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Quantifying local flow direction uncertainty
Authors:Glenn O'Neil  Ashton Shortridge
Affiliation:1. Institute of Water Research , Michigan State University , East Lansing , MI , USA oneilg@msu.edu;3. Department of Geography , Michigan State University , East Lansing , MI , USA
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
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