Improving the Robustness of the Comparison Model Method for the Identification of Hydraulic Transmissivities

The Comparison Model Method (CMM) is a relatively simple and computationally efficient direct method for the identification of the transmissivity of a confined aquifer by solution of an inverse problem. However, it suffers some of the classical drawbacks related to ill-posedness and ill-conditioning of inverse methods. Effectiveness of the CMM can be improved by some approaches. First of all, the introduction of a factor which permits to limit the negative effects of small hydraulic gradients by selection of a single parameter of the algorithm. Moreover, the CMM can be cast in a tomographic framework, i.e., by profiting of multiple sets of data, corresponding to different flow situations, produced by different boundary conditions or sources terms. Numerical tests are performed on a synthetic aquifer, by means of an open-source implementation based on the use of flopy for the solution of the forward problems. The tests show that the above mentioned approaches improve the robustness of the CMM with respect to error on the input head data.