This paper focuses on the identifiability problem of hydrological system modelling, taking implicit rainfall-runoff models as a target for study i.e. those models whose structures are nonlinear functions of their parameters. Because most implicit models and objective functions are very difficult as regards analytical solution or for finding high-order derivatives, a numerical analysis method is developed which not only can assess the identifiability problem but also can provide useful information for dealing with parameter optimization. The major studies involved are two-fold: (1) proposing a mathematical description and assessment method for the structural identifiability of hydrological models; and (2) providing a workable and robust identification technique using a rotating transformation of the parameter space. Using both generated error-free and watershed data in China, it has been verified that the approach is of significance and usefulness.