I answered that s/he should be proficient in:
Being specific, and following the above points:
- We are looking at gvSIG (but QGIS and GRASS are good choices).
- People use are SWAT, Topkapi-X, HEC-RAS, and in Urban contexts, SWMM (see also here). I have mine JGrass-NewAGE and GEOtop that give a lot of answers that the other models do not give.
- First choice is R. Then, it could be Python that has a vibrant community (Software Carpentry, Python for hydrologists, Python for Geoscientists) (for my models I use Java -see also here- and C/C++; my colleagues use the good-old FORTRAN: but these languages have a higher degree and complexity than R and Python. The latter can be used for the 90% of hydrological tasks that do not involve specific "complex" hydrological modeling).
- Learning SQL could be necessary. Postgres plus Postgis offer a professional answer. SQlite plus Spatialite can be a handy solution. See also this post.
- On this I cannot say much. But I will add information soon.