> omit the rows that are obviously wrong

This can skew the dataset and lead to misinterpreted results, if which rows are wrong is not completely random.

Eg if all data from a specific location (or year etc) comes wrong, then this kind of cleaning would just completely exclude this location, which depending on the context may or may not be a problem. Or if values come wrong above a specific threshold. Or any other way that the errors are not in some way randomly distributed.

Removing data is never a neutral choice, and it should always be taken into consideration (which data is removed).