How do primary and secondary information affect the results of parameter identification for groundwater modeling?

Geostatistical inverse problems always utilize both primary information and secondary information to identify subsurface parameters. Many articles investigated inverse algorithms that were used to estimate unknown parameters in a subsurface system, but few of them explore what role the primary and secondary information play and how they affect the results of parameter identification. The main theme of this article is to investigate how the results of identification are affected by head observations quantitatively and qualitatively. The cokriging technique is used as an interpolation tool for estimating unknown parameters in the system. Through several numerical examples the paper demonstrates and answers this question. Keywords: inverse problem, primary information, secondary information, cokriging technique