3D Inverse problem: Seawater intrusions

Modeling of seawater intrusions (SWI) is challenging as it involves solving the governing equations for variable density flow, multiple time scales and varying boundary conditions. Due to the nonlinearity of the equations and the large aquifer domains, 3D computations are a costly process, particularly when solving the inverse SWI problem. In addition the heads and concentration measurements are difficult to obtain due to mixing, saline wedge location is sensitive to aquifer topography, and there is general uncertainty in initial and boundary conditions and parameters. Some of these complications can be overcome by using indirect geophysical data next to standard groundwater measurements, however, the inverse problem is usually simplified, e.g. by zonation for the parameters based on geological information, steady state substitution of the unknown initial conditions, decoupling the equations or reducing the amount of unknown parameters by covariance analysis. In our work we present a discretization of the flow and solute mass balance equations for variable groundwater (GW) flow. A finite difference scheme is to solve pressure equation and a Semi - Lagrangian method for solute transport equation. In this way we are able to choose an arbitrarily large time step without losing stability up to an accuracy requirement coming from the coupled character of the variable density flow equations. We derive analytical sensitivities of the GW model for parameters related to the porous media properties and also the initial solute distribution. Analytically derived sensitivities reduce the computational cost of inverse problem, but also give insight for maximizing information in collected data. If the geophysical data are available it also enables simultaneous calibration in a coupled hydrogeophysical framework. The 3D inverse problem was tested on artificial time dependent data for pressure and solute content coming from a GW forward model and/or geophysical forward model. Two simple scenarios were explored, first estimating a heterogeneous permeability field assuming knowledge of boundary and initial conditions, second, inverting for the initial solute content distribution given the permeability field.