Exploring New Topography-based Subgrid Spatial Structures for Land Surface Modeling

Abstract. Topography exerts a major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, river network topology and drainage area. Land surface models with spatial structure that captures the spatial heterogeneity influenced by topography may improve representation of land surface processes. Previous studies found that land surface modeling using subbasins instead of structured grids as computational units improves scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties including surface elevation, slope and aspect. Two methods (Local and Global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the Northwestern United States. In the Global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin using different elevation ranges that also naturally accounts for slope variations. The relative merits of the two methods and subgrid structures are investigated for their capability to capture topographic heterogeneity and their implications on representations of atmospheric forcing and land cover spatial patterns. Results highlight the relative advantages of the Local method over the Global method. Comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Overall the Local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic, and vegetation variability important for land surface modeling.