Watershed-Based Representation Discretized into Topographic Units Better Captures Land Surface Heterogeneity

Watershed-based representation discretized into topographic subgrid units better captured small-scale land cover, precipitation, temperature, and snow variability across multiple spatial scales.

The Science

Earth system models (ESMs) often divide land into large grid cells, but real landscapes vary over short distances as a result of differences in topography, vegetation, and weather patterns. This makes it difficult to represent important small-scale land surface variability that influences runoff, snow accumulation, and energy exchange.

The Impact

Across spatial scales, this study found that watershed-based topography-based subgrid units (TGUs) (Fig. 1) better represented patterns in topographic slope, vegetation cover, and hydrometeorology compared with grid-based TGUs, although the two approaches performed similarly for elevation. When evaluated against site observations at the finest spatial scale, watershed-based TGUs better matched observed precipitation, temperature, and snow water equivalent at most SNOwpack TELemetry (SNOTEL) sites, indicating potential advantages of watershed-based subgrid structure for improving model realism and evaluation. These findings show that watershed-based land discretization can improve how ESMs represent realistic land surface variability without requiring high grid resolution. This approach can also improve how land model performance is evaluated using site observations and help strengthen simulations of snow, water, and land-atmosphere interactions, supporting more realistic land surface representation in ESMs.

Summary

This study evaluated how well two land discretization approaches — the use of grid- and watershed-based computational units — captured land surface heterogeneity when each was further discretized into TGUs. These were derived across the continental United States at four comparable spatial scales (1°, 0.5°, 0.25°, 0.125° for grid-based, HydroBASINS levels 07-10 for watershed-based) using consistent parameters and assessed using statistical metrics for elevation, slope, vegetation cover (normalized difference vegetation index, NDVI), and surface hydrometeorological variables (precipitation, air temperature, and snow water equivalent) (Fig. 2). The results showed that watershed-based TGUs were more consistent at capturing heterogeneity linked to slope, land cover, and surface hydrometeorology across spatial scales, while both approaches were similar for elevation. This improved capability reflects the combined effects of watershed-based computational units and TGU-level discretization.

Publication

• Tesfa, T. K., Leung, L. R. & Duan, Z. Land surface heterogeneity captured by topography-based subgrid structures in grid-based and watershed-based computational units. J. Adv. Model. Earth Syst. 18, e2025MS005101 (2026). https://doi.org/10.1029/2025MS005101

Funding

• This research is supported by the Office of Science of the Department of Energy as part of the Earth System Model Development program area through the Energy Exascale Earth System Model (E3SM) project. Pacific Northwest National Laboratory is operated by Battelle for the Department of Energy under contract DE-AC05-76RL01830. The reported research used the Department of Energy’s Biological and Environmental Research Earth System Modeling program’s COMPY computing cluster, located at Pacific Northwest National Laboratory. The authors thank the two reviewers for their insightful comments, questions, and suggestions. Notice: This manuscript was authored by Battelle Memorial Institute under contract DE-AC05-76RL01830 with the Department of Energy.

Contact

• L. Ruby Leung, Pacific Northwest National Laboratory