Rapid and objective characterization of channel morphology in a small, forested stream
Abstract. Forested, gravel bed streams possess complex channel morphologies which are difficult to objectively characterise. The spatial scale necessary to adequately capture variability in these streams is often unclear, as channels are governed by irregularly spaced features and episodic processes. This issue is compounded by the high cost and time-consuming nature of field surveys in this type of environment. In larger stream systems, remotely piloted aircraft (RPAs) have proven to be effective tools for characterizing channels at high resolutions over large spatial extents, but to date their use in small, forested streams with closed forest canopies has been limited. This paper seeks to demonstrate an objective method for characterizing channel attributes over large areas, using easily extractable data from RPA imagery collected under the forest canopy in a small (width = 10 to 15 m) stream, and to provide information on the spatial scale necessary to capture the dominant spatial morphological variability of these channels. First, the accuracy and coverage of RPAs for extracting channel data was investigated through a sub-canopy survey. From this survey data, relevant cross-sectional variables were extracted and used to characterize channel unit morphology using a principal component analysis-clustering (PCA-clustering) technique. Finally, the length scale required to capture dominant morphological variability was investigated from analysis of morphological diversity along nearly 3 km of channel. The results demonstrate that sub-canopy RPA surveys provide a viable alternative to traditional survey approaches for characterizing these systems, with 87 % coverage of the main channel stream bed. The PCA-clustering analysis provided a more objective means of classifying channel morphology with a correct classification rate of 85 %. Analysis of morphological diversity suggests that reaches of at least 15 bankfull width equivalents are required to capture the channel's dominant heterogeneity. Altogether, the results provide a precedent for using RPAs to characterize the morphology and diversity of forested streams under dense canopies.