Model Structure Identification in Three Dimensions and Observation Design in Groundwater Modeling.

摘要

The authors have developed a methodology for optimal observation network design for parameter structure identification in groundwater modeling. The design objective is to minimize experimental cost subject to data sufficiency requirement. By incorporating the data sufficiency requirement as a constraint in the optimization model, the methodology quantitatively unifies observation network design, model structure identification, and model application reliability. They use a geostatistical simulation method to generate realizations for the real parameter field according to the available prior information. For each realization, they search for the minimum cost design that satisfies the data sufficiency requirement. After solving the design problems for each of the realizations, they then analyze the overall results. In addition, the authors combine the adjoint state method with MODFLOW for calculating sensitivity coefficients. For the remainder of the project, they will explore the possibility of generalizing the adjoint method for MODFLOW. A bibliography of 11 publications is included.