Assessing parameter identifiability for multiple performance criteria to constrain model parameters

Reliable simulations of hydrological models require that model parameters are precisely identified. In constraining model parameters to small ranges, high parameter identifiability is achieved. In this study, it is investigated how precisely model parameters can be constrained in relation to a set of contrasting performance criteria. For this, model simulations with identical parameter samplings are carried out with a hydrological model (SWAT) applied to three contrasting catchments in Germany (lowland, mid-range mountains, alpine regions). Ten performance criteria including statistical metrics and signature measures are calculated for each model simulation. Based on the parameter identifiability that is computed separately for each performance criterion, model parameters are constrained to smaller ranges individually for each catchment. An iterative repetition of model simulations with successively constrained parameter ranges leads to more precise parameter identifiability and improves model performance. Based on these results, a more consistent handling of model parameters is achieved for model calibration.