Y. Honjo et N. Kashiwagi, Matching objective and subjective information in groundwater inverse analysis by Akaike's Bayesian Information Criterion, WATER RES R, 35(2), 1999, pp. 435-447
In order to overcome the illposedness of groundwater inverse analysis it is
inevitable to introduce prior information of some form and thus Bayesian s
tatistics. One of the essential problems in Bayesian inverse formulation is
the optimum matching between the objective information (i.e., the observat
ion) and the subjective information (i.e., the prior information). In this
study, Akaike's Bayesian Information Criterion (ABIC) is introduced to over
come this problem. ABIC is also effective in the model identification probl
em, and this aspect is also emphasized. The effectiveness of the method is
illustrated by analyses on an actual aquifer system. Both steady and transi
ent state analyses are carried out. The paper also provides the background
of ABIC in some detail.