Quantitative Evaluation of the Relationship between Grid Spacing of DEMs and Surface Depression Storage

Digital elevation models (DEMs) are commonly utilized for characterizing surface topography in watershed modeling. More often, DEMs can be the sole information that is used for watershed delineation, determination of flow directions and accumulations, and identification of subbasin boundaries. Thus, the resolution or grid size of the DEM data is critical. Surface depression storage is one of the primary topographic attributes and an essential hydrologic variable in watershed hydrologic modeling. Efforts have been made to evaluate the effects of grid spacing of DEMs on topographic attributes and hydrologic analyses. However, previous studies showed varied relationships between grid spacing and surface depression storage. The objective of this study is to quantitatively evaluate the effects of DEM resolutions on the computed maximum depression storage (MDS) and maximum ponding area (MPA). Six surfaces that possess varying spatial scales and microtopographic features are used in the discussion. In addition, six interpolation methods are selected and their influences on MDS also are evaluated. It is found from this in-depth study that grid pacing of DEMs affects MDS and MPA differently, depending on the characteristics of surfaces, delineation methods, and interpolation approaches used for generating the DEM data for various spatial scales.