A NEW METHOD FOR THE IDENTIFICATION OF DISTRIBUTED TRANSMISSIVITIES

For two-dimensional groundwater flow in an isotropic confined aquifer, it has been shown elsewhere that two independent steady state sets of data, i.e., piezometric heads and source terms corresponding to diffe rent steady state flow conditions, and the value of transmissivity at one point suffice to determine transmissivity uniquely in a connected domain. The data are independent if the hydraulic gradients are not pa rallel anywhere over the domain. Here transmissivity is numerically de termined by integration of suitably approximated functions of the data along polygonal lines connecting the nodes of a lattice; integration starts from the node where transmissivity is given. The choice of the integration path is based on the results of the stability analysis and allows us to minimize the effects of the approximations on the data. Since the approximated solution is computed along internode segments, the internode transmissivities are immediately calculated without intr oducing arbitrary averages of the node transmissivities. The internode transmissivities are the quantities necessary to set up a management model within a conservative finite differences scheme. The applicabili ty of this technique to real cases is tested with two synthetic exampl es. The first one was set up by ourselves, whereas the second one has been taken from the literature. The internode transmissivities identif ied with our procedure are compared with the synthetic reference ones. The ultimate check is performed of evaluating new head fields on the basis of the identified and reference internode transmissivities. The fit is good. The relative error for the identified internode transmiss ivities is very low when error-free data are used, and it varies by an amount approximately constant over the entire aquifer when an error o n the initial value of transmissivity is introduced. The errors on the piezometric heads bear more relevance, but nonetheless, the affected results are still good.