Improve performance with TI data load scripts for HydroTable load

[RobHanna-NOAA]

For the current 2.1.8 Code/Manual_Workflows/(data load script specific to a version), I am actively working on loading all data.

The script is/has been very in-efficient in areas for many versions. Almost all parts are relatively quick, ie < 35 mins, and are easy to keep an eye on and validate its completion and results, easily and quickly.

However, the loading of the Hydrotables is brutal. It is run entirely in a Jupyter kernal loading 1000's of records and take 5 plus hours to complete. Even though the kernal stays running and the job continues running even after logout, it does not appear to complete updating the output panel, so I am unable to tell if it finished.

I recommend we move this to some sort of Step function system, possibly grouping them up by huc or something. We can likely use other tools like lambda or something.

Note: For learning purposes, I would like to the one to do this task but will need a lot of guidance when we get there in the new year.