Here's a long comment that can't be put in the comment section:
If you know the location of errors in a binary system, and if errors are just bit flips, you can just flip those erroneous guys again. This ensures 100% error correction for obvious reasons. No coding theory involved. So it must be non-binary or erroneous bits become an illegal letter outside of the given alphabet.
Michael mentioned RAID5 in the comment. The error model for a RAID system is this latter kind, where a bit or digit may be flipped to a special symbol outside of the given legal letters. This kind of error is called an erasure. Here's a link to the Wikipedia article: http://en.wikipedia.org/wiki/Erasure_code.
Erasures are typically studied in the context of data storage, such as hard disks in a large server or optical media like Blu-rays. RAID Michael mentioned is a quintessential example of this. What it does is basically regard each disk as one (often non-binary) digit and encode them by a linear code. So, roughly speaking, you do the check-sum thing for the entire array of disks by seeing each node as one digit.
It might help grasp the concept if you imagine erasures as a "can't read" or "don't know what symbol" kind of error. If you come across a failed data section, you're sure it went wrong. But without any side information, you don't know if they were originally $0$, $1$, or whatever legal letter. It's just illegal data. So, you treat it as a special "can't read" section by assigning a special symbol "erasure" for this type of error.
The "located errors" you asked seem slightly different from erasures because you know which symbol each erroneous guy resulted in, although they can be corrected at least sub-optimally by optimal erasure codes. If there is a known pattern about errors (e.g., $0$ may become $1$, but $1$ never becomes $0$), knowing what symbol an erroneous bit resulted in may greatly help achieve a higher rate.
Of course, if you ask how much you can do better than traditionally studied channels, it all depends on exactly what kind of error model you consider. Since you didn't specify it, if we simply adopt the memoryless symmetrical channel, it's either trivial (i.e., the binary case of "just flip the wrong guy again") or the best possible rate is bounded from below by the capacity of the erasure channel. I don't know how large the gap in capacity is between the erasure channel and the located error channel.
There are many papers about erasures. And your textbook on coding theory may explain erasures well, too. But I haven't seen one that deals with the located error channel like you described.