The impact of meteorological forcing uncertainty on hydrological modeling in representative cryosphere basins on the global scale
Abstract
Meteorological forcing is a major uncertainty source in hydrological modeling. The recent development of large-scale probabilistic datasets enables convenient uncertainty characterization, which however is scarcely explored in large-domain research. This study analyzes how real-world meteorological uncertainties affect hydrological modeling in 289 globally representative cryosphere basins by forcing the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models with precipitation and air temperature estimates from the Ensemble Meteorological Dataset for Planet Earth (EM-Earth). EM-Earth deterministic estimates are used in model calibration together with satellite snow cover data, and 25-member EM-Earth probabilistic estimates are used in ensemble simulation for uncertainty analysis. The results reveal the differences in the magnitude and spatial distribution across the ensemble meteorological inputs propagate to the differences in various hydrological and energy variables. 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. Quick-response variables, such as surface runoff, tend to have larger uncertainty reduction caused by temporal averaging than slow-response variables, such as baseflow. Moreover, the uncertainties of different hydrological model output variables show distinct scale effects due to space-time averaging. This study provides insight into the utility of probabilistic datasets in hydrological modeling and reveal cryosphere basin modeling uncertainties stemming from meteorological forcing.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H15F..08T