The present tutorial addresses the ability (or otherwise) of yet-ungathered data to reduce the uncertainties of decision-critical predictions using linear analysis utilities from the PEST suite. Data worth analysis is applied to a model which was calibrated in another GMDSI tutorial; this model was subjected to a suite of common linear analysis tasks in yet another tutorial in this series.
This tutorial is part of a series of tutorials which demonstrate workflows for parameter estimation and uncertainty analysis with the PEST/PEST++ suites. Outcomes of data worth analysis such as the one demonstrated here can easily be plotted spatially (or over time) to provide didactic guidance to collection of further data. The example shown here is relatively simple. Its purpose is to introduce you to the basics of data worth analysis undertaken using PREDUNC5. Hopefully, this tutorial may encourage you to extend its use to real-world decision-support contexts.