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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- Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region D. Dalla Torre et al. 10.1016/j.ejrh.2024.101718
- Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management D. Dwivedi et al. 10.3389/frwa.2025.1496199
- Estimating changes in streamflow attributable to wildfire in multiple watersheds using a semi‐distributed watershed model R. Wells et al. 10.1002/eco.2697
- Micro-macro–scale flood modeling in ungauged channels: Rain-on-grid approach for improving prediction accuracy with varied resolution datasets A. Kumar et al. 10.1016/j.jhydrol.2025.132862
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- Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets K. Mankin et al. 10.5194/hess-29-85-2025
- 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
22 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
- High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution B. Oloruntoba et al. 10.5194/hess-29-1659-2025
- Perceived barriers and advances in integrating earth observations with water resources modeling S. Kumar et al. 10.1016/j.rsase.2023.101119
- Влияние временной агрегации данных наблюдений на результаты калибровки параметров и эффективность моделирования стока на примере малых водосборов (юг Приморского края, Россия) С. Лупаков et al. 10.31857/S0321059624030035
- From sandstorms to deluges: assessing flood risks in Al Ain City, United Arab Emirates N. Alhosani et al. 10.1080/19475705.2024.2429735
- 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
- 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
- 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
- Spatial Downscaling of Satellite Sea Surface Wind with Soft-Sharing Multi-Task Learning Y. Yue et al. 10.3390/rs17040587
- 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
- Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management D. Dwivedi et al. 10.3389/frwa.2025.1496199
- Estimating changes in streamflow attributable to wildfire in multiple watersheds using a semi‐distributed watershed model R. Wells et al. 10.1002/eco.2697
- Micro-macro–scale flood modeling in ungauged channels: Rain-on-grid approach for improving prediction accuracy with varied resolution datasets A. Kumar et al. 10.1016/j.jhydrol.2025.132862
- Hydro-Climatic variability in the Potohar Plateau of Indus River Basin under CMIP6 climate projections A. Khan et al. 10.1007/s00704-024-05274-1
- 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
- Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets K. Mankin et al. 10.5194/hess-29-85-2025
Latest update: 11 May 2025
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...
