Comparison of incoming error strings to known set and transformation into 3rd string
The inner for loops can be made easier:

match1 = max(fuzz.token_set_ratio(error, internal_error) for internal_error in error_list1)


And similar for match2 and match3.

However, the real complixity in your implementation lies in the determining of the error message to show.

I would suggest building a dictionary mapping the display error to internal errors:

def interpret_error(error):
    error_mapping = {
        "User error 1": [
            "Failure: 'mean_va' is not in list",
            "Failure: No JSON object could be decoded",
            "Failure: Expecting ':' delimiter: line 1 column 14410098 (char 14410097)",
            "Failure: cannot concatenate 'str' and 'ContentDecodingError' objects",
            "Failure: Unknown error",
            "Failure: Error returned by EPA WATERS web service: No Results Returned",
        ],
        "User error 2": [
            "Failure: Error returned by EPA WATERS web service: Flowline comid 4505568 at measure 79.99388 not found in NHDPlus stream network",
            "Failure: Error returned by EPA WATERS web service: No Catchments match navigation results",
        ],
        "User error 3": [
            "Failure: Error returned by EPA WATERS web service: Start permid must have a hydroseq greater than the hydroseq for stop permid",
            "Failure: Error returned by EPA WATERS web service: Start measure must be greater than stop measure when navigating a single reach",
        ],
    }

    display_error = None
    score = 0.0
    for message, internal_errors in error_mapping.items():
        tmp = max(fuzz.token_set_ratio(error, internal_error) for internal_error in internal_errors)

        # This matches better than any earlier internal_error.
        if tmp &gt;= score:
            score = tmp
            display_error = message

    return display_error


Ideally: move the mapping to a separate .py file, or some form of config file (.json, .yaml or even .xml), or the database.