The effect of weighting hydrological projections based on the robustness of hydrological models under a changing climate

Abstract

Study region: This study is developed in three catchments located in Denmark, France and Spain, covering different climate and physical conditions in Europe. Study focus: The simulation skill of hydrological models under contrasting climate conditions is evaluated using a Differential Split Sample Test (DSST). In each catchment, three different hydrological models are given a weight based on their simulation skill according to their robustness considering the DSST results for traditional and purpose-specific metrics. Four weighting approaches are used, each including a different set of evaluation metrics. The weights are applied to obtain reliable future projections of annual mean river discharge and purpose-specific metrics. New hydrological insights: Projections are found to be sensitive to model weightings in cases where the models show significantly different skills in the DSST. However, when the skills of the models are similar, there is no significant change when applying different weighting schemes. Nevertheless, the methodology proposed here increases the reliability of the purpose-for-fit hydrological projections in a climate change context.

Keywords

• Uncertainty
• Climate change impacts
• Model weighting
• Differential split sampling test, Bayesian model averaging