Does Kelly work when "ruin" is not such a clear cut permanent barrier? I can be "ruined" today but have more money next payday.

This would be less a Kelly issue and more an issue of the bankroll variable you're using. Advantage gamblers generally find the concept of "sessions" meaningless - essentially, one's entire gambling career is just one long session. So if for example you have $1K per week of expendable income that you wish to use for the bankroll, and you're willing to risk that amount for a year, then you'd likely want to approach the Kelly calculation with a $52K bankroll. You would have wild swings within that year, and very short sessions when you lost (because you couldn't play again until your next paycheck), but you would still be betting the correct amount for the total risk you're willing to take.

This is also an argument for finding investments that allow you to better define the downside risk of investments. I think that this is why static investments or hedges have such value; they may not change the expected value, they might even reduce it (based on mean estimates), but they reduce / eliminate the estimation error in your downside risk, allowing you a much more certain calculation of leverage.

Insurance in general has a reduced expected value while also hedging against downside risk.

In such cases what are models that are more effective?

I don't know of anything that's guaranteed to be effective out of the box. But as a rule, simpler is better. Any assumptions should be picked apart with a fine-tooth comb and tested for robustness. But in the end, there's not a whole lot that you can do: just cross your fingers and hope.

You could probably model something that uses sampled variance less aggressively

Something bayesian