Statistically derived morphological signatures of large river channels extracted from topo‐bathymetric LiDAR data

Abstract

AbstractWith the development of LiDAR technology and the availability of topo‐bathymetric data of high quality, new methods are emerging to describe and understand more accurately fluvial geomorphology. We explore the capacities of probability density functions (PDFs) of detrended dimensionless elevations extracted from digital elevation models (DEMs) to document channels morphology and configuration. These DEMs were obtained from a topo‐bathymetric LiDAR survey of 450 km performed on the middle and lower reaches of the largest river of France: the Loire River. The objective is to propose a thorough and complete method for PDF analysis in order to assess the vertical structuration of river reaches presenting various fluvial patterns. The analysis was conducted on the PDFs of active channel belt of four sites selected for the diversity of their morphological configurations (anabranching, braided, channelized and meandering). Results showed that PDFs appear to be specific of a reach and that they are useful for describing its vertical structure. The simplification with Gaussian mixture model (GMM) is effective in slicing PDF and the resulting Gaussians components are related to morphological units (MUs). The distance between Gaussian curves obtained using GMMs can be considered as an indicator of topo‐bathymetric connectivity between MUs (e.g., main and side channels) on sites presenting multichannel or channelized channel configurations. The study showed the high potential of PDF and GMM analysis in the field of fluvial geomorphology and suggests interesting developments for river management and restoration.