Influence of numerical precision on the calibration of AEM-based groundwater flow models

Groundwater modelers have embraced the use of automated calibration tools based on classical nonlinear regression techniques. While clearly an improvement over trial-and-error calibration, it is not clear to what extent these popular inverse modeling tools yield accurate parameter sets for groundwater flow models. The impact of model configuration and precision upon automated parameter estimation is also unclear. An extensive set of numerical experiments was performed to explore the influence of model configuration on the calibration of a regional groundwater flow model developed using the analytic element method. The results provided insight into the manner in which the specified level of model precision and the location of observation points influence the results of inverse modeling based on nonlinear regression. While the importance of these issues is application-specific, obtaining an accurate model calibration for the case study required both a careful placement of test observations and a greater-than-anticipated level of model precision. The required level of model precision for calibration was more than necessary to produce an acceptable flow solution.