Weighting climate models for hydrological projections: effects on contrasting hydroclimatic regions

Abstract

Weighting climate models has recently become a more accepted approach. However, it remains a topic of ongoing discussion, especially for analyses needed at regional scales, such as hydrological assessments. Various studies have evaluated the weighting approaches for climate simulations. Yet, few case studies have assessed the impacts of weighting climate models on streamflow projections. Additionally, the methodological and location limitations of previous studies make it difficult to extrapolate their conclusions over regions with contrasting hydroclimatic regimes, highlighting the need for further studies. Thus, this study evaluates the effects of different climate model’s weighting approaches on hydrological projections over hydrologically diverse basins. An ensemble of 24 global climate model (GCM) simulations coupled with a lumped hydrological model is used over 20 North American basins to generate 24 GCM-driven streamflow projections. Six unequal-weighting approaches, comprising temperature-, precipitation-, and streamflow-based criteria, were evaluated using an out-of-sample approach during the 1976–2005 reference period. Moreover, the unequal-weighting approaches were compared against the equal-weighting approach over the 1976–2005, 2041–2070, and 2070–2099 periods. The out-of-sample assessment showed that unequally weighted ensembles can improve the mean hydrograph representation under historical conditions compared to the common equal-weighting approach. In addition, results revealed that unequally weighting climate models not only impacted the magnitude and climate change signal, but also reduced the model response uncertainty spread of hydrological projections, particularly over rain-dominated basins. These results underline the need to further evaluate the adequacy of equally weighting climate models, especially for variables with generally larger uncertainty at regional scale.