1. Once you've seen a colored element in the graphic, you want to quickly match it to its corresponding element in a legend (or vice versa). Having distinct hue and chroma is more important for this, because lightness is so vulnerable to your brain's tendency to 'correct' it based on contextual cues.
2. Hues should be aesthetically pleasing.
3. Lightness tends to impart connotations to an visualization: class X is more important than other classes if it is substantially darker or lighter. Same goes for chroma. So one wants to bound lightness and chroma to within a specific range when using them for class labeling.
Another deep complication is color impossibility, which is another way of saying that for any reasonably perceptually uniform color space like CIELAB, there is no straight-forward parametrization of the space that is both linear and avoids impossible colors.
My gut instinct is that space-filling curves could play a greater role in parameterizing the valid portions of such color spaces. Desiderata 3 is suggestive: we want some parameter that 'wiggles' within the allowed range of lightness and chroma to achieve both good distinction between nearby parameterized colors, and good global uniformity of color and chroma.
This wiggling could also 'absorb' the 'nooks and crannies' that color impossibility produces.
Still a research project, though.