F. Delay et al., Empirical orthogonal functions analysis applied to the inverse problem in hydrogeology: Evaluation of uncertainty and simulation of new solutions, MATH GEOL, 33(8), 2001, pp. 927-949
To fulfil the need to generate more realistic solutions, stochastic inverse
simulations in hydrogeology are now constrained on both piezometric head a
nd hydraulic conductivity data. These inverse techniques, often based on ge
ostatistics. allow modifications of an initial solution conditioned only on
hydraulic conductivity data to arrive at a final solution that also matche
s observed heads. By repeating the process as many times as necessary with
different initial solutions, one generates an ensemble of final solutions t
hereby addressing the uncertainty of the inverse problem. This requires a m
ethod able to handle the whole ensemble and to work on its relevant charact
eristics. From this standpoint, the analysis by Empirical Orthogonal Functi
ons (EOF) appears promising. The method builds an orthogonal decomposition
of the covariance matrix, calculated over the whole set of solutions, and t
he areas in space where the first functions have a greater influence corres
ponding to locations of maximum uncertainty, in the solutions. These locati
ons depend both on the hydraulic characteristics of the flow problem and on
the spatial distribution of available data. The EOF analysis is used on a
synthetic problem that mimics a possible behavior of the Culebra aquifer of
the Waste Isolation Pilot Plant (WIPP, New Mexico). The method also allows
new solutions to be generated at lower computational cost by a random comp
osition of the functions obtained by the EOF analysis. These new solutions
keep the main characteristics of the initial ensemble and because they can
be conditioned, they return very good results when they are used to solve t
he direct problem.