May 1, 2023
Research Highlight

Resolution Matters When Choosing the Meteorological Forcing for Watershed Simulations

Watershed hydrological responses are sensitive to the spatial and temporal resolution of the gridded meteorological forcing used in simulations

Generated figure showing different sized triangles covering a watershed area in different shades of blue

The resolution of the gridded meteorological forcing used in watershed models affects different watershed functions in distinct ways.

(Image by Pin Shuai | Pacific Northwest National Laboratory)

The Science                                

Meteorological forcing, including precipitation and air temperature, plays a crucial role in simulating the watershed hydrological cycle. Current process-based watershed models often require gridded meteorological forcing (GMF), available at different spatial and temporal resolutions, as an input. However, the effects of GMF resolution on simulated watershed responses are poorly understood. Scientists compared three widely available GMFs, evaluating the effects of their spatial and temporal resolution on simulated watershed responses. The findings suggest that the choice of GMF and its spatiotemporal resolution depends on the watershed function of interest. This study has important implications for model calibration and watershed management decisions.

The Impact

Watershed simulations are often driven by GMF with coarse spatial (e.g., ≥4 km) and temporal (e.g., ≥daily) resolution. This study shows that resolution matters when selecting the GMF for watershed simulations. However, the appropriate spatial and temporal resolution in the GMF depend on the measured variable of interest. Distributed variables such as snow water equivalent are more sensitive to the spatial resolution of GMF than watershed streamflow. This work can help guide researchers in their selection of GMF for modeling watershed hydrological responses.


Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (tens of meters) has become efficient and computationally affordable. These hyper-resolution watershed models require high resolution meteorological forcing as a model input to produce accurate simulated responses.

Using a high-resolution integrated watershed model, scientists compared three commonly available GMFs to study how their spatiotemporal resolution affected simulated watershed responses in a mountainous headwater watershed (the Coal Creek watershed in the headwaters of the Colorado River). By comparing various spatial (ranging from 400 m to 4 km) and temporal resolutions (ranging from hourly to daily) of GMF, the spatially distributed variables, including snow water equivalents, were found to be more sensitive to the resolution of GMF than the simulated streamflow at the watershed outlet. For example, simulated streamflow marginally worsened when the GMF spatial resolution was coarsened to 4 km (~ 30% of the watershed area) or temporal resolution was refined to sub-daily. This work highlights the importance of considering spatial and temporal resolution of GMF on watershed simulations. Resolution may have important implications for model calibration and watershed management decisions. This study used high-performance computing resources provided by the National Energy Research Scientific Computing Center.

PNNL Contact

Xingyuan Chen, Pacific Northwest National Laboratory,


This work was funded by the ExaSheds project, which was supported by the Department of Energy Office of Science, Biological and Environmental Research program, Earth and Environmental Systems Sciences Division, Data Management Program.

Published: May 1, 2023

Shuai, P., et al. 2022. “The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses.” Hydrology and Earth System Science, 26, 2245–2276. [DOI: 10.5194/hess-26-2245-2022]