A multi-objective approach for calibrating the FLEXG model to improve glacio-hydrological modelling

Hydrological models as common simulation tools for water resources management play a key role in improving our understanding of hydrological processes on the catchment and global scales. The reliability of hydrological simulations depends on the model structure, the quality of input data, and the calibration of model parameters. A large number of model parameters and interactions among each hydrological variable increase the complexity of the model calibration. Multi-objective model calibration is beneficial to reduce hydrological modeling uncertainty by different calibration criteria, which can lead to more realistic simulations. The FLEX^G model is a conceptual glacio-hydrological model within the flexible modeling framework. The FLEX^G model considers the effects of topography on the spatial distribution of temperature, precipitation, and runoff generation to have a better understanding of the impacts of landscape on hydrological processes. The FLEX^G can simulate various glacio-hydrological variables such as runoff from different sources (e.g. snow and glacier melt), glacier mass balance, snow cover area, and snow water equivalent. This study aims to evaluate the influences of several calibration strategies on the FLEXG model's performance in simulating simulated runoff, snow cover area, glacier mass balance, and snow water equivalent in a glacierized catchment in Sweden. To this end, the FLEX^G model was calibrated based on remotely sensed snow cover area data and compared to the traditional calibration strategy (calibrating merely against gauged streamflow data). The FLEX^G model was also calibrated based on both gauged streamflow data and satellite snow cover area data as a multi-objective calibration. Glacio-hydrological simulations from the FLEX^G model using different calibration strategies were evaluated with multiple metrics and at different temporal scales. Results showed that calibrating the FLEX^G using only one variable (runoff or snow cover area) can provide acceptable results for only one variable, while the multi-objective calibration strategy can have acceptable simulation for both runoff and snow cover area. In addition, calibrating the FLEX^G model using only snow cover area may underestimate runoff simulation.