can be used to locate the optimal set of parameters for the objective function. The time dependent adjoint variable formulation of discrete sensitivity analysis is derived and applied to a time‐dependent, two‐dimensional groundwater code. The derivatives agreed with finite difference derivatives to between 6 and 8 significant digits, at approximately ⅛ the computational cost. Using the BFGS optimization algorithm to update the parameters, the parameter estimation technique successfully identified the target values, for problems with small number of parameters. Copyright © 2002 John Wiley & Sons, Ltd.
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