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There are numerous situations where engineers and managers need to estimate flow resistance (roughness) in natural channels. Most estimates of roughness in small streams come from humid areas. Ephemeral streams in arid and semi-arid areas have different morphology and vegetation that leads to different roughness characteristics, but roughness in this class of stream has seldom been studied. A lack of high-resolution spatial data hinders our understanding of channel form and vegetation composition. High resolution structure-from-motion (SfM)-derived point clouds allow us to estimate channel boundary roughness and quantify the influence of vegetation during bankfull flows. These point clouds show individual plants at centimetre accuracy. Firstly, a semi-supervised machine learning procedure called CANUPO was used to identify and map key geomorphic features within a series of natural channels in the Pilbara region of Western Australia. Secondly, we described the variation within these reaches and the contribution of geomorphic forms and vegetation to the overall in-channel roughness. Channel types are divided into five reach types based on presence and absence of geomorphic forms: bedrock; alluvial single channel (≥cobble or sand dominated); alluvial multithread; composed of either nascent barforms or more established; stable alluvial islands. Using this reach classification as a guide, we present estimates of Manning’s roughness within these channels drawing on an examination of 650 cross sections. The contribution of in-channel vegetation toward increasing channel roughness was investigated at bankfull flow conditions for a subset of reaches. Roughness within these channels is highly variable and established in-channel vegetation can provide between a 35–55% increase in total channel roughness across all channel types. This contribution is likely higher in shallow flows and identifies the importance of integrating vegetation and geomorphic features into restorative practices for these headwater channels. These results also guide Manning’s selection for these semi-arid river systems and contribute to the vegetation-roughness literature within a relatively understudied region.

Using Structure-from-Motion Photogrammetry to Improve Roughness Estimates for Headwater Dryland Streams in the Pilbara, Western Australia