Articles | Volume 26, issue 8
https://doi.org/10.5194/hess-26-2245-2022
© Author(s) 2022. 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-26-2245-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 May 2022
Research article |
| 02 May 2022
| 02 May 2022
The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses
Pacific Northwest National Laboratory, Richland, WA 99352, USA
Xingyuan Chen
Pacific Northwest National Laboratory, Richland, WA 99352, USA
Utkarsh Mital
Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Ethan T. Coon
Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Dipankar Dwivedi
Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
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Cited
14 citations as recorded by crossref.
- Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado P. Jiang et al. 10.5194/hess-27-2621-2023
- 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
- Perceived barriers and advances in integrating earth observations with water resources modeling S. Kumar et al. 10.1016/j.rsase.2023.101119
- 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
- Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions I. Özgen-Xian et al. 10.1038/s41598-023-31925-w
- Large-sample assessment of varying spatial resolution on the streamflow estimates of the wflow_sbm hydrological model J. Aerts et al. 10.5194/hess-26-4407-2022
- Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data P. Costabile et al. 10.1029/2023WR034599
- Exploring the Critical Zone Heterogeneity and the Hydrological Diversity Using an Integrated Ecohydrological Model in Three Contrasted Long‐Term Observatories J. Ackerer et al. 10.1029/2023WR035672
- Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps U. Mital et al. 10.1175/AIES-D-22-0010.1
- The 2021 heatwave results in simultaneous but different hydrological responses over Canada west of 100°W P. Whitfield et al. 10.1016/j.jhydrol.2024.130824
- Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region D. Dalla Torre et al. 10.1016/j.ejrh.2024.101718
- Estimating changes in streamflow attributable to wildfire in multiple watersheds using a semi‐distributed watershed model R. Wells et al. 10.1002/eco.2697
- The Effect of Temporal Aggregation of Observation Data on Parameter Calibration Results and the Efficiency of Runoff Simulation: Case Study of Small Catchments (Southern Primorskii Krai, Russia) S. Lupakov et al. 10.1134/S0097807824700738
- 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
13 citations as recorded by crossref.
- Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado P. Jiang et al. 10.5194/hess-27-2621-2023
- 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
- Perceived barriers and advances in integrating earth observations with water resources modeling S. Kumar et al. 10.1016/j.rsase.2023.101119
- 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
- Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions I. Özgen-Xian et al. 10.1038/s41598-023-31925-w
- Large-sample assessment of varying spatial resolution on the streamflow estimates of the wflow_sbm hydrological model J. Aerts et al. 10.5194/hess-26-4407-2022
- Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data P. Costabile et al. 10.1029/2023WR034599
- Exploring the Critical Zone Heterogeneity and the Hydrological Diversity Using an Integrated Ecohydrological Model in Three Contrasted Long‐Term Observatories J. Ackerer et al. 10.1029/2023WR035672
- Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps U. Mital et al. 10.1175/AIES-D-22-0010.1
- The 2021 heatwave results in simultaneous but different hydrological responses over Canada west of 100°W P. Whitfield et al. 10.1016/j.jhydrol.2024.130824
- Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region D. Dalla Torre et al. 10.1016/j.ejrh.2024.101718
- Estimating changes in streamflow attributable to wildfire in multiple watersheds using a semi‐distributed watershed model R. Wells et al. 10.1002/eco.2697
- The Effect of Temporal Aggregation of Observation Data on Parameter Calibration Results and the Efficiency of Runoff Simulation: Case Study of Small Catchments (Southern Primorskii Krai, Russia) S. Lupakov et al. 10.1134/S0097807824700738
Latest update: 01 Nov 2024
Short summary
Using an integrated watershed model, we compared simulated watershed hydrologic variables driven by three publicly available gridded meteorological forcings (GMFs) at various spatial and temporal resolutions. Our results demonstrated that spatially distributed variables are sensitive to the spatial resolution of the GMF. The temporal resolution of the GMF impacts the dynamics of watershed responses. The choice of GMF depends on the quantity of interest and its spatial and temporal scales.
Using an integrated watershed model, we compared simulated watershed hydrologic variables driven...
