An inverse finite-difference method (FDM) is developed to characterise the spatially dependent components of the hydraulic conductivity tensor together with the specific storage for anisotropic materials, using 'experimental' data generated from the direct FDM. This simulated surface data serves as additional information to a genetic algorithm (GA) optimisation procedure, using a modified least squares functional, that minimises the difference between the 'experimental' data and the FDM-predicted boundary pressure and/or average hydraulic flux measurements based on current hydraulic conductivity tensor and specific storage estimates.