Introducing additional information sources, such as hydrochemical signatures and water isotopes, into the model calibration has shown to be useful to enhance model robustness by increasing parameter identifiability and maintaining simulation reliability. Our study explores the added value of discharge young water fractions (F_yw, derived from the volume-weighted δ¹⁸O concentrations) on the model reliability as a calibration constraint. For this, we coupled a karst hydrological model (VarKarst) with a catchment-scale transport model (StorAge Selection (SAS) function approach) to simulate discharge δ¹⁸O concentration (δ¹⁸O_Q) and corresponding F_yw. We performed a multi-variable calibration scheme by simultaneously constraining a large model ensemble (1x10⁶ realizations) with respect to the model performance on discharge and F_yw. By searching a model output space in which the model performance on discharge and model performance on F_yw provides an optimal trade-off, we extracted hydrologically more informative model realizations. We tested our calibration approach at the Wasseralm spring, which supplies drinking water to the city of Vienna, Austria. The contribution of the information content of F_yw to the model robustness was assessed by the degree of reduction in the parameter and simulation uncertainties. Our results indicate that the inclusion of F_yw notably reduced the uncertainty in model parameters (6 parameters out of 8), simulations (14 % vs. 10 % by δ¹⁸O_Q), and water balance components for the model internal states (around 40 %). Our findings reveal that F_yw confirms the model reliability (KGE: 0.71 ± 0.01 in validation) in that it mainly reduces the parameter equifinality by providing physically more plausible and identifiable parameter sets. Therefore, F_yw is a potentially useful metric to better constrain the model outputs, thereby limiting the model uncertainty.