Quantifying local flow direction uncertainty

Abstract

Absolute elevation error in digital elevation models (DEMs) can be within acceptable National Map Accuracy standards, but still have dramatic impacts on field-level estimates of surface water flow direction, particularly in level regions. We introduce and evaluate a new method for quantifying uncertainty in flow direction rasters derived from DEMs. The method utilizes flow direction values derived from finer resolution digital elevation data to estimate uncertainty, on a cell-by-cell basis, in flow directions derived from coarser digital elevation data. The result is a quantification and spatial distribution of flow direction uncertainty at both local and regional scales. We present an implementation of the method using a 10-m DEM and a reference 1-m lidar DEM. The method contributes to scientific understanding of DEM uncertainty propagation and modeling and can inform hydrological analyses in engineering, agriculture, and other disciplines that rely on simulations of surface water flow.

Keywords:

• DEM
• flow direction
• hydrology
• accuracy
• lidar

Notes

1. Although FF could be constrained to the boundary of C, we extended FF to the center of each member of CN because most flow-routing algorithms, including the one used is this study, base their calculations of flow direction on changes in elevation over the horizontal distance between the center point of a cell and the centers of its neighboring cells. In order to justifiably compare FLOW_C→CN and , we ensured that their predictions correspond to the same geographic space.