Ground-water model calibration and uncertainty analysis
University of Colorado
Course DescriptionModels are used extensively to evaluate ground-water systems and to predict their response to such things as changes in pumpage and proposed remediation efforts. Because many aspects of ground-water systems are unknown, most models are calibrated. Calibration commonly is achieved by trial and error alone, but these methods provide less insight than is possible. This course teaches how sensitivity analysis, nonlinear regression, and associated statistics can be used to greatly improve how data is used to calibrate and test ground-water models. For example, parameters that can not be estimated accurately and uniquely with the available data can be quickly identified. Parameter values that produce the best fit between simulated and observed hydraulic heads, concentrations, and so on can be estimated by nonlinear regression. Measures of prediction uncertainty and measures of the importance of existing and potential observations are a natural consequence of regression methods.
Prerequisites: Basic statistics, computer usage. Ideas are taught using ground-water modeling but apply to any modeling; ground-water model experience is not a prerequisite.
Teaching staffMary C. Hill Research scientist, U.S. Geological Survey, Boulder, CO. Author of MODFLOWP, the popular PCG2 solver for MODFLOW, MODFLOWP, and MODFLOW-2000, articles on the numerical methods of solvers, nonlinear regression, confidence intervals, and calibration methodology, and co-author of UCODE and MODFLOW-2000. Dr. Hill has conducted and consulted on numerous national and international ground-water investigations, including saltwater intrusion, ground-water supply and stream interaction, and evaluation of the Death Valley regional ground-water flow system, which underlies the U.S. proposed high-level nuclear waste site at Yucca Mountain. Dr. Hill has taught for 19 years and holds a Ph.D. in Civil Engineering, Princeton University.
Richard L. Cooley Research hydrologist, U.S. Geological Survey, Lakewood, CO. Authored some of the first publications on applying nonlinear regression to calibration and uncertainty analysis of ground-water models. Awarded the O.E Meinzer award of the Geological Society of America for his 1979 paper on the subject. Primary fields of research have been numerical methods, calibration, and uncertainty analysis of ground-water models; he has published on a variety of topics in hydrogeology, including variably saturated flow, geomorphology, and recharge through desert alluvial fans. Dr. Cooley has taught for 30 years and holds a Ph.D. in Geology, Pennsylvania State University.
Claudia C. Faunt Hydrologist at the U.S. Geological Survey in San Diego, California. Expert in the development of hydrogeologic models for ground-water model development using advanced three-dimensional data base and visualization methods. Dr. Faunt has used these methods extensively to analyze the Death Valley regional ground-water flow system in Nevada and California. Dr. Faunt holds a Ph.D. in Geological Engineering, Colorado School of Mines.
Program ScheduleCourse participants will learn nonlinear regression methods using the U.S. Geological Survey computer programs MODFLOW-2000, an inverse ground-water flow model that is numerically sophisticated but applies to limited situations, UCODE, a universal inverse code that can be used with any model, and MT3DMS, a forward ground-water transport program. These public domain programs are well-documented, tested, and suitable for complex field application.
Class hours will be from 12:30 to 1:45, Tuesday and Thursday, starting August 29. The course will proceed as follows:
Last Modified: August 15, 2000