Date of Award


Document Type


Degree Name

Master of Science


Department of Operational Sciences

First Advisor

Paul F. Auclair, PhD

Second Advisor

Dave C. Coulliette, PhD


This thesis examined the effect of parameter bounding, a reduced data set, and data enrichment techniques on a response surface methodology (RSM) approach to groundwater model calibration. The four phases of the study included a calibration using a very dense data matrix, a calibration using a sparse calibration matrix, an evaluation of several data enrichment techniques, and a calibration using a data matrix enlarged with the use of the best enrichment technique. All calibrations were conducted using only a first order approximation to the response surface and with bounds placed on the input parameters. The first two calibrations using the dense and sparse data sets produced calibrated models which were very similar and very accurate. This led to the conclusion that reducing the size of the data set did not seriously degrade the calibration. The third calibration produced using the enriched data set produced results which were not as accurate as the first two calibrations and it required more calculations. Also, it was discovered that the use of a screening design would eliminate influential model parameters. All of the calibration methods provided accurate hydraulic head values, and final parameter values which were feasible.

AFIT Designator


DTIC Accession Number