New Topography-Based Subgrid Units Improve Land-Surface Modeling

Researchers find a way to better represent the impacts of topographic variability in modeling processes that exchange energy between land and atmosphere.

The Science

Land-surface models capable of capturing the impact of topographic variability could be better at simulating land-surface processes such as soil moisture and runoff, essential to understanding energy exchanges between land, water, and atmosphere. Exploring different approaches to represent the topographic variability within watersheds, researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) demonstrated more effective methods to divide watersheds into multiple spatial units based on their topographic characteristics.

The Impact

Researchers compared different methods to represent the topographic variability within watersheds in regions with complex terrain. They demonstrated that adopting systematic descriptions of landforms (geomorphologic concepts) in dividing watersheds into multiple spatial units improves the capability of capturing subgrid topographic variability. This method allows climatic and land-cover variability to be better represented in models with a nominal increase in computational requirements of the land-surface model


Topography exerts major control on land-surface processes through its influence on atmospheric processes, soil and vegetation properties, and river network topology and drainage area. Using a spatial structure that captures topographic variability, land-surface models may produce more accurate simulations of the terrestrial water cycle and land-atmosphere interactions. This study explored new representations of land surface by dividing watersheds into subgrid units to take advantage of the emergent patterns and scaling properties of atmospheric, hydrologic, and vegetation processes in land-surface models. Researchers developed geolocated and nongeolocated subgrid units by applying two watershed delineation methods (local and global) over the Columbia River basin in the northwestern United States. The global method combined a global surface elevation classification scheme with classifications of topographic slope and landscape orientation. The local method utilized concepts of hypsometric analysis (studying the relationship between elevation and area in a watershed) combined with the classification of landscape orientation. Because the hypsometric analysis implicitly relates elevation and slope, the local method only needs to represent subgrid variability of two topographic aspects (elevation and landscape orientation), whereas three topographic aspects (elevation, slope, and landscape orientation) are represented in the global method. Therefore, land-surface modeling using the local method is more computationally efficient. The study demonstrated that the local method improved capability of capturing topographic variability through the adoption of the hypsometric curve for delineating watersheds into multiple subgrid units.

Principal Investigator(s)

L. Ruby Leung
Pacific Northwest National Laboratory


The U.S. Department of Energy Office of Science, Biological and Environmental Research supported this research as part of the Accelerated Climate Modeling for Energy (ACME) project of the Earth System Modeling (ESM) program.


T.K. Tesfa, L.R. Leung, “Exploring New Topography-Based Subgrid Spatial Structures for Improving Land Surface Modeling.” Geoscientific Model Development 10, 873-888 (2017). [DOI: 10.5194/gmd-10-873-2017].