ABSTRACT
A model is explicitly or implicitly involved in every attempted analytical solution of a problem. The model may be theoretical, such as the ideal gas law, or empirical, as in the determination of total dissolved matter. The critical relation of the model to the problem should be obvious, and decision makers must be aware of the consequences of using an incorrect one. The development of an appropriate model requires a thorough understanding of the phenomena or the system under investigation. If there are gaps in this knowledge, there could be defects in the model. Accordingly data quality objectives must be based on cost-effective considerations based on realistic needs of the problem and the capability of the measurement process. As the data quality requirements and the analytical capability approach each other, the resulting numerical data can become utterly meaningless.
