Qualitatively, the knee in each curve represents the point above which noise is limited by photon statistics, and below which noise becomes more and more dominated by sensor read noise.
If you project the shot-only part of the curve as a straight line without read noise, you can clearly see that read noise robs ISO 100 of a few stops of DR. The visual experience would be even greater than that difference, IMO, as shot noise has a much more aesthetically pleasing look than read noise, and looks like a marbled texture in deep shadows areas, with blacks truly approaching black, whereas with read noise, contrast in the deep shadows is obliterated by the blanket of read noise that covers both black and near-black alike.
So, if your criterion is the range of EV over which SNR>1, that's the range of EV along the horizontal axis for which the curve is positive. For instance, 11.1 stops for ISO100 (from 2.5 to 13.6), on down to 9.2 stops for ISO 1600 -- roughly comparable to the engineering definition of DR. If you want a more stringent criterion, say SNR > 4=2^2, then that's the range above 2 on the vertical axis; this gives a DR of about 9 stops at ISO 100, etc. Direct sensor measurements are not "useless" as the first response in this thread seemed to imply; they contain all the data needed to reconstruct the camera's noise profile and signal-to-noise ratio at any exposure level.
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Just stating a single standard deviation, however, noise is not always represented properly in terms of its visibility, even with a fixed or standardized pixel viewing magnification. 1-dimensional noises are more visible than their statistical strength suggests, and low-frequency noises are, as well. Neither reduces as much as high-frequency 2-dimensional noise, either, with downsampling, binning, or decreased image display magnification.
To be thorough, these things should be taken into account as well, however, current technology is moving away from 1-dimensional and low-frequency noises, it seems.