Assessing Optimal Digital Elevation Model Selection for Active River Area Delineation Across Broad Regions

Abstract

The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data quality and methodology, ARA studies to date have not achieved effective computer-based ARA-component delineation, limiting the efficacy of the ARA framework in terms of informing riparian conservation and management. To achieve framework refinement and determine the optimal input elevation data for future ARA studies, this study tested a novel Digital Elevation Model (DEM) smoothing algorithm and assessed ARA outputs derived from a range of DEMs for accuracy and efficiency. It was found that the tested DEM smoothing algorithm allows the ARA framework to take advantage of high-resolution LiDAR DEM and considerably improves the accuracy of high-resolution LiDAR DEM derived ARA results; smoothed LiDAR DEM in 5-meter spatial resolution best balanced ARA accuracy and data processing efficiency and is ultimately recommended for future ARA delineations across large regions.

Smoothing of digital elevation models and the alteration of overland flow path length distributions

“…Each smoothing filter tested caused a straightening of flow paths in each study site, as predicted, with greater degrees of smoothing causing further generalization of flow paths. This finding is consistent with other work that demonstrates smoothing produces considerable changes in other hydrological features such as modelled flood plain area, creek and headwater flow width, and delineated streams (Ma et al, 2021; Yu et al, 2021). However, smoothing in high‐relief landscapes appears to straighten flow paths to a greater degree than smoothing in low‐relief landscapes.…”

“…Therefore, the scale of the analysis will also impact the degree of smoothing required by the application and thus the effects of smoothing on flow path length distributions. Furthermore, because the optimal DEM resolution (i.e., the resolution that produces the most accurate results) will depend on application (Ma et al, 2021), this also suggests that the choice of an appropriate smoothing filter will depend on DEM resolution. Topographic Wetness Index (Beven & Kirkby, 1979), from smoothed and unsmoothed DEMs (Gillin et al, 2015).…”