This command makes iTOUGH2 evaluate the sensitivity matrix without performing any optimization. By default, the scaled Jacobian matrix, i.e., the sensitivity coefficients scaled by the standard deviation of the observation and expected parameter variation, respectively, is printed to the iTOUGH2 output file:
In addition, the unscaled sensitivity coefficients can be printed by invoking subcommand >>> SENSITIVITY in block >> OUTPUT. This information can be used to identify the parameters that most strongly affect the system behavior at actual or potential observation points. Similarly, the relative information content of actual or potential observations, i.e., the contribution of each data point to the solution of the inverse problem can be evaluated. Based on this command, iTOUGH2 also calculates the covariance matrix of the estimated parameters, i.e., the estimation uncertainty under the assumption that the variances of the residuals are accurately depicted by the prior covariance matrix Czz. This information along with the global sensitivity measures (sums of absolute sensitivity coefficients) can be used to optimize the design of an experiment. It is recommended to use a relatively large perturbation factor (see command >>> PERTURB), possibly in combination with centered finite difference quotients (see command >>> CENTERED) for the purpose of sensitivity analysis.
>>> perform a SENSITIVITY analysis for test DESIGN