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Section 1: Publication
Publication Type
Journal Article
Authorship
Tang, Guoqiang; Clark, Martyn P.; Knoben, Wouter J. M.; Liu, Hongli; Gharari, Shervan; Arnal, Louise; Beck, Hylke E.; Wood, Andrew W.; Newman, Andrew J.; Papalexiou, Simon Michael
Title
The Impact of Meteorological Forcing Uncertainty on Hydrological Modeling: A Global Analysis of Cryosphere Basins
Year
2023
Publication Outlet
John Wiley & Sons, Ltd, Water Resources Research, Vol. 59, Iss. 6, e2022WR033767
DOI
ISBN
ISSN
0043-1397
Citation
Tang, Guoqiang; Clark, Martyn P.; Knoben, Wouter J. M.; Liu, Hongli; Gharari, Shervan; Arnal, Louise; Beck, Hylke E.; Wood, Andrew W.; Newman, Andrew J.; Papalexiou, Simon Michael (2023) The Impact of Meteorological Forcing Uncertainty on Hydrological Modeling: A Global Analysis of Cryosphere Basins, John Wiley & Sons, Ltd, Water Resources Research, Vol. 59, Iss. 6, e2022WR033767,
https://doi.org/10.1029/2022WR033767
Abstract
Meteorological forcing is a major source of uncertainty in hydrological modeling. The recent development of probabilistic large-domain meteorological data sets enables convenient uncertainty characterization, which however is rarely explored in large-domain research. This study analyzes how uncertainties in meteorological forcing data affect hydrological modeling in 289 representative cryosphere basins by forcing the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models with precipitation and air temperature ensembles from the Ensemble Meteorological Data set for Planet Earth (EM-Earth). EM-Earth probabilistic estimates are used in ensemble simulation for uncertainty analysis. The results reveal the magnitude, spatial distribution, and scale effect of uncertainties in meteorological, snow, runoff, soil water, and energy variables. There are three main findings. (a) The uncertainties in precipitation and temperature lead to substantial uncertainties in hydrological model outputs, some of which exceed 100% of the magnitude of the output variables themselves. (b) The uncertainties of different variables show distinct scale effects caused by spatial averaging or temporal averaging. (c) Precipitation uncertainties have the dominant impact for most basins and variables, while air temperature uncertainties are also nonnegligible, sometimes contributing more to modeling uncertainties than precipitation uncertainties. We find that three snow-related variables (snow water equivalent, snowfall amount, and snowfall fraction) can be used to estimate the impact of air temperature uncertainties for different model output variables. In summary, this study provides insight into the impact of probabilistic data sets on hydrological modeling and quantifies the uncertainties in cryosphere basin modeling that stem from the meteorological forcing data.
Plain Language Summary
Section 2: Additional Information
Program Affiliations
Project Affiliations
Submitters
Publication Stage
Published
Theme
Presentation Format
Additional Information
Keywords: hydrological model; precipitation; air temperature; uncertainty; cryosphere