Observation Types Accepted by iTOUGH2

Input parameters for the TOUGH2 code can be estimated based on any type of sensitive data for which a corresponding TOUGH2 output is calculated. A list of observation types currently implemented in iTOUGH2 is shown below. Furthermore, an interface routine is provided in which users can specify their own observation types. This option is especially useful for defining arbitrary cost functions for the optimization of groundwater management problems.

Each observation refers to one or more grid blocks, connections or sink/source term in the TOUGH2 model. Time-dependent or steady-state data can be provided as lists in an arbitrary format. Measurement uncertainties can be specified for each data set or individually for each data point.

The following is a list of available observation types:

Prior information: A special type of observations are measurements or prior knowledge of the parameters that are to be estimated by inverse modeling. Adding prior information to the set of observations is a way of incorporating measured parameter values (e.g., porosity and permeability measurements from core samples). Prior information can also be used for regularization purposes, i.e., to make the inverse problem well-posed.


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Page updated: July 25, 1997