Asher, Michael; Croke, Barry; Jakeman, Anthony; Peeters, L.J.M.
The spatially and temporally variable parameters and inputs to complex groundwater models typically result in long runtimes which hinder comprehensive calibration, sensitivity, and uncertainty analysis. Surrogate modeling aims to provide a simpler, and hence faster, model which emulates the specified output of a more complex model in function of its inputs and parameters. In this review paper, we summarize surrogate modeling techniques in three categories: data-driven, projection, and...[Show more]
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.