Large-sample study of uncertainty of hydrological model components over North America

Abstract

The impacts of hydrological model components on performance and uncertainty of streamflow simulations are investigated using a multi-model approach over 698 catchments in North America. An ensemble of 180 different hydrological model structures is obtained by combining five snow models (SM), four potential evapotranspiration formulations (PET), three vertical (VFS) and three horizontal (HFS) flow rounting schemes. This study aims to first compare the multiple component combinations of SM, PET, VFS and HFS in terms of their ability at simulating streamflows for ten Köppen climate zones. A secondary goal is to evaluate the contribution of each model component to the total variance of the streamflow response according to the model structure for three streamflow metrics representing mean, high and low flows. Results indicate that there is no clear relationship between the structural and parametric complexity of the hydrological components and model performance for all three streamflow metrics. There is no single model structure which performs best in all climate zones and for all streamflow metrics. Streamflow uncertainty generated by the 180 synthetic hydrological model structures depends primarily on the metrics under study, but also on the climate zone. The evapotranspiration formulation is only critical for the mean flow metric. For the low-flow criterion, the VFS generates the most uncertainty and is therefore the most critical, whereas for the high-flow metric, performance is mostly related to the HFS component and SM for Nordic catchments. A better understanding of how hydrological model components generate uncertainty for a given climate and streamflow metric will lead to more robust model structures and therefore reduce the uncertainty of hydrological simulations.