Residual, Error and Uncertainty Propagation Analysis

Residual Analysis

Assessing the goodness-of-fit is a crucial step in inverse modeling. If the goodness-of-fit criterion suggests that the model is an unlikely match to the data, then the estimated parameter set is bound to be meaningless. iTOUGH2 performs a detailed residual analysis which includes:

Estimation Error Analysis

The covariance matrix of the estimated parameter set is calculated to assess estimation uncertainty. The error analysis in iTOUGH2 contains the following elements:

Uncertainty Propagation Analysis

Uncertainty in the parameters entering a TOUGH2 model lead to uncertainties in the model predictions. Given the distributions of the parameters considered uncertain, iTOUGH2 calculates prediction uncertainty using one of the methods listed below. An application is described in James and Oldenburg [1997].

Top of Page | Flow Chart
Parameters | Observations | Objective Function | Minimization Algorithm | Error Analysis
Examples | Bibliography | Availability | Updates | Command Index
iTOUGH2 Home | TOUGH2 Home | ESD Home | LBNL Home

Page updated: July 12, 1999