Assessing calibration quality
Just a heads-up—this section is still a work in progress! I’ll be revising and expanding it soon to make sure it’s as useful as possible. Curious about what’s already done or currently in the works? Check the changelog for updates.
You've gone through several iterations of adjusting parameters, running your model, and comparing results. But how do you know when your model is "good enough"? How do you objectively assess how well it's calibrated?
This section introduces the various quantitative metrics and qualitative graphical comparisons you'll use to answer these critical questions. We’ll discuss commonly used quantitative metrics, like calculating the mean error, absolute mean error, or root mean square error between modeled and observed values for pressure or flow. Another common approach is to determine the percentage of model data points that fall within a defined tolerance (e.g., +/- 2 psi or +/- 5% flow) of the corresponding field data.
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