The Calibration Results can be visualized by choosing a Statistical Metric Variable through the Spatial Results Toolbar. When the variable has been chosen, the subbasins on the map would be color-coded based on the range that they fall into.
To view Calibration Results, navigate to the combo box (1) in the figure below, and choose a Statistical Metric Variable.

To make edits to the Ranges and Colors, navigate to the Gear icon at (2), and a Display Settings dialog will popup. One example of the dialog are shown below.

The color scales reflect the Moriasi et. al. 2007 and 2015 performance evaluation criteria. In particular, the following criteria are used:
Below is a table showing the combined performance criteria from the two papers.
The Modified Kling-Gupta Efficiency (MKGE) (Kling et al., 2012) is also available as a calibration statistic. The Kling-Gupta Efficiency was first proposed by Gupta et al. (2009) as a multi-objective alternative to mean squared error and Nash-Sutcliffe Efficiency (NSE). MKGE can be decomposed into three terms: (1) correlation coefficient r, (2) bias ratio β, and (3) variability ratio γ. The value of MKGE gives the lower limit of the three components (r, β, γ). The value of the correlation coefficient, bias ratio, and variability ratio can be viewed in the *.results files.