As models become larger and simulated processes become more complex, automated approaches for model development are essential. However, many aspects of the initial modeling process, such as achieving convergence or an initial calibration, benefit from a hands-on approach, particularly for large regional MODFLOW models. The deluge of data involved in manually improving convergence and calibration can mask important trends or insights. To this end, freely available toolboxes have been developed to assist modelers with manually improving calibration and convergence. Although PEST is a widely accepted for parameter estimation, modelers must still develop appropriate conceptualizations based on geologic insight. As such, manual calibration is necessary in the initial phases of model development. However, manual calibration to temporal datasets is difficult in large regional models with widely variable geology. The second toolbox reads the simulated head file as well as a target shapefile. The calibration results can then be queried by stress period, layer, and three user-defined fields. The toolbox also creates a residual error map based on the query. Large MODFLOW models will often be slowed by a few cells that have difficulty converging on a user-defined head change or residual criteria. The list file provides information on these bad actors, but can run into severe memory limitations in many text editors or word processors. This precludes the modeler from fully exploring the range of errors. The first toolbox reads the entirety of the list file and outputs the cells with the largest and the most frequent errors.
|Original language||English (US)|
|Title of host publication||Proceedings of the MODFLOW and More 2017 Conference|
|State||Published - 2017|