Articles | Volume 24, issue 7
https://doi.org/10.5194/hess-24-3451-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-3451-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sensitivity of meteorological-forcing resolution on hydrologic variables
Fadji Z. Maina
CORRESPONDING AUTHOR
Energy Geosciences Division, Lawrence Berkeley National Laboratory,
1 Cyclotron Road, M. S. 74R-316C, Berkeley, CA, 94704, USA
Erica R. Siirila-Woodburn
Energy Geosciences Division, Lawrence Berkeley National Laboratory,
1 Cyclotron Road, M. S. 74R-316C, Berkeley, CA, 94704, USA
Pouya Vahmani
Climate & Ecosystem Sciences Division, Lawrence Berkeley National
Laboratory, 1 Cyclotron Road, M. S. 74R-316C, Berkeley, CA, 94704, USA
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- The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses P. Shuai et al. 10.5194/hess-26-2245-2022
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- A low-to-no snow future and its impacts on water resources in the western United States E. Siirila-Woodburn et al. 10.1038/s43017-021-00219-y
- Assessing Integrated Hydrologic Model: From Benchmarking to Case Study in a Typical Arid and Semi-Arid Basin Z. Lu et al. 10.3390/land12030697
- Recent decreases in snow water storage in western North America K. Hale et al. 10.1038/s43247-023-00751-3
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- Impact of forcing data and land surface properties on snow simulation in a regional climate model: a case study over the Tianshan Mountains, Central Asia Q. Li et al. 10.1007/s11629-020-6621-2
- The Role of Atmospheric Rivers on Groundwater: Lessons Learned From an Extreme Wet Year E. Siirila‐Woodburn et al. 10.1029/2022WR033061
- Spatial downscaling of precipitation for hydrological modelling: Assessing a simple method and its application under climate change in Britain A. Kay et al. 10.1002/hyp.14823
- Parameter estimation and uncertainty analysis in hydrological modeling P. Herrera et al. 10.1002/wat2.1569
- Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States) U. Mital et al. 10.5194/essd-14-4949-2022
- Assessing the impacts of hydrodynamic parameter uncertainties on simulated evapotranspiration in a mountainous watershed F. Maina et al. 10.1016/j.jhydrol.2022.127620
- Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM) Z. Xu & A. Di Vittorio 10.1016/j.jhydrol.2021.126646
- Hydrological forecasting at impact scale: the integrated ParFlow hydrological model at 0.6 km for climate resilient water resource management over Germany A. Belleflamme et al. 10.3389/frwa.2023.1183642
- Deep learning in statistical downscaling for deriving high spatial resolution gridded meteorological data: A systematic review Y. Sun et al. 10.1016/j.isprsjprs.2023.12.011
- On the role of atmospheric simulations horizontal grid spacing for flood modeling F. Quintero et al. 10.1007/s00382-022-06233-0
- Projecting end-of-century climate extremes and their impacts on the hydrology of a representative California watershed F. Maina et al. 10.5194/hess-26-3589-2022
- Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin Z. Xu et al. 10.5194/hess-27-1771-2023
- Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region D. Dalla Torre et al. 10.1016/j.ejrh.2024.101718
- Effects of meteorological forcing uncertainty on high-resolution snow modeling and streamflow prediction in a mountainous karst watershed C. Tyson et al. 10.1016/j.jhydrol.2023.129304
20 citations as recorded by crossref.
- The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses P. Shuai et al. 10.5194/hess-26-2245-2022
- A review of hydrologic signatures and their applications H. McMillan 10.1002/wat2.1499
- A low-to-no snow future and its impacts on water resources in the western United States E. Siirila-Woodburn et al. 10.1038/s43017-021-00219-y
- Assessing Integrated Hydrologic Model: From Benchmarking to Case Study in a Typical Arid and Semi-Arid Basin Z. Lu et al. 10.3390/land12030697
- Recent decreases in snow water storage in western North America K. Hale et al. 10.1038/s43247-023-00751-3
- Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model W. Rudisill et al. 10.5194/gmd-16-6531-2023
- Impact of forcing data and land surface properties on snow simulation in a regional climate model: a case study over the Tianshan Mountains, Central Asia Q. Li et al. 10.1007/s11629-020-6621-2
- The Role of Atmospheric Rivers on Groundwater: Lessons Learned From an Extreme Wet Year E. Siirila‐Woodburn et al. 10.1029/2022WR033061
- Spatial downscaling of precipitation for hydrological modelling: Assessing a simple method and its application under climate change in Britain A. Kay et al. 10.1002/hyp.14823
- Parameter estimation and uncertainty analysis in hydrological modeling P. Herrera et al. 10.1002/wat2.1569
- Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States) U. Mital et al. 10.5194/essd-14-4949-2022
- Assessing the impacts of hydrodynamic parameter uncertainties on simulated evapotranspiration in a mountainous watershed F. Maina et al. 10.1016/j.jhydrol.2022.127620
- Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM) Z. Xu & A. Di Vittorio 10.1016/j.jhydrol.2021.126646
- Hydrological forecasting at impact scale: the integrated ParFlow hydrological model at 0.6 km for climate resilient water resource management over Germany A. Belleflamme et al. 10.3389/frwa.2023.1183642
- Deep learning in statistical downscaling for deriving high spatial resolution gridded meteorological data: A systematic review Y. Sun et al. 10.1016/j.isprsjprs.2023.12.011
- On the role of atmospheric simulations horizontal grid spacing for flood modeling F. Quintero et al. 10.1007/s00382-022-06233-0
- Projecting end-of-century climate extremes and their impacts on the hydrology of a representative California watershed F. Maina et al. 10.5194/hess-26-3589-2022
- Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin Z. Xu et al. 10.5194/hess-27-1771-2023
- Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region D. Dalla Torre et al. 10.1016/j.ejrh.2024.101718
- Effects of meteorological forcing uncertainty on high-resolution snow modeling and streamflow prediction in a mountainous karst watershed C. Tyson et al. 10.1016/j.jhydrol.2023.129304
Latest update: 07 Nov 2024
Short summary
Projecting the changes in water resources under a no-analog future climate requires integrated hydrologic models. However, these models are plagued by several sources of uncertainty. A hydrologic model was forced with various resolutions of meteorological forcing (0.5 to 40.5 km) to assess its sensitivity to these inputs. We show that most hydrologic variables reveal biases that are seasonally and spatially dependent, which can have serious implications for calibration and water management.
Projecting the changes in water resources under a no-analog future climate requires integrated...