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Sample text

The developers of the landfill raise important questions about the steady-state model, so that additional data are needed. We use the steady-state model to evaluate potential new data that can be collected once the supply wells are completed, and we use the analysis in combination with field considerations to design a monitoring network. The data are collected, a transient model is produced that includes the pumping wells, and the model is recalibrated using the data from both steady-state and stressed conditions.

Two of these conditions relate to true errors, which equal the unknown amounts by which an observation or prior information equation differs from the value in the actual system. The conditions are: (1) Relevant processes, system geometry, and so on are adequately represented and simulated; (2) true errors of the observations and prior information are random and have a mean of zero; and (3) weighted true errors are independent, which means that the weighting needs to be proportional to the inverse of the variance-covariance matrix on the true observation errors (Draper and Smith, 1998, p.

An alternative but, in practice, equivalent version is derived by Burnham and Anderson (2002, p. 12). , 1993; Menke, 1989). Minimizing the L1 norm is often accomplished using the simplex method and does not require sensitivities or derivatives of the objective function. Inferential and diagnostic statistics that are derived from sensitivities and used for the sensitivity analysis, data assessment, and uncertainty evaluation described in this book can be obtained if the sensitivities are calculated separately.

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