Abstract
An analysis of hydrological response to a multi-model approach based on an ensemble of seven snow models (SM; degree-day and mixed degree-day/energy balance models) coupled with three hydrological models (HM) is presented for a snowmelt-dominated basin in Canada. The present study aims to compare the performance and the reliability of different types of SM-HM combinations at simulating snowmelt flows over the 1961–2000 historical period. The multi-model approach also allows evaluating the uncertainties associated with the structure of the SM-HM ensemble to better predict river flows in Nordic environments. The 20-year calibration shows a satisfactory performance of the ensemble of 21 SM-HM combinations at simulating daily discharges and snow water equivalents (SWEs), with low streamflow volume biases. The validation of the ensemble of 21 SM-HM combinations is conducted over a 20-year period. Performances are similar to the calibration in simulating the daily discharges and SWEs, again with low model biases for streamflow. The spring-snowmelt-generated peak flow is captured only in timing by the ensemble of 21 SM-HM combinations. The results of specific hydrologic indicators show that the uncertainty related to the choice of the given HM in the SM-HM combinations cannot be neglected in a more quantitative manner in simulating snowmelt flows. The selection of the SM plays a larger role than the choice of the SM approach (degree-day versus mixed degree-day/energy balance) in simulating spring flows. Overall, the snow models provide a low degree of uncertainty to the total uncertainty in hydrological modeling for snow hydrology studies.
Highlights
In recent decades, important developments have been made in hydrological modeling, including growth in computational power and improved understanding of the physics of the hydrological system.This has led to higher complexity of hydrological models (HM) ranging from lumped and conceptual models to distributed physics-based models
A generally good accordance with the observations can be observed over the study basin, some apparent weaknesses of both the DD and day and energy-balance (DD/EB) models in simulating the seasonal snowpack processes can be underlined: the snow models (SM) underestimate the snow water equivalents (SWEs) during the snow accumulation period, while they overestimate the SWE over the snowmelt period, with higher differences between the models with the SM-GR4J combination
Considering these elements, our work demonstrates that the SM components are not an important source of uncertainty when compared to the entire HMs for snowmelt flow simulations over the study Nordic catchment
Summary
Important developments have been made in hydrological modeling, including growth in computational power and improved understanding of the physics of the hydrological system This has led to higher complexity of hydrological models (HM) ranging from lumped and conceptual models to distributed physics-based models. Of the most sensitive components to changing climatic conditions, evaluating how the snow models (SM) affect the streamflow simulations might contribute to a better understanding of HM structure uncertainty. This information will help to narrow the total uncertainty of hydrological modeling in impact studies
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