An iterative stochastic approach is developed to estimate transmissivity and head distributionsudin heterogeneous aquifers. This approach is similar to the classical cokriging technique and it usesuda linear estimator that depends on the covariances of transmissivity and hydraulic head and theirudcross -covariance. The linear estimator is, however, improved successively by solving the governingudflow equation and by updating the covariances and cross -covariance function of transmissivity andudhydraulic head fields in an iterative manner. As a result, the nonlinear relationship betweenudtransmissivity and head is incorporated in the estimation and the estimated fields are approximateudconditional means. The ability of the iterative approach is tested with some deterministic andudstochastic inverse problems. The results show that the estimated transmissivity and hydraulic headudfields have smaller mean square errors than those obtained by classical cokriging even in the aquiferudwith variance of transmissivity up to 3.
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