INVERSE MODELS - A NECESSARY NEXT STEP IN GROUNDWATER MODELING

Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the in sight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flo w problem to illustrate the requirements and benefits of the nonlinear least-squares regression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse mod eling include: (1) expedited determination of best fit parameter value s; (2) quantification of the (a) quality of calibration, (b) data shor tcomings and needs, and (c) confidence limits on parameter estimates a nd predictions; and (3) identification of issues that are easily overl ooked during nonautomated calibration.