>>> WORTH (PARAMETER/PREDICTION) (DETERMINANT/TRACE) (SET)
The data-worth analysis is available whenever the Jacobian matrix and estimation or prediction covariance matrices are evaluated (i.e., for sensitivity analysis and derivative-based optimization). However, since the analysis may be costly if many observations or data sets are involved, it is only executed if the number of observations is less than 500, or if the explicit purpose of the iTOUGH2 run is to perform a data-worth analysis (i.e., when command >>> WORTH (op) is specified).
This command forces iTOUGH2 to perform a data-worth analysis even if there are more than 500 observations or data sets. If keyword SET is present, the data-worth analysis is performed for entire data sets, i.e., not individual data points. It also allows the user to select the basis for the analysis. For details about the data-worth analysis, see command>>> WORTH (op). The metric used to evaluate data worth can be selected using keyword METRIC, followed by an integer that identifies the function (see separate manual).
The data worth can be printed directly or as a percentage (keyword PERCENT) of the total data worth of all actual or potential calibration points.
Background information about data-worth analysis can be found in Finsterle (Water Resour. Res., 51(12), 9904-9924, doi:10.1002/2015WR017445, 2015).
>>> print data-WORTH analysis results based on DETERMINANT of PARAMETER covariance matrix using METRIC: 0
>>> WORTH (op)