[1] "Structural noise" is a term often used to describe model-to-measurement misfit that cannot be ascribed to measurement noise and therefore must be ascribed to the imperfect nature of a numerical model as a simulator of reality. As such, it is often the dominant contributor to model-to-measurement misfit. As the name "structural noise" implies, this type of misfit is often treated as an additive term to measurement noise when assessing model parameter and predictive uncertainty. This paper inquires into the nature of defectinduced model-to-measurement misfit and provides a conceptual basis for accommodating it. It is shown that inasmuch as defect-induced model-to-measurement misfit can be characterized as "noise," this noise is likely to show a high degree of spatial and temporal correlation; furthermore, its covariance matrix may approach singularity. However, the deleterious impact of structural noise on the model calibration process may be mitigated in a variety of ways. These include adoption of a highly parameterized approach to model construction and calibration (including the strategic use of compensatory parameters where appropriate), processing of observations and their model-generated counterparts in ways that are able to filter out structural noise prior to fitting one to the other, and/or through implementation of a weighting strategy that gives prominence to observations that most resemble predictions required of a model.

Approaches in highly parameterized inversion-PEST++ Version 3, a Parameter ESTimation and uncertainty analysis software suite optimized for large environmental models: U.S. Geological Survey Techniques and Methods, book 7, chap. C12, 54 p., http://dx.doi.org/10.3133/tm7C12.

There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we now know we don't know. But there are also unknown unknowns. These are things we do not know we don't know. -Donald Rumsfeld, Former United States Secretary of DefenseWater issues-quantity and quality-are expected to

Approaches in highly parameterized inversion-PEST++, a Parameter ESTimation code optimized for large environmental models: U.S. Geological Survey Techniques and Methods, book 7, section C5, 47 p.

As part of the Comprehensive Everglades Restoration Plan (CERP), various water supply projects have been proposed in a region located between the Miami metropolitan area and the extensive regional wetland systems that are part of the Everglades or remnant Everglades. A ground water flow model of the surficial aquifer within northern Miami‐Dade County was constructed using MODFLOW to evaluate the effects of these projects on water levels in the wetlands and the underlying surficial aquifer. The new Wetlands package was used to conjunctively simulate overland flow through these wetlands and the shallow ground water system. Comparisons of simulated to measured ground water levels and wetland stages were very satisfactory, where computed and measured water levels agreed within 0.5 ft over most of the period of record at nearly all of the monitoring sites. Temporal trends in water levels were also replicated. It was concluded that the assumptions and methodologies inherent to the Wetlands package were suitable for simulating regional wetland hydrology within the Everglades area.